Industrial Engineering and Operations Research
315 S. W. Mudd, MC 4704
212-854-2941
ieor.columbia.edu
Industrial engineering is the branch of the engineering profession that is concerned with the design, analysis, and control of production and service systems. Originally, an industrial engineer worked in a manufacturing plant and was involved only with the operating efficiency of workers and machines. Today, industrial engineers are more broadly concerned with productivity and all of the technical problems of production management and control. They may be found in every kind of organization: manufacturing, distribution, transportation, mercantile, and service. Their responsibilities range from the design of unit operations to that of controlling complete production and service systems. Their jobs involve the integration of the physical, financial, economic, computer, and human components of such systems to attain specified goals. Industrial engineering includes activities such as production planning and control; quality control; inventory, equipment, warehouse, and materials management; plant layout; and workstation design.
Operations research is concerned with quantitative decision problems, generally involving the allocation and control of limited resources. Such problems arise, for example, in the operations of industrial firms, financial institutions, health care organizations, transportation systems, and government. The operations research analyst develops and uses mathematical and statistical models to help solve these decision problems. Like engineers, they are problem formulators and solvers. Their work requires the formation of a mathematical model of a system and the analysis and prediction of the consequences of alternate modes of operating the system. The analysis may involve mathematical optimization techniques, probabilistic and statistical methods, experiments, and computer simulations.
Management Science and Engineering (also known as Engineering Management Systems) is a multidisciplinary field integrating industrial engineering, operations research, contemporary technology, business, economics, and management. It provides a foundation for decision making and managing risks in complex systems.
Financial engineering is a multidisciplinary field integrating financial theory with economics, methods of engineering, tools of mathematics, and practice of programming. The field provides training in the application of engineering methodologies and quantitative methods to finance.
Business Analytics involves the use of data science tools for solving operational and marketing problems. Students learn to leverage advanced quantitative models, algorithms, and data for making actionable decisions to improve business operations.
Current Research Activities
In industrial engineering, research is conducted in the area of logistics, routing, scheduling, production and supply chain management, inventory control, revenue management, and quality control.
In operations research, new developments are being explored in mathematical programming, combinatorial optimization, stochastic modeling, computational and mathematical finance, queueing theory, reliability, simulation, and both deterministic and stochastic network flows.
In engineering and management systems, research is conducted in the areas of logistics, supply chain optimization, and revenue and risk management.
In financial engineering, research is being carried out in portfolio management; option pricing, including exotic and real options; computational finance, such as Monte Carlo simulation and numerical methods; as well as data mining and risk management.
Projects are sponsored and supported by leading private firms and government agencies. In addition, our students and faculty are involved in the work of four research and educational centers: the Center for Applied Probability (CAP), the Center for Financial Engineering (CFE), the Computational and Optimization Research Center (CORC), and the FDT Center for Intelligent Asset Management.
The Center for Applied Probability (CAP) is a cooperative center involving the School of Engineering and Applied Science, several departments in the Graduate School of Arts and Sciences, and Columbia Business School. Its interests are in four applied areas: mathematical and computational finance, stochastic networks, logistics and distribution, and population dynamics.
The Center for Financial Engineering (CFE) at Columbia University encourages interdisciplinary research in financial engineering and mathematical modeling in finance and promoting collaboration between Columbia faculty and financial institutions, through the organization of research seminars, workshops, and the dissemination of research done by members of the Center.
The Computational Optimization Research Center (CORC) at Columbia University is an interdisciplinary group of researchers from a variety of departments on the Columbia campus. Its permanent members are Professors Daniel Bienstock, Don Goldfarb, Garud Iyengar, Jay Sethuraman, and Cliff Stein, from the Industrial Engineering and Operations Research Department, and Professor David Bayer, from the Department of Mathematics at Barnard College. Researchers at CORC specialize in the design and implementation of state-of-the-art algorithms for the solution of large-scale optimization problems arising from a wide variety of industrial and commercial applications.
The FDT Center for Intelligent Asset Management is led by Professor Xunyu Zhou at Columbia University. The Center will focus on the exploration of theoretical underpinnings and modeling strategies for financial portfolio management through the introduction of big data analytical techniques. The Center's research will combine modern portfolio theory, behavioral finance, machine learning, and data science to study core problems including optimal asset allocation and risk management; and the research of the Center sits at the crossroads of financial engineering, computer science, statistics, and finance, aiming at providing innovative and intelligent investment solutions.
Chair
Jay Sethuraman
326 S. W. Mudd
Director of Finance and Operations
Shi Yee Lee
324 S. W. Mudd
Director of Academic and Student Affairs
Carmen Ng
322A S. W. Mudd
Director of Career Placement
Lucy Mahbub
Director of Undergraduate Programs
Yi Zhang
Director of Financial Engineering
Ali Hirsa
Director of Management Science and Engineering, Business Analytics
Hardeep Johar
Director of Industrial Engineering, Operations Research
Fabrizio Lecci
Director of Doctoral Programs
Yuri Faenza
Henry Lam
Professors
Daniel Bienstock
Agostino Capponi
Donald Goldfarb
Garud Iyengar
Jay Sethuraman
Karl Sigman
Clifford Stein
David D. Yao
Xunyu Zhou
Professors of Professional Practice
Ali Hirsa
Soulaymane Kachani
Harry West
Associate Professor of Professional Practice
Fabrizio Lecci
Associate Professors
Rachel Cummings
Ton Dieker
Adam Elmachtoub
Yuri Faenza
Vineet Goyal
Daniel Lacker
Henry Lam
Assistant Professors
Anish Agarwal
Eric Balkanski
Anran Hu
Cédric Josz
Christian Kroer
Tianyi Lin
Bento Natura
Wenpin Tang
Kaizheng Wang
Senior Lecturer in Discipline
Hardeep Johar
Lecturers in Discipline
Christopher Dolan
Yaren Kaya
Uday Menon
Yi Zhang
Adjunct Faculty
Amit Arora
Luca Capriotti
Nicolas Chikhani
Krzysztof Choromanski
Naftali Cohen
Siddhartha Dastidar
Owen Davis
Kosrow Dehnad
David DeRosa
Sebastien Donadio
Tony Effik
Michelle Glaser
Leon S. Gold
Ken Goodman
Ebad Jahangir
Alireza Javaheri
Gary Kazantsev
Dave Lerner
Paul Logston
Allan Malz
Gunter Meissner
Michael Miller
Amal Moussa
Gerard Neumann
Christopher Perez
Michael Robbins
Lynn Root
Moshe Rosenwein
Ali Sadighian
Cyril Shmatov
Andrei Simion
Rodney Sunada-Wong
Maya Waisman
Nadejda Zaets
Course Descriptions
For up-to-date course offerings, please visit ieor.columbia.edu
IEME E4200 HUMAN-CENTERED DESIGN AND INNOVATION. 3.00 points.
Open to SEAS graduate and advanced undergraduate students, Business School, and GSAPP. Students from other schools may apply. Fast-paced introduction to human-centered design. Students learn the vocabulary of design methods, understanding of design process. Small group projects to create prototypes. Design of simple product, more complex systems of products and services, and design of business
Fall 2024: IEME E4200
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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IEME 4200 | 001/14537 | T 4:10pm - 5:25pm 420 Pupin Laboratories |
Harry West | 3.00 | 54/50 |
IEME 4200 | 001/14537 | T 5:25pm - 6:40pm 430 River Side Church |
Harry West | 3.00 | 54/50 |
IEME E4310 MANUFACTURING ENTERPRISE. 3.00 points.
Lect: 3.
The strategies and technologies of global manufacturing and service enterprises. Connections between the needs of a global enterprise, the technology and methodology needed for manufacturing and product development, and strategic planning as currently practiced in industry
IEME E4810 INTRO-HUMANS IN SPACE FLIGHT. 3.00 points.
Introduction to human spaceflight from a systems engineering perspective. Historical and current space programs and spacecraft. Motivation, cost, and rationale for human space exploration. Overview of space environment needed to sustain human life and health, including physiological and psychological concerns in space habitat. Astronaut selection and training processes, spacewalking, robotics, mission operations, and future program directions. Systems integration for successful operation of a spacecraft. Highlights from current events and space research, Space Shuttle, Hubble Space Telescope, and International Space Station (ISS). Includes a design project to assist International Space Station astronauts
IEOR E Fieldwork. 0 points.
IEOR E1000 Frontiers in Operations Research and Data Analytics. 1.00 point.
Introductory course for overview of modern approaches and ideas of operations research and data analytics. Through a series of interactive sessions, students engage in activities exploring OR topics with various faculty members from the IEOR department
Spring 2024: IEOR E1000
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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IEOR 1000 | 001/12883 | F 1:30pm - 2:30pm 141 Uris Hall |
Yi Zhang | 1.00 | 30/60 |
IEOR E2000 Data Engineering with Python. 3.00 points.
Introduction to essential data engineering methods. Potential topics include Arrays, Linked Lists, Stacks and Queues, Trees and Graphs, Hash Tables, Search Algorithms and Efficiency, Relational databases, SQL, NoSQL, and Data Wrangling. Practice both theory and applications using Python programming
Spring 2024: IEOR E2000
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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IEOR 2000 | 001/11815 | M W 2:40pm - 3:55pm 303 Seeley W. Mudd Building |
Yi Zhang | 3.00 | 28/50 |
IEOR E2261 ACCOUNTING AND FINANCE. 3.00 points.
Lect: 3.
Prerequisites: (ECON UN1105)
For undergraduates only. Examines the fundamental concepts of financial accounting and finance, from the perspective of both managers and investors. Key topics covered include principles of accrual accounting; recognizing and recording accounting transactions; preparation and analysis of financial statements; ratio analysis; pro-forma projections; time value of money (present values, future values and interest/discount rates); inflation; discounted-cash-flow (DCF) project evaluation methods; deterministic and probabilistic measures of risk; capital budgeting
Fall 2024: IEOR E2261
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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IEOR 2261 | 001/14531 | F 10:10am - 12:40pm 833 Seeley W. Mudd Building |
Christopher Perez | 3.00 | 119/120 |
IEOR E3106 STOCHASTIC SYSTEMS AND APPLICATIONS. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E3658) and
Some of the main stochastic models used in engineering and operations research applications: discrete-time Markov chains, Poisson processes, birth and death processes and other continuous Markov chains, renewal reward processes. Applications: queueing, reliability, inventory, and finance. IEOR E3106 must be completed by the fifth term. Only students with special academic circumstances may be allowed to take these courses in alternative semesters with the consultation of CSA and Departmental advisers
Fall 2024: IEOR E3106
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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IEOR 3106 | 001/14543 | T Th 10:10am - 11:25am 209 Havemeyer Hall |
Henry Lam | 3.00 | 82/100 |
IEOR E3402 PRODUCTN-INVENTORY PLAN-CONTRL. 4.00 points.
Lect: 3. Recit: 1.
Prerequisites: (IEOR E3608) and (IEOR E3658) and
For undergraduates only. Required for all undergraduate students majoring in IE, OR:EMS, OR:FE, and OR. Must be taken during (or before) the sixth semester. Inventory management and production planning. Continuous and periodic review models: optimal policies and heuristic solutions, deterministic and probabilistic demands. Material requirements planning. Aggregate planning of production, inventory, and work force. Multi-echelon integrated production-inventory systems. Production scheduling. Term project. Recitation section required
Spring 2024: IEOR E3402
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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IEOR 3402 | 001/11586 | M W 8:40am - 9:55am 614 Schermerhorn Hall |
Ali Sadighian | 4.00 | 57/100 |
IEOR E3404 SIMULATION MODELING AND ANALYSIS. 4.00 points.
Prerequisites: (IEOR E3658) and (IEOR E4307) and knowledge of a programming language such as Python, C, C++ or Matlab.
Corequisites: IEOR E3106
It is strongly advised that Stochastic modeling (IEOR E3106 or IEOR E4106) be taken before this course. This is an introductory course to simulation, a statistical sampling technique that uses the power of computers to study complex stochastic systems when analytical or numerical techniques do not suffice. The course focuses on discrete-event simulation, a general technique used to analyze a model over time and determine the relevant quantities of interest. Topics covered in the course include the generation of random numbers, sampling from given distributions, simulation of discrete-event systems, output analysis, variance reduction techniques, goodness of fit tests, and the selection of input distributions. The first half of the course is oriented toward the design and implementation of algorithms, while the second half is more theoretical in nature and relies heavily on material covered in prior probability courses. The teaching methodology consists of lectures, recitations, weekly homework, and both in-class and take-home exams. Homework almost always includes a programming component for which students are encouraged to work in teams
Spring 2024: IEOR E3404
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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IEOR 3404 | 001/11816 | T Th 10:10am - 11:25am 303 Seeley W. Mudd Building |
Christopher Dolan | 4.00 | 79/73 |
IEOR E3608 FOUNDATIONS OF OPTIMIZATION. 3.00 points.
Lect: 3.
Prerequisites: (MATH UN2010)
Corequisites: COMS W3134,COMS W3137
This first course in optimization focuses on theory and applications of linear optimization, network optimization, and dynamic programming
Fall 2024: IEOR E3608
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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IEOR 3608 | 001/14547 | M W 8:40am - 9:55am 833 Seeley W. Mudd Building |
Eric Balkanski | 3.00 | 81/100 |
IEOR E3609 ADVANCED OPTIMIZATION. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E3608)
For undergraduates only. Required for all undergraduate students majoring in IE, OR:EMS, OR:FE, and OR. This is a follow-up to IEOR E3608 and will cover advanced topics in optimization, including integer optimization, convex optimization, and optimization under uncertainty, with a strong focus on modeling, formulations, and applications
Spring 2024: IEOR E3609
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 3609 | 001/11817 | M W 4:10pm - 5:25pm 303 Seeley W. Mudd Building |
Jay Sethuraman | 3.00 | 65/73 |
IEOR E3658 PROBABILITY FOR ENGINEERS. 3.00 points.
Lect: 3.
Prerequisites: Solid knowledge of calculus, including multiple variable integration.
Introductory course to probability theory and does not assume any prior knowledge of subject. Teaches foundations required to use probability in applications, but course itself is theoretical in nature. Basic definitions and axioms of probability and notions of independence and conditional probability introduced. Focus on random variables, both continuous and discrete, and covers topics of expectation, variance, conditional distributions, conditional expectation and variance, and moment generating functions. Also Central Limit Theorem for sums of random variables. Consists of lectures, recitations, weekly homework, and in-class exams
Spring 2024: IEOR E3658
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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IEOR 3658 | 001/11818 | T Th 10:10am - 11:25am 310 Fayerweather |
Daniel Lacker | 3.00 | 83/96 |
Fall 2024: IEOR E3658
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 3658 | 001/14551 | T Th 10:10am - 11:25am 303 Seeley W. Mudd Building |
Daniel Lacker | 3.00 | 103/120 |
IEOR E3700 Research Immersion in OR and Data Analytics. 3.00 points.
An overview of active research areas in Operations Research and Data Analytics, and an introduction to the essential components of research studies. This course helps students develop fundamental research skills, including paper reading, problem formulation, problem-solving, scientific writing, and research presentation. Classes are in seminar format, with students analyzing research papers, developing research projects, and presenting research findings
Spring 2024: IEOR E3700
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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IEOR 3700 | 001/11819 | T Th 2:40pm - 3:55pm 609 Hamilton Hall |
Eric Balkanski | 3.00 | 13/35 |
IEOR E3899 Research Training. 0.00 points.
Research training course. Recommended in preparation for laboratory related research
IEOR S3900 UNDERGRAD RESEARCH OR PROJECT. 1.00-3.00 points.
IEOR E3900 UNDERGRAD RESEARCH OR PROJECT. 1.00-3.00 points.
Prerequisites: approval by a faculty member who agrees to supervise the work.
Independent work involving experiments, computer programming, analytical investigation, or engineering design
Spring 2024: IEOR E3900
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 3900 | 001/11712 | |
Anish Agarwal | 1.00-3.00 | 0/40 |
IEOR 3900 | 002/11713 | |
Shipra Agrawal | 1.00-3.00 | 0/40 |
IEOR 3900 | 003/11715 | |
Eric Balkanski | 1.00-3.00 | 0/40 |
IEOR 3900 | 004/11716 | |
Daniel Bienstock | 1.00-3.00 | 0/40 |
IEOR 3900 | 005/11718 | |
Agostino Capponi | 1.00-3.00 | 0/40 |
IEOR 3900 | 006/11719 | |
Rachel Cummings | 1.00-3.00 | 0/40 |
IEOR 3900 | 007/11721 | |
Antonius Dieker | 1.00-3.00 | 0/40 |
IEOR 3900 | 008/11723 | |
Christopher Dolan | 1.00-3.00 | 0/40 |
IEOR 3900 | 009/11724 | |
Adam Elmachtoub | 1.00-3.00 | 0/40 |
IEOR 3900 | 010/11725 | |
Yuri Faenza | 1.00-3.00 | 1/40 |
IEOR 3900 | 011/11726 | |
Donald Goldfarb | 1.00-3.00 | 0/40 |
IEOR 3900 | 012/11727 | |
Vineet Goyal | 1.00-3.00 | 0/40 |
IEOR 3900 | 013/11728 | |
Ali Hirsa | 1.00-3.00 | 2/40 |
IEOR 3900 | 014/11729 | |
Garud Iyengar | 1.00-3.00 | 0/40 |
IEOR 3900 | 015/11730 | |
Hardeep Johar | 1.00-3.00 | 0/40 |
IEOR 3900 | 016/11731 | |
Cedric Josz | 1.00-3.00 | 0/40 |
IEOR 3900 | 017/11732 | |
Soulaymane Kachani | 1.00-3.00 | 7/40 |
IEOR 3900 | 018/11733 | |
Yaren Kaya | 1.00-3.00 | 3/40 |
IEOR 3900 | 019/11734 | |
Christian Kroer | 1.00-3.00 | 0/40 |
IEOR 3900 | 020/11735 | |
Daniel Lacker | 1.00-3.00 | 3/40 |
IEOR 3900 | 021/11737 | |
Henry Lam | 1.00-3.00 | 0/40 |
IEOR 3900 | 022/11740 | |
Fabrizio Lecci | 1.00-3.00 | 0/40 |
IEOR 3900 | 023/11741 | |
Uday Menon | 1.00-3.00 | 0/40 |
IEOR 3900 | 024/11742 | |
Jay Sethuraman | 1.00-3.00 | 2/40 |
IEOR 3900 | 025/11743 | |
Karl Sigman | 1.00-3.00 | 0/40 |
IEOR 3900 | 026/11744 | |
Clifford Stein | 1.00-3.00 | 0/40 |
IEOR 3900 | 027/11746 | |
Wenpin Tang | 1.00-3.00 | 0/40 |
IEOR 3900 | 028/11750 | |
Kaizheng Wang | 1.00-3.00 | 0/40 |
IEOR 3900 | 029/11754 | |
David Yao | 1.00-3.00 | 0/40 |
IEOR 3900 | 030/11755 | |
Yi Zhang | 1.00-3.00 | 11/40 |
IEOR 3900 | 031/11757 | |
Xunyu Zhou | 1.00-3.00 | 0/40 |
IEOR 3900 | 032/11711 | |
Cindy Borgen, Carmen Ng | 1.00-3.00 | 2/40 |
Summer 2024: IEOR E3900
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 3900 | 001/12371 | |
Anish Agarwal | 1.00-3.00 | 0/40 |
IEOR 3900 | 002/12372 | |
Shipra Agrawal | 1.00-3.00 | 0/40 |
IEOR 3900 | 003/12378 | |
Eric Balkanski | 1.00-3.00 | 0/40 |
IEOR 3900 | 004/12379 | |
Daniel Bienstock | 1.00-3.00 | 0/40 |
IEOR 3900 | 005/12381 | |
Agostino Capponi | 1.00-3.00 | 0/40 |
IEOR 3900 | 006/12385 | |
Rachel Cummings | 1.00-3.00 | 0/40 |
IEOR 3900 | 007/12387 | |
Antonius Dieker | 1.00-3.00 | 0/40 |
IEOR 3900 | 008/12391 | |
Christopher Dolan | 1.00-3.00 | 0/40 |
IEOR 3900 | 009/12396 | |
Adam Elmachtoub | 1.00-3.00 | 0/40 |
IEOR 3900 | 010/12399 | |
Yuri Faenza | 1.00-3.00 | 0/40 |
IEOR 3900 | 011/12402 | |
Donald Goldfarb | 1.00-3.00 | 0/40 |
IEOR 3900 | 012/12380 | |
Vineet Goyal | 1.00-3.00 | 0/40 |
IEOR 3900 | 013/12376 | |
Ali Hirsa | 1.00-3.00 | 0/40 |
IEOR 3900 | 014/12389 | |
Anran Hu | 1.00-3.00 | 0/40 |
IEOR 3900 | 015/12384 | |
Garud Iyengar | 1.00-3.00 | 0/40 |
IEOR 3900 | 016/12392 | |
Hardeep Johar | 1.00-3.00 | 0/40 |
IEOR 3900 | 017/12398 | |
Cedric Josz | 1.00-3.00 | 0/40 |
IEOR 3900 | 018/12397 | |
Soulaymane Kachani | 1.00-3.00 | 0/40 |
IEOR 3900 | 019/12400 | |
Yaren Kaya | 1.00-3.00 | 0/40 |
IEOR 3900 | 020/12401 | |
Christian Kroer | 1.00-3.00 | 0/40 |
IEOR 3900 | 021/12406 | |
Daniel Lacker | 1.00-3.00 | 0/40 |
IEOR 3900 | 022/12410 | |
Henry Lam | 1.00-3.00 | 0/40 |
IEOR 3900 | 023/12374 | |
Fabrizio Lecci | 1.00-3.00 | 0/40 |
IEOR 3900 | 024/12375 | |
Tianyi Lin | 1.00-3.00 | 0/40 |
IEOR 3900 | 025/12377 | |
Jay Sethuraman | 1.00-3.00 | 0/40 |
IEOR 3900 | 026/12382 | |
Karl Sigman | 1.00-3.00 | 0/40 |
IEOR 3900 | 027/12383 | |
Clifford Stein | 1.00-3.00 | 0/40 |
IEOR 3900 | 028/12386 | |
Wenpin Tang | 1.00-3.00 | 0/40 |
IEOR 3900 | 029/12388 | |
Kaizheng Wang | 1.00-3.00 | 0/40 |
IEOR 3900 | 030/12390 | |
David Yao | 1.00-3.00 | 0/40 |
IEOR 3900 | 031/12393 | |
Yi Zhang | 1.00-3.00 | 1/40 |
IEOR 3900 | 032/12394 | |
Xunyu Zhou | 1.00-3.00 | 0/40 |
IEOR 3900 | 033/12395 | |
Cindy Borgen, Carmen Ng | 1.00-3.00 | 0/40 |
Fall 2024: IEOR E3900
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 3900 | 001/11766 | |
Anish Agarwal | 1.00-3.00 | 0/40 |
IEOR 3900 | 002/11767 | |
Shipra Agrawal | 1.00-3.00 | 0/40 |
IEOR 3900 | 003/11768 | |
Eric Balkanski | 1.00-3.00 | 0/40 |
IEOR 3900 | 004/11769 | |
Daniel Bienstock | 1.00-3.00 | 0/40 |
IEOR 3900 | 005/11770 | |
Agostino Capponi | 1.00-3.00 | 0/40 |
IEOR 3900 | 006/11772 | |
Rachel Cummings | 1.00-3.00 | 0/40 |
IEOR 3900 | 007/11776 | |
Antonius Dieker | 1.00-3.00 | 0/40 |
IEOR 3900 | 008/11779 | |
Christopher Dolan | 1.00-3.00 | 0/40 |
IEOR 3900 | 009/11781 | |
Adam Elmachtoub | 1.00-3.00 | 0/40 |
IEOR 3900 | 010/11782 | |
Yuri Faenza | 1.00-3.00 | 0/40 |
IEOR 3900 | 011/11783 | |
Donald Goldfarb | 1.00-3.00 | 0/40 |
IEOR 3900 | 012/11785 | |
Vineet Goyal | 1.00-3.00 | 0/40 |
IEOR 3900 | 013/11787 | |
Ali Hirsa | 1.00-3.00 | 0/40 |
IEOR 3900 | 014/11788 | |
Anran Hu | 1.00-3.00 | 0/40 |
IEOR 3900 | 015/11789 | |
Garud Iyengar | 1.00-3.00 | 0/40 |
IEOR 3900 | 016/11791 | |
Hardeep Johar | 1.00-3.00 | 0/40 |
IEOR 3900 | 017/11793 | |
Cedric Josz | 1.00-3.00 | 0/40 |
IEOR 3900 | 018/11794 | |
Soulaymane Kachani | 1.00-3.00 | 5/40 |
IEOR 3900 | 019/11796 | |
Yaren Kaya | 1.00-3.00 | 4/40 |
IEOR 3900 | 020/11798 | |
Christian Kroer | 1.00-3.00 | 0/40 |
IEOR 3900 | 021/11807 | |
Daniel Lacker | 1.00-3.00 | 0/40 |
IEOR 3900 | 022/11806 | |
Henry Lam | 1.00-3.00 | 0/40 |
IEOR 3900 | 023/11805 | |
Fabrizio Lecci | 1.00-3.00 | 0/40 |
IEOR 3900 | 024/11804 | |
Tianyi Lin | 1.00-3.00 | 0/40 |
IEOR 3900 | 025/11801 | |
Jay Sethuraman | 1.00-3.00 | 0/40 |
IEOR 3900 | 026/11800 | |
Karl Sigman | 1.00-3.00 | 0/40 |
IEOR 3900 | 027/11799 | |
Clifford Stein | 1.00-3.00 | 0/40 |
IEOR 3900 | 028/11795 | |
Wenpin Tang | 1.00-3.00 | 0/40 |
IEOR 3900 | 029/11792 | |
Kaizheng Wang | 1.00-3.00 | 0/40 |
IEOR 3900 | 030/11790 | |
David Yao | 1.00-3.00 | 0/40 |
IEOR 3900 | 031/11786 | |
Yi Zhang | 1.00-3.00 | 1/40 |
IEOR 3900 | 032/11784 | |
Xunyu Zhou | 1.00-3.00 | 0/40 |
IEOR 3900 | 033/11778 | |
Carmen Ng, Cindy Borgen | 1.00-3.00 | 0/40 |
IEOR E3999 FIELDWORK. 1.00-2.00 points.
1-1.5 pts. (up to 2 pts. summer only)
Prerequisites: Obtained internship and approval from faculty advisor.
Final reports are required. This course may not be taken for pass/fail credit or audited
Spring 2024: IEOR E3999
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 3999 | 001/11674 | |
Cindy Borgen, Yi Zhang | 1.00-2.00 | 3/50 |
Summer 2024: IEOR E3999
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 3999 | 001/12346 | |
Cindy Borgen, Yi Zhang | 1.00-2.00 | 21/200 |
Fall 2024: IEOR E3999
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 3999 | 001/18864 | |
Yi Zhang, Cindy Borgen | 1.00-2.00 | 3/40 |
IEOR E4001 DESIGN/MGT OF PROD/SERV SYSTMS. 3.00 points.
IEOR E4003 CORPORATE FINANCE FOR ENGINEERS. 3.00 points.
Lect: 3.
Introduction to the economic evaluation of industrial projects. Economic equivalence and criteria. Deterministic approaches to economic analysis. Multiple projects and constraints. Analysis and choice under risk and uncertainty
Fall 2024: IEOR E4003
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4003 | 001/14555 | Th 7:10pm - 9:40pm 207 Mathematics Building |
Maya Waisman | 3.00 | 82/100 |
IEOR E4004 OPTIMIZATION MODELS AND METHODS. 3.00 points.
Lect: 3.
A graduate course only for MS&E, IE, and OR students. This is also required for students in the Undergraduate Advanced Track. For students who have not studied linear programming. Some of the main methods used in IEOR applications involving deterministic models: linear programming, the simplex method, nonlinear, integer and dynamic programming
Spring 2024: IEOR E4004
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4004 | 001/11679 | M W 2:40pm - 3:55pm 614 Schermerhorn Hall |
Daniel Bienstock | 3.00 | 109/110 |
IEOR 4004 | 002/11682 | M W 4:10pm - 5:25pm 833 Seeley W. Mudd Building |
Daniel Bienstock | 3.00 | 81/110 |
Fall 2024: IEOR E4004
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4004 | 001/14539 | M W 4:10pm - 5:25pm 209 Havemeyer Hall |
Yaren Kaya | 3.00 | 110/110 |
IEOR 4004 | 002/14544 | M W 10:00am - 11:25am 207 Mathematics Building |
Yaren Kaya | 3.00 | 91/110 |
IEOR 4004 | 003/14546 | M W 11:40am - 12:55pm 833 Seeley W. Mudd Building |
Yuri Faenza | 3.00 | 96/96 |
IEOR 4004 | V01/17632 | |
Yaren Kaya | 3.00 | 5/99 |
IEOR E4007 OPT MODELS & METHODS FOR FE. 3.00 points.
Lect: 3.
Prerequisites: Linear algebra.
Linear, quadratic, nonlinear, dynamic, and stochastic programming. Some discrete optimization techniques will also be introduced. The theory underlying the various optimization methods is covered. The emphasis is on modeling and the choice of appropriate optimization methods. Applications from financial engineering are discussed
Fall 2024: IEOR E4007
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4007 | 001/14548 | M W 10:10am - 11:25am 428 Pupin Laboratories |
Tianyi Lin | 3.00 | 125/140 |
IEOR 4007 | V01/21433 | |
Tianyi Lin | 3.00 | 0/99 |
IEOR E4008 COMPUTATION DISCRETE OPT. 3.00 points.
Not offered during 2023-2024 academic year.
Discrete optimization problems. Mathematical techniques and testing strengths and limits in practice on relevant applications. Transportation (travelling salesman and vehicle routing) and matching (online advertisement and school allocation) problems
Spring 2024: IEOR E4008
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4008 | 001/11683 | M W 10:10am - 11:25am 415 Schapiro Cepser |
Yuri Faenza | 3.00 | 19/40 |
IEOR E4009 NON-LINEAR OPTIMIZATION. 3.00 points.
Lect.: 2.5.Not offered during 2023-2024 academic year.
Prerequisites: A course on optimization models and methods (at the level of IEOR 4004) and a course on linear algebra.
Unconstrained and constrained nonlinear optimization involving continuous functions. Additionally, fundamental concepts such as optimality conditions and convergence, principle focus on practical optimization methods
IEOR E4100 STATISTICS & SIMULATION. 1.50 point.
Lecture 1.5
Prerequisites: Understanding of single- and multi-variable calculus.
Probability and simulation. Statistics building on knowledge in probability and simulation. Point and interval estimation, hypothesis testing, and regression. A specialized version of IEOR E4150 for MSE and MSBA students who are exempt from the first half of IEOR E4101. Must obtain waiver for E4101
Fall 2024: IEOR E4100
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4100 | 003/14607 | M W 2:40pm - 3:55pm 451 Computer Science Bldg |
Yi Zhang | 1.50 | 11/20 |
IEOR E4101 PROBABILITY STAT & SIMULATION. 3.00 points.
Prerequisites: Understanding of singe and multi-variable calculus.
Basic probability theory, including independence and conditioning, discrete and continuous random variable, law of large numbers, central limit theorem, and stochastic simulation, basic statistics, including point and interval estimation, hypothesis testing, and regression; examples from business applications such as inventory management, medical treatments, and finance. A specialized version of IEOR E4150 for MSE and MSBA students
Fall 2024: IEOR E4101
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4101 | 001/14588 | M W 5:40pm - 6:55pm 209 Havemeyer Hall |
Yi Zhang | 3.00 | 110/110 |
IEOR 4101 | 002/14592 | M W 7:10pm - 8:25pm 209 Havemeyer Hall |
Yi Zhang | 3.00 | 79/110 |
IEOR 4101 | 003/14594 | M W 2:40pm - 3:55pm 451 Computer Science Bldg |
Yi Zhang | 3.00 | 96/100 |
IEOR E4102 STOCHASTIC MODELING FOR MSE. 3.00 points.
Prerequisites: IEOR E4101
Introduction to stochastic processes and models, with emphasis on applications to engineering and management; random walks, gambler’s ruin problem, Markov chains in both discrete and continuous time, Poisson processes, renewal processes, stopping times, Wald’s equation, binomial lattice model for pricing risky assets, simple option pricing; simulation of simple stochastic processes, Brownian motion, and geometric Brownian motion. A specialized version of IEOR E4106 for MSE students
Spring 2024: IEOR E4102
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4102 | 001/11697 | T Th 10:10am - 11:25am 209 Havemeyer Hall |
Antonius Dieker | 3.00 | 93/110 |
IEOR S4105E Probability. 3 points.
Fundaments, random variables and distribution functions in one or more dimensions; moments, conditional probabilities, and densities; Laplace transforms and characteristic functions. Infinite sequences of random variables; weak and strong laws of large numbers; central limit theorem. \n
IEOR E4106 STOCHASTIC MODELS. 3.00 points.
Lect: 3.
Prerequisites: (STAT GU4001)
Some of the main stochastic models used in engineering and operations research applications: discrete-time Markov chains, Poisson processes, birth and death processes and other continuous Markov chains, renewal reward processes. Applications: queueing, reliability, inventory, and finance
Spring 2024: IEOR E4106
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4106 | 001/11703 | T Th 10:10am - 11:25am 501 Northwest Corner |
Kaizheng Wang | 3.00 | 158/150 |
Fall 2024: IEOR E4106
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4106 | 001/14560 | M W 1:10pm - 2:25pm 833 Seeley W. Mudd Building |
Karl Sigman | 3.00 | 96/120 |
IEOR E4108 SUPPLY CHAIN ANALYTICS. 3.00 points.
Prerequisites: IEOR E3402, IEOR E4000 or instructor’s permission.
Prerequisites: see notes re: points IEOR 3402, IEOR 4000 or permission of instructor
Supply chain management, model design of a supply chain network, inventories, stock systems, commonly used inventory models, supply contracts, value of information and information sharing, risk pooling, design for postponement, managing product variety, information technology and supply chain management; international and environmental issues. Note: replaced IEOR E4000 beginning in fall 2018
Spring 2024: IEOR E4108
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4108 | 001/11704 | T Th 2:20pm - 3:50pm 620 Kravis Hall |
Awi Federgruen | 3.00 | 15/25 |
IEOR E4111 OPERATIONS CONSULTING. 3.00 points.
Prerequisites: (IEOR E3658) and (IEOR E4307) or (STAT GU4001) and Deterministic Models at the level of IEOR E3608 or IEOR E4004, or instructor permission.
Aims to develop and harness the modeling, analytical, and managerial skills of engineering students and apply them to improve the operations of both service and manufacturing firms. Structured as a hands-on laboratory in which students "learn by doing" on real-world consulting projects (October to May). The student teams focus on identifying, modeling, and testing (and sometimes implementing) operational improvements and innovations with high potential to enhance the profitability and/or achieve sustainable competitive advantage for their sponsor companies. The course is targeted toward students planning careers in technical consulting (including operations consulting) and management consulting, or pursuing positions as business analysts in operations, logistics, supply chain and revenue management functions, positions in general management, and future entrepreneurs
Spring 2024: IEOR E4111
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4111 | 001/11705 | Th 7:10pm - 9:40pm 501 Northwest Corner |
Soulaymane Kachani | 3.00 | 0/0 |
Fall 2024: IEOR E4111
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4111 | 001/14565 | Th 7:10pm - 9:40pm 501 Northwest Corner |
Soulaymane Kachani | 3.00 | 93/110 |
IEOR E4150 INTRO-PROBABILITY & STATISTICS. 3.00 points.
Lect: 3.
Prerequisites: Calculus, including multiple integration.
Covers the following topics: fundamentals of probability theory and statistical inference used in engineering and applied science; Probabilistic models, random variables, useful distributions, expectations, law of large numbers, central limit theorem; Statistical inference: pint and confidence interval estimation, hypothesis tests, linear regression. For IEOR graduate students
Fall 2024: IEOR E4150
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4150 | 001/14559 | T Th 2:40pm - 3:55pm 501 Northwest Corner |
Yaren Kaya | 3.00 | 154/164 |
IEOR 4150 | V01/17633 | |
Yaren Kaya | 3.00 | 9/99 |
IEOR E4177 Think Bigger. 3.00 points.
Innovative solutions to complex problems that are both novel and useful. Focuses on The Think Bigger Innovation Method, uses decision-making theory, cognitive science, and industry practice to facilitate creativity and innovation. Designed to foster new ideas during the beginning of the semester that will then function as the seeds for entrepreneurially minded. Culminates in a final project with presentation of formal and polished pitch of an innovative idea in front of a distinguished panel of successful minds from across the city
IEOR E4199 MSIEOR Quantitative Bootcamp. 0.00 points.
Zero-credit course. Primer on quantitative and mathematical concepts. Required for all incoming MSOR and MSIE students
Fall 2024: IEOR E4199
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4199 | 001/15458 | |
Michael Miller | 0.00 | 189/250 |
IEOR E4201 The Engineering of Management, I. 3 points.
Lect: 3.
This course is required for undergraduate students majoring in IE. Analytical models of the processes of managing and engineering. Application of recent developments in industrial engineering, operations research, and computing to management problems in establishing policies and objectives, patterns of organization, decision processes, and communication and control systems.
IEOR E4202 The Engineering of Management, II. 3 points.
Lect: 3.
Prerequisites: IEOR E4201 or the instructor's permission
This course is required for undergraduate students majoring in IE. Application of quantitative techniques to problems of organization and management. Integration of optimization, simulation, gaming, knowledge bases, expert systems, sensitivity analyses, and measurement into management information, decision support, and project management and tracking systems. Practical cases and term project.
IEOR E4205 STUDIES IN OPERATIONS RESEARCH. 3.00 points.
IEOR E4206 Intellectual Property for Engineers. 0.00 points.
Many of this century’s biggest business successes have emerged from science-based innovations: Google, next gen semiconductors, cancer therapeutics, DNA sequencing, CRISPR, advanced batteries, and more. For most of these, strong intellectual property is a critical part of the business’ success. This class will provide an overview of how intellectual property (primarily patents, but also trademarks and copyrights) is created, protected, and leveraged by successful startups and large companies alike. In addition to lectures and exercises, there will be many guest speakers from successful venture capital firms, startups, and industry. While legal principles will be addressed, the primary focus is on leveraging intellectual property to create competitive advantage
IEOR E4207 HUMAN FACTORS: PERFORMANCE. 3.00 points.
Lect: 3.
Prerequisites: Refer to course syllabus.
Required for undergraduate students majoring in IE. Sensory and cognitive (brain) processing considerations in the design, development, and operations of systems, products, and tools. User or operator limits and potential in sensing, perceiving decision making, movement coordination, memory, and motivation
Fall 2024: IEOR E4207
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4207 | 001/14563 | M 4:10pm - 6:40pm 333 Uris Hall |
Leon Gold | 3.00 | 49/52 |
IEOR E4208 SEM IN HUMAN FACTORS DESIGN. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4207) or IEOR E4207: Human Factors: Performance or the instructor's permission.
An elective for undergraduate students majoring in IE. An in-depth exploration of the application potential of human factor principles for the design of products and processes. Applications to industrial products, tools, layouts, workplaces, and computer displays. Consideration to environmental factors, training and documentation. Term project
Spring 2024: IEOR E4208
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4208 | 001/11613 | M 4:10pm - 6:40pm 627 Seeley W. Mudd Building |
Leon Gold | 3.00 | 19/50 |
IEOR E4210 Supply Chain Management. 3 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: IEOR 3402, IEOR 4000 or permission of instructor.
This is a IE elective for undergraduate students majoring in IE. Major issues in supply chain management, including, definition of a supply chain; role of inventory; supply contracts; bullwhip effect and information sharing; vendor-managed inventories and other distribution strategies; third-party logistics providers; managing product variety; information technology and supply chain management; international issues. Emphasis on quantitative models and analysis.
IEOR E4211 APPLIED CONSULTING. 3.00 points.
Prerequisites: (IEOR E3658) and (IEOR E4307) or (IEOR E4150) or (STAT GU4001) and familiarity with R or SAS.
Basic and advanced techniques in commercial and government consulting. Case studies supported by lectures focused on collecting and analyzing skills, client/market data, client interview techniques, and application of quantitative and qualitative methodologies. Exposure to critical skills on workplan development, interview techniques, presentation deck preparation, costing, and application of analytic techniques to solve complex problems.
IEOR E4212 Data Analytics & Machine Learning for OR. 3.00 points.
Surveys tools available in Python for getting (web scraping and APIs) and visualizing data (charts and maps). Introduction to analytics through machine learning (ML algorithms, model evaluation, text analytics, network algorithms, deep learning)
Fall 2024: IEOR E4212
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4212 | 001/14566 | M W 2:40pm - 3:55pm 331 Uris Hall |
Hardeep Johar | 3.00 | 43/45 |
IEOR E4220 Demand And Supply Analytics. 3 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: IEOR E4004 (or IEOR E3608), IEOR E4106 (or IEOR E3608).
Tools to efficiently manage supply and demand networks. Topics include service and inventory trade offs, stock allocation, pricing, markdown management and contracts, timely product distribution to market while avoiding excess inventory, allocating adequate resources to the most profitable products and selling the right product to the right customer at the right price and at the right time.
IEOR E4307 STATISTICS AND DATA ANALYSIS. 3.00 points.
Lect: 3.
Prerequisites: Probability, linear algebra.
Descriptive statistics, central limit theorem, parameter estimation, sufficient statistics, hypothesis testing, regression, logistic regression, goodness-of-fit tests, applications to operations research models
Fall 2024: IEOR E4307
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4307 | 001/14569 | T Th 8:40am - 9:55am 310 Fayerweather |
Fabrizio Lecci | 3.00 | 64/90 |
IEOR E4308 Industrial Budgeting and Financial Control. 3 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: ENGI W2261 or accounting and finance.
Management control via the budgeting and financial processes. Topics include the preparation, evaluation, and implementation of operating and capital budgets and review of their performance. Examples from contemporary practice.
IEOR E4311 Derivatives Marketing & Structuring. 1.50 point.
Points: 1.5 Prerequisites: IEOR E3402, IEOR E4000 or permission of instructor.
Prerequisites: see notes re: points
Covers topics in Accounting, relationships among different elements of financial statements, short- term and long-term financing alternatives, using swaps, cap, and floors to manage interest rate risk, hedging interest risk of corporate finance, using options as cheapeners, structured swaps, accounting treatment of derivatives, cash flow hedging, accrual accounting, hedging issuance of a bond using treasuries, hedging employee stock options, preferred shares and their use in corporate treasury, FX risk and FX translation, commodities hedging, operating lease vs capital lease, credit risk, and cred spread and funding. Note: restricted to IEOR MS students
IEOR E4312 Application of OR & AI Techniques in Marketing. 1.50 point.
1.5 Points Prerequisites: Working knowledge EXCEL and a high-level language such as Python, R, MATLAB, or VBA and an introductory courses in Probability and Statistics.
Prerequisites: see notes re: points
Covers working knowledge of quantitative methods and data mining techniques applied to marketing and customer relationship management. Topics include clustering methods, conjoint analysis and customer preferences, forecasting, market share, product life cycle, new product, nearest neighbor, discriminant analysis, decision tree, revenue management, price and advertising elasticity, resource allocation and return on investment (ROI), economic analysis of a network and its formation, and networked markets. Note: restricted to IEOR MS students
IEOR E4399 MSE Quantitative Bootcamp. 0.00 points.
Zero-credit course. Primer on quantitative and mathematical concepts. Required for all incoming MSOR and MSIE students
Fall 2024: IEOR E4399
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4399 | 001/15459 | |
Michael Miller | 0.00 | 97/200 |
IEOR E4402 Corporate Finance, Accounting & Investment Banking. 3.00 points.
Interpret financial statements, build cash flow models, value projects, value companies, and make Corporate Finance decisions. Additional topics include: cost of capital, dividend policy, debt policy, impact of taxes, Shareholder/Debtholder agency costs, dual-class shares, using option pricing theory to analyze management behavior, investment banking activities, including equity underwriting, syndicated lending, venture capital, private equity investing and private equity secondaries. Application of theory in real-world situations: analyzing financial activities of companies such as General Electric, Google, Snapchat, Spotify, and Tesla
Spring 2024: IEOR E4402
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4402 | 001/11717 | Th 4:10pm - 6:40pm 329 Pupin Laboratories |
Rodney Sunada-Wong | 3.00 | 43/100 |
Fall 2024: IEOR E4402
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4402 | 001/14571 | T 7:10pm - 9:40pm 833 Seeley W. Mudd Building |
Rodney Sunada-Wong | 3.00 | 103/110 |
IEOR E4403 QUANTITATIVE CORPORATE FINANCE. 3.00 points.
Lect: 3.
Prerequisites: Probability theory and linear programming.
Required for students in the Undergraduate Advanced Track. Key measures and analytical tools to assess the financial performance of a firm and perform the economic evaluation of industrial projects. Deterministic mathematical programming models for capital budgeting. Concepts in utility theory, game theory and real options analysis
Fall 2024: IEOR E4403
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4403 | 001/14577 | F 10:10am - 12:40pm 602 Hamilton Hall |
David DeRosa | 3.00 | 14/75 |
IEOR 4403 | V01/17554 | |
David DeRosa | 3.00 | 6/99 |
IEOR E4404 SIMULATION. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E3658) and (IEOR E4307) or (STAT GU4001) and computer programming.
Corequisites: IEOR E3106,IEOR E4106
Generation of random numbers from given distributions; variance reduction; statistical output analysis; introduction to simulation languages; application to financial, telecommunications, computer, and production systems. Graduate students must register for 3 points. Undergraduate students must register for 4 points. Note: Students who have taken IEOR E4703 Monte Carlo simulation may not register for this course for credit. Recitation section required
Spring 2024: IEOR E4404
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4404 | 001/11720 | T Th 4:10pm - 5:25pm 501 Schermerhorn Hall |
Christopher Dolan | 3.00 | 110/150 |
Fall 2024: IEOR E4404
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4404 | 001/14579 | T Th 8:40am - 9:55am 833 Seeley W. Mudd Building |
Henry Lam | 3.00 | 103/110 |
IEOR 4404 | V01/17634 | |
Henry Lam | 3.00 | 3/99 |
IEOR E4405 PRODUCTION SCHEDULING. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E3608) and (IEOR E3658) and computer programming.
Required for undergraduate students majoring in IE and OR. Job shop scheduling: parallel machines, machines in series; arbitrary job shops. Algorithms, complexity, and worst-case analysis. Effects of randomness: machine breakdowns, random processing time. Term project
Spring 2024: IEOR E4405
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4405 | 001/11606 | M W 11:40am - 12:55pm 517 Hamilton Hall |
Yuri Faenza | 3.00 | 19/80 |
IEOR E4406 Facilities Location, Routing and Network Design. 3 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: IEOR E3608 or IEOR E4004
Facility location problems in application areas such as telecommunications networks, product distribution systems and emergency services. Emphasis on applications, algorithmic approaches, routing and network design problems.
IEOR E4407 GAME THEOR MODELS OF OPERATION. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4004) or (IEOR E3608) and (IEOR E4106) or (IEOR E3106) and familiarity with differential equations and computer programming; or instructor's permission.
Required for undergraduate students majoring in OR:FE and OR. A mathematically rigorous study of game theory and auctions, and their application to operations management. Topics include introductory game theory, private value auction, revenue equivalence, mechanism design, optimal auction, multiple-unit auctions, combinatorial auctions, incentives, and supply chain coordination with contracts. No previous knowledge of game theory is required
Fall 2024: IEOR E4407
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4407 | 001/14532 | M W 4:10pm - 5:25pm 303 Seeley W. Mudd Building |
Jay Sethuraman | 3.00 | 50/75 |
IEOR 4407 | V01/19422 | |
Jay Sethuraman | 3.00 | 2/99 |
IEOR E4408 RESOURCE ALLOCATION. 3.00 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: (IEOR E3608) or (IEOR E4004) and basic knowledge of nonlinear and integer programming.
Overview of resource allocation models. Single resource allocation with concave returns; equitable resource allocation; lexicographic minmax/maxmin optimization; extensions to substitutable resources; multiperiod resource allocation; equitable allocation in multi-commodity network flow models; equitable content distribution in networks; equitable resource allocation with discrete decision variables
IEOR E4412 QUALITY CONTROL AND MANAGEMENT. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E3658) and (STAT GU4001) Additional pre-requisite: working knowledge of statistics
Required for undergraduate students majoring in IE. Statistical methods for quality control and improvement: graphical methods, introduction to experimental design and reliability engineering and the relationships between quality and productivity. Contemporary methods used by manufacturing and service organizations in product and process design, production and delivery of products and services
IEOR E4416 Capacity Planning: Models, Algorithms and Applications. 3 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: IEOR 3608 or IEOR 4004.
Capacity planning problems are of significant importance in capital-intensive service and manufacturing industries, including telecommunications networks, power generation and transport, transportation networks, and heavy process industries. We will explore a large variety of capacity planning models with emphasis on timing, sizing, location, and capacity type decisions. The course will emphasize modeling approaches, key issues, and algorithms.
IEOR E4418 TRANSPORTATION ANALYTICS & LOGISTICS. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E3608 or IEOR E4404 or IEOR E4007 or CSOR W4231 or CSOR W4246) and (IEOR E3106 or IEOR E4307 or SIEO W3600 or IEOR E4100 or IEOR E4101 or IEOR E4150 or STAT GR5701 or STAT GR5703) or permission of instructor.
Transportation, primarily focused on the movement of people, and logistics, primarily focused on the movement of goods, are two of the most fundamental challenges to modern society. To address many problems in these areas, a wide array of mathematical models and analytics tools have been developed. This class will introduce many of the foundational tools used in transportation and logistics problems, relying on ideas from linear optimization, integer optimization, stochastic processes, statistics, and simulation. We will address problems such as optimizing the routes of cars and delivery trucks, positioning emergency vehicles, and controlling traffic behavior. Moreover, we will discuss modern issues such as bicycle sharing, on-demand car and delivery services, humanitarian logistics, and autonomous vehicles. Concepts will be reinforced with technical content as well as real-world data and examples
IEOR E4500 APPLICATIONS PROGRAMMNG FOR FE. 3.00 points.
Lect: 3.
Prerequisites: Computer programming or instructor's approval.
We will take a hands-on approach to developing computer applications for Financial Engineering. Special focus will be placed on high-performance numerical applications that interact with a graphical interface. In the course of developing such applications we will learn how to create DLLs, how to integrate VBA with C/C programs, and how to write multithreaded programs. Examples of problems settings that we consider include simulation of stock price evolution, tracking, evaluation and optimization of a stock portfolio; optimal trade execution. In the course of developing these applications, we review topics of interest to OR:FE in a holistic fashion
Fall 2024: IEOR E4500
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4500 | 001/14580 | T Th 8:40am - 9:55am 142 Uris Hall |
Anran Hu | 3.00 | 97/100 |
IEOR E4501 TOOLS FOR ANALYTICS. 3.00 points.
MS IEOR students only. Introduction programming in Python, tools with the programmer's ecosystem. Python, Data Analysis tools in Python (NumPy, pandas, bokeh), GIT, Bash, SQL, VIM, Linux/Debia, SSH
Spring 2024: IEOR E4501
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4501 | 001/11722 | M 7:10pm - 9:40pm 313 Fayerweather |
Lynn Root | 3.00 | 17/75 |
Fall 2024: IEOR E4501
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4501 | 001/14582 | M 7:10pm - 9:40pm 614 Schermerhorn Hall |
Lynn Root | 3.00 | 50/100 |
IEOR E4502 Python for Analytics. 0.00 points.
Zero-credit course. Primer on Python for analytics concepts. Required for MSBA students
Fall 2024: IEOR E4502
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4502 | 001/15462 | |
Paul Bulkley-Logston | 0.00 | 196/250 |
IEOR E4505 OPERATION RES IN PUBLIC POLICY. 3.00 points.
Prerequisites: (IEOR E3608) or (IEOR E4004) and (IEOR E3106) or (IEOR E4106)
Aims to give the student a broad overview of the role of Operations Research in public policy. The specific areas covered include voting theory, apportionment, deployment of emergency units, location of hazardous facilities, health care, organ allocation, management of natural resources, energy policy, and aviation security. Draws on a variety techniques such as linear and integer programming, statistical and probabilistic methods, decision analysis, risk analysis, and analysis and control of dynamic systems
Spring 2024: IEOR E4505
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4505 | 001/15102 | M W 1:10pm - 2:25pm 501 Northwest Corner |
Yaren Kaya | 3.00 | 51/80 |
IEOR E4506 DESIGN DIGITAL OPERATING MODELS. 3.00 points.
IEOR students only. Understand digital businesses, apply scientific, engineering thinking to digital economy. Data-driven digital strategies and operating models. Sectors: ecommerce, advertising technology, and marketing technology. Automation of the marketing, sales, and advertising functions. Algorithms, patents, and business models. Business side of the digital ecosytem and the digital economy
Fall 2024: IEOR E4506
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4506 | 001/14586 | M 7:10pm - 9:40pm 303 Seeley W. Mudd Building |
Anthony Effik | 3.00 | 34/70 |
IEOR E4507 HEALTHCARE OPERATIONS MGT. 3.00 points.
Not offered during 2023-2024 academic year.
Prerequisites: (IEOR E3608) and (IEOR E3658) and (IEOR E4307)
Prerequisite(s): for senior undergraduate Engineering students: IEOR E3608, E3658, and E4307; for Engineering graduate students (M.S. or Ph.D.): Probability and statistics at the level of IEOR E4150, and deterministic models at the level of IEOR E4004; for healthcare management students: P8529 Analytical methods for health services management. Develops modeling, analytical, and managerial skills of engineering and health care management students. Enables students to master an array of fundamental operations management tools adapted to the management of health care systems. Through real-world business cases, students learn to identify, model, and analyze operational improvements and innovations in a range of health care contexts
Spring 2024: IEOR E4507
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4507 | 001/11612 | M 7:10pm - 9:40pm 501 Northwest Corner |
Amit Arora | 3.00 | 37/100 |
IEOR E4510 PROJECT MANAGEMENT. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4004) or (IEOR E3608)
Management of complex projects and the tools that are available to assist managers with such projects. Topics include project selection, project teams and organizational issues, project monitoring and control, project risk management, project resource management, and managing multiple projects
Spring 2024: IEOR E4510
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4510 | 001/11607 | W 7:10pm - 9:40pm 614 Schermerhorn Hall |
Moshe Rosenwein | 3.00 | 39/120 |
IEOR E4511 Industry Projects in Analytics & Operations Research. 3.00 points.
Teams of students work on real-world projects in analytics. Focus on three aspects of analytics: identifying client analytical requirements; assembling, cleaning and organizing data; identifying and implementing analytical techniques (e.g., statistics and/or machine learning); and delivering results in a client-friendly format. Each project has a defined goal and pre-identified data to analyze in one semester. Client facing class. Class requires 10 hours of time per week and possible client visits on Fridays
Spring 2024: IEOR E4511
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4511 | 001/11608 | M 9:00am - 11:30am 633 Seeley W. Mudd Building |
Michael Robbins | 3.00 | 50/150 |
Fall 2024: IEOR E4511
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4511 | 001/14587 | M 9:00am - 11:30am 750 Schapiro Cepser |
Michael Robbins | 3.00 | 71/150 |
IEOR 4511 | V01/21001 | |
Michael Robbins | 3.00 | 0/99 |
IEOR E4520 APPLIED SYSTEMS ENGINEERING. 3.00 points.
Lect: 3.
Prerequisites: B.S. in Engineering or Applied Sciences; Professional experience recommended; Calculus, Probability and Statistics, Linear Algebra.
Introduction to fundamental methods used in systems engineering. Rigorous process that translates customer needs into a structured set of specific requirements; synthesizes a system architecture that satisfies those requirements and allocates them in a physical system, meeting cost, schedule, and performance objectives throughout the product life-cycle. Sophisticated modeling of requirements optimization and dependencies, risk management, probabilistic scenario scheduling, verification matrices, and systems-of-systems constructs are synthesized to define the meta-workflow at the top of every major engineering project
IEOR E4521 SYSTEM ENGI TOOLS/METHODS. 3.00 points.
Applications of SE tools and methods in various settings. Encompasses modern complex system development environments, including aerospace and defense, transportation, energy, communications, and modern software-intensive systems
IEOR E4522 PYTHON FOR OPERATIONS RESEARCH. 1.50 point.
Lect: 1.5.Not offered during 2023-2024 academic year.
IEOR Students Only; Priority to MSOR Students. Introduction to programming in Python, providing a working knowledge of how to use Python to extract knowledge and information from data. Overview of Python libraries for data analysis. Fundamental course for MSOR students in order to engage in higher level analytics courses.
IEOR E4523 DATA ANALYTICS. 3.00 points.
Lect: 3.
Corequisites: IEOR E4501
IEOR students only; priority to MSBA students. Survey tools available in Python for getting, cleaning, and analyzing data. Obtain data from files (csv, html, json, xml) and databases (Mysql, PostgreSQL, NoSQL), cover the rudiments of data cleaning, and examine data analysis, machine learning, and data visualization packages (NumPy, pandas, Scikit-lern, bokeh) available in Python. Brief overview of natural language processing, network analysis, and big data tools available in Python. Contains a group project component that will require students to gather, store, and analyze a data set of their choosing
Spring 2024: IEOR E4523
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4523 | 001/11771 | T Th 5:40pm - 6:55pm 833 Seeley W. Mudd Building |
Uday Menon | 3.00 | 24/80 |
Fall 2024: IEOR E4523
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4523 | 001/14590 | T Th 11:40am - 12:55pm 702 Hamilton Hall |
Uday Menon | 3.00 | 82/85 |
IEOR 4523 | 002/14575 | T Th 1:10pm - 2:25pm 602 Hamilton Hall |
Uday Menon | 3.00 | 85/85 |
IEOR 4523 | 003/17468 | T Th 4:10pm - 5:25pm 602 Hamilton Hall |
Uday Menon | 3.00 | 78/85 |
IEOR 4523 | V01/17556 | |
Uday Menon | 3.00 | 1/99 |
IEOR E4524 ANALYTICS IN PRACTICE. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4523) and IEOR E4501
MSBA students only. Groups of students will work on real world projects in analytics, focusing on three aspects: identifying client analytical requirements; assembling, cleaning, and organizing data; identifying and implementing analytical techniques (statistics, OR, machine learning); and delivering results in a client-friendly format. Each project has a well-defined goal, comes with sources of data preidentified, and has been structured so that it can be completed in one semester. Client-facing class with numerous on-site client visits; students should keep Fridays clear for this purpose
Spring 2024: IEOR E4524
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4524 | 001/11824 | Th 7:10pm - 9:40pm 301 Pupin Laboratories |
Uday Menon, Yaren Kaya | 3.00 | 187/200 |
IEOR E4525 MACHINE LEARNING FE & OPR. 3.00 points.
Prerequisites: optimization, applied probability, statistics or simulation.
MS IEOR students only. Introduction to machine learning, practical use of ML algorithms and applications to financial engineering and operations. Supervised learning: regression, classification, resampling methods, regularization, support vector machines (SVMs), and deep learning. Unsupervised learning: dimensionality reduction, matrix decomposition, and clustering algorithms
Spring 2024: IEOR E4525
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4525 | 001/11774 | F 10:10am - 12:40pm 833 Seeley W. Mudd Building |
Christian Kroer | 3.00 | 38/120 |
Fall 2024: IEOR E4525
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4525 | 001/14593 | F 10:10am - 12:40pm 614 Schermerhorn Hall |
Anish Agarwal | 3.00 | 93/120 |
IEOR E4526 ANALYTICS ON THE CLOUD. 3.00 points.
Prerequisites: IEOR E4501 and IEOR E4523
To introduce students to programming issues around working with clouds for data analytics. Class will learn how to work with infrastructure of cloud platforms, and discussion about distributed computing, focus of course is on programming. Topics covered include MapReduce, parallelism, rewriting of algorithms (statistical, OR, and machine learning) for the cloud, and basics of porting applications so that they run on the cloud
Fall 2024: IEOR E4526
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4526 | 001/14597 | M 8:40am - 11:10am 303 Seeley W. Mudd Building |
Hardeep Johar | 3.00 | 30/60 |
IEOR 4526 | V01/17534 | |
Hardeep Johar | 3.00 | 0/99 |
IEOR E4530 TOPICS IN OPERATIONS RESEARCH. 3.00 points.
This course will cover the basics of game theory and market design, with a focus on how AI and optimization enables large-scale game solving and markets. We will cover the core ideas behind recent superhuman AIs for games such as Poker. Then, we will discuss how AI and game theory ideas are used in marketplaces such as internet advertising, fair course seat allocation, and spectrum reallocation. This is intended to be an advanced MS level and senior undergraduate course for students in Operations Research and Financial Engineering
Fall 2024: IEOR E4530
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4530 | 001/14600 | M W 10:10am - 11:25am 313 Fayerweather |
Christian Kroer | 3.00 | 28/75 |
IEOR E4532 Visualization and Storytelling with Data. 1.50 point.
Data visualization and how to build a story with data. Using complex data or statistics to communicate results effectively. Learn to present analysis and results conscisely and effectively
Fall 2024: IEOR E4532
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4532 | 001/15887 | F 9:00am - 5:00pm 633 Seeley W. Mudd Building |
1.50 | 67/70 |
IEOR E4533 Performance, Objectives, & Results Using Data Analytics. 1.50 point.
OKR framework and different variations. Measurement techniques (A/B testing, validation, correlation, etc.) Identifying what to measure in product experience and business initiatives. Data-driven decision making
Spring 2024: IEOR E4533
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4533 | 001/11827 | F Sa S 9:00am - 5:00pm 633 Seeley W. Mudd Building |
Nicolas Chikhani | 1.50 | 38/60 |
Fall 2024: IEOR E4533
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4533 | 001/14536 | F Sa S 9:00am - 5:00pm 633 Seeley W. Mudd Building |
Nicolas Chikhani | 1.50 | 56/60 |
IEOR E4534 Applied Analytics: from Data to Decisions. 3.00 points.
Applied Analytics focus querying and transforming data with SQL, defining and visualizing metrics, measuring impact of products / processes. Tools and techniques to convert raw data to business decisions, statistical analysis. Be able to apply these techniques to real-world datasets
Fall 2024: IEOR E4534
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4534 | 001/14585 | T Th 11:40am - 12:55pm 413 Kent Hall |
Fabrizio Lecci | 3.00 | 71/71 |
IEOR E4540 DATA MINING. 3.00 points.
Course covers major statistical learning methods for data mining under both supervised and unsupervised settings. Topics covered include linear regression and classification, model selection and regularization, tree-based methods, support vector machines, and unsupervised learning. Students learn about principles underlying each method, how to determine which methods are most suited to applied settings, concepts behind model fitting and parameter tuning, and how to apply methods in practice and assess their performance. Emphasizes roles of statistical modeling and optimization in data mining
Spring 2024: IEOR E4540
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4540 | 001/11777 | W 7:10pm - 9:40pm 633 Seeley W. Mudd Building |
Krzysztof Choromanski | 3.00 | 31/60 |
Fall 2024: IEOR E4540
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4540 | 001/14595 | W 7:10pm - 9:40pm 303 Seeley W. Mudd Building |
Krzysztof Choromanski | 3.00 | 78/73 |
IEOR 4540 | V01/17557 | |
Krzysztof Choromanski | 3.00 | 3/99 |
IEOR E4544 Statistical Methods for Analytics. 3.00 points.
Focus on advanced statistical techniques for a career in data science or business analytics. Covers the use of writing probabilistic models for data-generating processes, using Bayesian Methods/MCMC to solve such problems. Emphasizes problem identification and general problem-solving tools. Special Topics: Survival Analysis, Missing Data, Robust Statistics, Sequential Analysis, Multiple Testing. Assignments are case-based
Spring 2024: IEOR E4544
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4544 | 001/11773 | T Th 1:10pm - 2:25pm 627 Seeley W. Mudd Building |
Christopher Dolan | 3.00 | 13/50 |
IEOR E4545 Causal Analysis for Data Analytics and OR. 3.00 points.
Survey of different approaches to causal inference with an emphasis on applications. Counterfactuals, Causal Structural Models and Graphical Models. G-formula, IP weighting, and g-estimation. Backdoor and Frontdoor adjustment, introduction to the do-calculus. Regression discontinuity, Instrumental Variables, Difference-in-Difference, Synthetic Control. Advanced Topics: Causal Survival Analysis, Time-Varying Treatments, Competing Events. Emphasis on problem-solving and working with data
IEOR E4550 ENTREPRENEURIAL BUS CREA-ENGIN. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E2261)
Required for undergraduate students majoring in OR:EMS. Introduces the basic concepts and methodologies that are used by the nonengineering part of the world in creating, funding, investing in, relating to, and operating entrepreneurial ventures. The first half of the course focuses on the underpinning principles and skills required in recognizing, analyzing, evaluating, and nurturing a business idea. The second half focuses on basic legal knowledge necessary in creating a business entity, defending your business assets, and in promoting effective interaction with other individuals and organizations
IEOR E4555 DESIGN/AGILE PROJ MGMT ENG LAB. 3.00 points.
Lect: 3.Not offered during 2023-2024 academic year.
Intensive, team-, and project-based seminar covering multidisciplinary approach to evidence-based product design; agile project planning and execution; rapid MVP prototyping; and launch strategy formulation and implementation. Focuses on practical use of design thinking, design studio, and iterative design sprint methodologies. Systematic approaches to Lean User Research, User Experience (UX), and User Interface (UI) design and deployment are integral components of course curriculum. Mix of startup and enterprise projects, including application drive, data-driven, or combination of both. Teams are fully supported in devising prototypes and actualizing proposed solutions
IEOR E4560 THE LEAN LAUNCH PAD. 3.00 points.
IEOR E4561 LAUNCH YOUR STARTUP: TECH. 3.00 points.
Tools and knowledge to develop a comprehensive new venture that is scalable, repeatable, and capital efficient. Covers customer discovery, market sizing, pricing, competition, distribution, funding, developing a minimal viable product, and other facets of creating new ventures. A company blueprint and final investor pitch are deliverables
IEOR E4562 Innovate Using Design Thinking. 3.00 points.
How Design Thinking can enhance innovation activities, market impact, value creation, and speed. Topics include: conceptual and practical understanding of design thinking, creative solutions, develop robust practices to lead interdisciplinary teams. Course aims to strengthen individuals and collaborative capabilities to identify customer needs, indirect and qualitative research, create concept hypotheses, develop prototype, defined opportunities into actionable innovation possibilities, and recommendations for client organizations
IEOR E4563 Technology Breakthroughs. 1.50 point.
Technological breakthroughs driven change, disruption, and transformation of the business landscape/society. Course covers overview of deep learning and neural networks; AI and robotics; imaging and vision; photonics; blockchain; smart/digital cities; and the application of these technologies for creating new products and services
IEOR E4570 TOPICS IN OPERATIONS RESEARCH. 1.50 point.
1.5 points
This course is designed as an introductory exposure to entrepreneurial concepts and practical skills for engineering students (and others) who wish to explore entrepreneurship conceptually or as a future endeavor in their careers. The class will be a mix of lecture, discussion, team-building and in-the-field workshopping of concepts we cover
Fall 2024: IEOR E4570
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4570 | 001/14549 | F 9:00am - 5:00pm 227 Seeley W. Mudd Building |
David Lerner | 1.50 | 46/45 |
IEOR E4571 TOPICS IN OPERATIONS RESEARCH. 3.00 points.
The last decade of 20 th century witnessed a rapid convergence of three C’s: Communications, Computers, and Consumer Electronics. This convergence has given us the Internet, smart phones, and an abundance of data with Data Science playing a major role in analyzing these data and providing predictive analytics that lead to actionable items in many fields and businesses. Finance is a field with a large amount of information and data that can utilize the skills of Data Scientists, however, to be effective in this field a data scientist, in addition to analytic knowledge, should also be knowledgeable of the working, instruments, and conventions of financial markets that range from Foreign Exchange to Equities, Bonds, Commodities, Cryptocurrencies and host of other asset classes. The objective of this course is to provide Data Science students with a working knowledge of major areas of finance that could help them in finding a position in the Financial Industry. The wide range of topics covered in this course besides expanding the range of positions where students could be a fit, it gives them more flexibility in their job search. The course will also be of value to them in managing their own finances in the future
Fall 2024: IEOR E4571
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4571 | 001/14558 | Th 1:10pm - 3:40pm 627 Seeley W. Mudd Building |
Khosrow Dehnad, Robert Kramer | 3.00 | 48/55 |
IEOR E4572 TOPICS IN OPERATIONS RESEARCH. 3.00 points.
Lect: 3.,Points: 1.5
Each offering of this course is devoted to a particular sector of Operations Research and its contemporary research, practice, and approaches. If topics are different, then course can be taken more than once for credit
Spring 2024: IEOR E4572
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4572 | 001/11772 | T Th 2:40pm - 3:55pm 633 Seeley W. Mudd Building |
Uday Menon | 3.00 | 12/70 |
Fall 2024: IEOR E4572
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4572 | 001/21201 | F 2:10pm - 4:00pm 301 Pupin Laboratories |
Uday Menon | 3.00 | 0/200 |
IEOR E4573 TOPICS IN OR. 3.00 points.
Points: 1.5
Each offering of this course is devoted to a particular sector of Operations Research and its contemporary research, practice, and approaches. If topics are different, then course can be taken more than once for credit
IEOR E4574 TOPICS IN OR. 3.00 points.
Each offering of this course is devoted to a particular sector of Operations Research and its contemporary research, practice, and approaches. If topics are different, then course can be taken more than once for credit
Spring 2024: IEOR E4574
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4574 | 001/15103 | M W 11:40am - 12:55pm 428 Pupin Laboratories |
Fabrizio Lecci | 3.00 | 70/70 |
IEOR E4575 TOPICS IN OPERATIONS RESEARCH. 3.00 points.
Note to students: 1.5 credits Note to students re: pre-requisites: Probability and statistics, Basic optimization (e.g., familiarity with linear and convex optimization, gradient descent, basic algorithm design constructs), familiarity with Programming in python (or experience with programming in other languages like C/C++/Matlab and willingness to learn python). Knowledge of machine learning is not required, but some basic familiarity may help.
Each offering of this course is devoted to a particular sector of Operations Research and its contemporary research, practice, and approaches. If topics are different, then course can be taken more than once for credit
IEOR E4576 TOPICS IN OPERATIONS RESEARCH. 3.00 points.
1.5 pts
This Columbia University course offers a project-based learning experience focused on systematic quantitative investment. It covers the full data science workflow, from concept to performance evaluation. Students will engage in a real-time financial forecasting competition, using open-source financial and alternative data, to make and present investment decisions. Ideally, this course suits students aspiring to careers as quants or data scientists in the financial sector
Fall 2024: IEOR E4576
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4576 | 001/14591 | M 7:10pm - 9:40pm 627 Seeley W. Mudd Building |
Naftali Cohen | 3.00 | 51/52 |
IEOR E4577 TOPICS IN OPERATIONS RESEARCH. 1.50 point.
Points: 1.5
The course focuses on a PRACTICAL study of how to quantify & predict RISK in organizations by using learnings from: Regression analysis; Monte Carlo simulation; Factor analysis; Cohort analysis; Cluster analysis; Time series analysis; Sentiment analysis. Expectation is that incoming students should have a basic understanding of such concepts and statistics. The course will offer meeting & listening to CXO's & top executives from companies who have implemented robust AI & Applied Risk solutions to solve real-world problems in their own industries. It will give students a great opportunity to learn practical applications of predictive analytics to solve real business problems
Fall 2024: IEOR E4577
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4577 | 001/14562 | T 5:40pm - 8:10pm 303 Seeley W. Mudd Building |
Amit Arora | 1.50 | 31/60 |
IEOR E4578 TOPICS IN OPERATION RESEARCH. 3.00 points.
Prerequisites: Must be registered in one of the MS IEOR Programs
By taking this course, students will gain the tools and knowledge to develop a comprehensive new venture that is scalable, repeatable and capital efficient. The course will help students formulate new business ideas through a process of ideation and testing. Students will test the viability of their ideas in the marketplace and will think through the key areas of new venture. The first part of the course will help students brainstorm about new ideas and test the basic viability of those ideas through of process of design and real world tests. After an idea is developed students will work towards finding a scalable, repeatable business model. We will cover customer discovery, market sizing, pricing, competition, distribution, funding, developing a minimal viable product and many other facets of creating a new venture. The course will end with students having developed a company blueprint and final investor pitch. Course requirements include imagination, flexibility, courage, getting out of the building, and passion
Spring 2024: IEOR E4578
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4578 | 001/12910 | T 7:00pm - 9:30pm 633 Seeley W. Mudd Building |
Syed Haider, Robert Kramer | 3.00 | 35/70 |
Fall 2024: IEOR E4578
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4578 | 001/14533 | T 6:00pm - 8:30pm 303 Uris Hall |
Owen Davis | 3.00 | 38/60 |
IEOR E4579 TOPICS IN OR. 1.50-3.00 points.
In this course, you'll leverage student engagement data to create a photo and text recommendation app similar to Instagram/Twitter. This app will utilize AI-generated photos and text and require you to recommend a feed from over 500,000 pieces of AI generated content. We'll explore various techniques to achieve this, including, but not limited to: Candidate Generation (Collaborative filtering, Trending, Cold start, N-tower neural network models, Cross-attention teachers, Distillation, Transfer learning, Random graph walking, Reverse indexes, LLMs as embedding), Filtering (Small online models, Caching, Deduplication, Policy), Prediction/Bidding (User logged activity based prediction (time-series), Multi-gate mixture of experts (MMOE), Regularization, Offline/Online evaluation (NDCG, p@k, r@k), Boosted Trees, Value Based Bidding), Ranking (Re-ranking, Ordering, Diversity, Enrich/Metadata/Personalization, Value Functions), Misc (Data Privacy and AI Ethics, Creator Based Models, Declared, Explicit and implicit topics, Explore/Exploit, Interpret/Understand/Context/Intention). These concepts are applicable to various recommendation systems, from e-commerce to travel to social media to financial modeling. The instructor's experience at Uber Eats, Facebook, Instagram, and Google will provide valuable insights into real-world use cases
Spring 2024: IEOR E4579
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4579 | 001/11610 | T 6:00pm - 8:30pm 501 Northwest Corner |
Gary Kazantsev | 1.50-3.00 | 51/100 |
Fall 2024: IEOR E4579
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4579 | 001/14578 | M 6:00pm - 8:30pm 750 Schapiro Cepser |
Kenneth Goodman | 1.50-3.00 | 61/75 |
IEOR E4599 MSBA Quantitative Bootcamp. 0.00 points.
Primer on quantitative and mathematical concepts. Required for all incoming MSBA students
Fall 2024: IEOR E4599
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4599 | 001/15460 | |
Michael Miller | 0.00 | 196/250 |
IEOR E4600 APPLIED INTEGER PROGRAMMING. 3.00 points.
Lect: 3.
Prerequisites: Linear programming, linear algebra, and computer programming.
This course is required for undergraduate students majoring in OR. This course covers applications of mathematical programming techniques, especially integer programming, with emphasis on software implementation. This course also covers topics of modeling and solution of problems in supply chain, logistics, routing. Particular emphasis is placed on optimization modeling systems, such as AMPL and OPL and state-of-the-art solvers.
IEOR E4601 DYNAMIC PRICING/REVENUE MGMT. 3.00 points.
Lect: 3.
Prerequisites: (STAT GU4001) and (IEOR E4004)
Focus on capacity allocation, dynamic pricing and revenue management. Perishable and/or limited product and pricing implications. Applications to various industries including service, airlines, hotel, resource rentals, etc
IEOR E4602 QUANTITATIVE RISK MANAGEMENT. 3.00 points.
Lect: 3.
Prerequisites: (STAT GU4001) and (IEOR E4106)
Risk management models and tools; measure risk using statistical and stochastic methods, hedging and diversification. Examples include insurance risk, financial risk, and operational risk. Topics covered include VaR, estimating rare events, extreme value analysis, time series estimation of extremal events; axioms of risk measures, hedging using financial options, credit risk modeling, and various insurance risk models
Fall 2024: IEOR E4602
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4602 | 001/14538 | M W 11:40am - 12:55pm 750 Schapiro Cepser |
Agostino Capponi | 3.00 | 43/58 |
IEOR 4602 | V01/17636 | |
Agostino Capponi | 3.00 | 2/99 |
IEOR E4611 DECISION MODELS AND APPLIC. 3.00 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: (IEOR E3608) and (IEOR E4004) or (IEOR E3658) and (IEOR E4307) and (STAT GU4001) or the equivalent. For graduate students: instructor's permission is required.
Corequisites: IEOR E4404
Students are introduced to deterministic and stochastic decision tools used by leading corporations and applied researchers, and apply these software packages to complex, real-world problems in engineering and finance. Building on a basic theoretical understanding of optimization, simulation and game theory obtained in prerequisite classes, students master commercial decision modeling programs such as Premium Solver Professional (linear, integer and non-linear optimization), TreePlan (decision-trees), Crystal Ball (simulation), and OptQuest (optimization under uncertainty). Students are also welcome to complete most modeling assignments with Matlab. After students have mastered the course software, its limitations and the frameworks for applying it, they work in small teams to address (as a mid-term project) one large-scale deterministic project and (as an end-of-semester project) one similarly-complex stochastic problem. While addressing their first projects, students learn effective presentation and project reporting skills, suitable for communicating with CFOs and CEOs. Students present their project analyses to a small panel of industry experts and executives. Throughout the course, the importance of outside-the-model considerations, model limitations and sources of modeling error are stressed, and general frameworks for approaching particular problem types are developed.
IEOR E4615 SERVICE ENGINEERING. 3.00 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: (SIEO W3600) and (IEOR E3106) or (IEOR E4106) or equivalent.
Focus on service systems viewed as stochastic networks, exploiting the theoretical framework of queueing theory. Includes multidisciplinary perspectives involving Statistics, Psychology, and Marketing. Significant emphasis on data analysis, exploiting data from banks, hospitals, and call centers to demonstrate the use of decision support tools. Analytical models, flow models of service networks, Little’s law, measuring methods in face-to-face and computerized systems, forecasting methods, stability of service systems, operational quality of service, economies of scale, staffing, complex service networks, skill-based routing
IEOR E4620 PRICING MODELS FOR FIN ENGIN. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4700)
Required for undergraduate students majoring in OR:FE. Characteristics of commodities or credit derivatives. Case study and pricing of structures and products. Topics covered include swaps, credit derivatives, single tranche CDO, hedging, convertible arbitrage, FX, leverage leases, debt markets, and commodities
Fall 2024: IEOR E4620
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4620 | 001/14540 | T 7:10pm - 9:40pm 633 Seeley W. Mudd Building |
Michael Miller | 3.00 | 48/70 |
IEOR E4630 ASSET ALLOCATION. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4700)
Models for pricing and hedging equity, fixed-income, credit-derivative securities, standard tools for hedging and risk management, models and theoretical foundations for pricing equity options (standard European, American equity options, Asian options), standard Black-Scholes model (with multiasset extension), asset allocation, portfolio optimization, investments over longtime horizons, and pricing of fixed-income derivatives (Ho-Lee, Black-Derman-Toy, Heath-Jarrow-Morton interest rate model)
Spring 2024: IEOR E4630
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4630 | 001/11714 | T Th 4:10pm - 5:25pm 301 Pupin Laboratories |
Christopher Perez | 3.00 | 69/130 |
IEOR E4650 BUSINESS ANALYTICS. 3.00 points.
Prepares students to gather, describe, and analyze data, using advanced statistical tools to support operations, risk management, and response to disruptions. Analysis is done by targeting economic and financial decisions in complex systems that involve multiple partners. Topics include probability, statistics, hypothesis testing, experimentation, and forecasting
Spring 2024: IEOR E4650
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4650 | 001/11673 | M W 5:40pm - 6:55pm 303 Seeley W. Mudd Building |
Yi Zhang | 3.00 | 28/73 |
IEOR 4650 | 002/11611 | M W 7:10pm - 8:25pm 303 Seeley W. Mudd Building |
Yi Zhang | 3.00 | 21/73 |
Fall 2024: IEOR E4650
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4650 | 001/14552 | Th 5:40pm - 8:25pm 620 Geffen Hall |
Charles Guetta | 3.00 | 146/150 |
IEOR 4650 | 002/14568 | Th 10:10am - 12:55pm 620 Geffen Hall |
Charles Guetta | 3.00 | 144/150 |
IEOR E4651 DATA MINING. 3.00 points.
IEOR E4700 INTRO TO FINANCIAL ENGINEERING. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E3106) or (IEOR E4106)
Prerequisite(s): IEOR E4106 or E3106. Required for undergraduate students majoring in OR:FE. Introduction to investment and financial instruments via portfolio theory and derivative securities, using basic operations research/engineering methodology. Portfolio theory, arbitrage; Markowitz model, market equilibrium, and the capital asset pricing model. General models for asset price fluctuations in discrete and continuous time. Elementary introduction to Brownian motion and geometric Brownian motion. Option theory; Black-Scholes equation and call option formula. Computational methods such as Monte Carlo simulation
Spring 2024: IEOR E4700
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4700 | 001/11623 | T Th 11:40am - 12:55pm 209 Havemeyer Hall |
Xunyu Zhou | 3.00 | 97/105 |
Fall 2024: IEOR E4700
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4700 | 001/14554 | M W 11:40am - 12:55pm 428 Pupin Laboratories |
David Yao | 3.00 | 49/100 |
IEOR 4700 | V01/17609 | |
David Yao | 3.00 | 6/99 |
IEOR E4701 STOCHASTIC MODELS FOR FIN ENG. 3.00 points.
Lect: 3.
Prerequisites: (STAT GU4001)
This graduate course is only for M.S. Program in Financial Engineering students, offered during the summer session. Review of elements of probability theory, Poisson processes, exponential distribution, renewal theory, Wald’s equation. Introduction to discrete-time Markov chains and applications to queueing theory, inventory models, branching processes
Fall 2024: IEOR E4701
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4701 | 001/14557 | M W 1:10pm - 2:25pm 501 Northwest Corner |
David Yao | 3.00 | 126/140 |
IEOR 4701 | V01/17610 | |
David Yao | 3.00 | 1/99 |
IEOR E4702 Statistical Inference for Financial Engineering. 1.5 point.
Lect: 1.5.Not offered during 2023-2024 academic year.
Corequisites: IEOR E4701 and IEOR E4706.
This course is for MSFE students only, offered during the summer session. The course covers basic tools of statistical inference relevant to financial engineering. The statistical topics covered include point estimation, maximum likelihood estimators, confidence intervals, the delta method, hypothesis testing, and goodness of fit tests. The financial examples include selection bias in finance, estimation of drift and volatility in the geometric Brownian motion model, the leptokurtic feature, and difficulties in estimating the tail distributions of asset returns.
IEOR E4703 MONTE CARLO SIMULATION METHODS. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4701)
This graduate course is only for M.S. Program in Financial Engineering students. Multivariate random number generation, bootstrapping, Monte Carlo simulation, efficiency improvement techniques. Simulation output analysis, Markov-chain Monte Carlo. Applications to financial engineering. Introduction to financial engineering simulation software and exposure to modeling with real financial data. Note: Students who have taken IEOR E4404 Simulation may not register for this course for credit
Spring 2024: IEOR E4703
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4703 | 001/11632 | T Th 8:40am - 9:55am 833 Seeley W. Mudd Building |
Ali Hirsa | 3.00 | 101/120 |
IEOR E4705 STUDIES IN OPERATION RESEARCH. 3.00 points.
IEOR E4706 FOUNDATIONS FR FINANCIAL ENGIN. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4701) and (IEOR E4702) and linear algebra.
This graduate course is only for M.S. Program in Financial Engineering students, offered during the summer session. Discrete-time models of equity, bond, credit, and foreign-exchange markets. Introduction to derivative markets. Pricing and hedging of derivative securities. Complete and incomplete markets. Introduction to portfolio optimization and the capital asset pricing model
Fall 2024: IEOR E4706
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4706 | 001/14561 | T Th 11:40am - 12:55pm 428 Pupin Laboratories |
Wenpin Tang | 3.00 | 124/140 |
IEOR 4706 | V01/17637 | |
Wenpin Tang | 3.00 | 1/99 |
IEOR E4707 FE CONTINUOUS TIME MODELS. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4701)
This graduate course is only for MS program in FE students. Modeling, analysis, and computation of derivative securities. Applications of stochastic calculus and stochastic differential equations. Numerical techniques: finite-difference, binomial method, and Monte Carlo
Spring 2024: IEOR E4707
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4707 | 001/11636 | T Th 2:40pm - 3:55pm 833 Seeley W. Mudd Building |
Xunyu Zhou | 3.00 | 100/120 |
IEOR E4709 STATISTICAL ANALYSIS AND TIME SERIES. 3.00 points.
Lect: 3.
Prerequisites: Probability.
Corequisites: IEOR E4706,IEOR E4702
This graduate course is only for M.S. Program in Financial Engineering students. Empirical analysis of asset prices: heavy tails, test of the predictability of stock returns. Financial time series: ARMA, stochastic volatility, and GARCH models. Regression models: linear regression and test of CAPM, non-linear regression and fitting of term structures
Spring 2024: IEOR E4709
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4709 | 001/11648 | M W 10:10am - 11:25am 833 Seeley W. Mudd Building |
Agostino Capponi | 3.00 | 100/120 |
IEOR E4710 TERM STRUCTURE MODELING. 3.00 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: (IEOR E4706) and (IEOR E4707) and computer programming.
Interest rate models and numerical techniques for pricing and hedging interest rate contracts and fixed income securities
IEOR E4711 GLOBAL CAPITAL MARKETS. 3.00 points.
Prerequisites: Refer to course syllabus.
An introduction to capital markets and investments providing an overview of financial markets and tools for asset valuation. Topics covered include the pricing of fixed-income securities (treasury markets, interest rate swaps futures, etc.), discussions on topics in credit, foreign exchange, sovereign ad securitized markets—private equity and hedge funds, etc
Fall 2024: IEOR E4711
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4711 | 001/14564 | M 6:00pm - 8:30pm 633 Seeley W. Mudd Building |
Siddhartha Ghosh Dastidar | 3.00 | 63/70 |
IEOR E4718 INTRO-IMPLIED VOLATILITY SMILE. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4706) and knowledge of derivatives valuation models.
During the past 15 years the behavior of market options prices have shown systematic deviations from the classic Black-Scholes model. Examines the empirical behavior of implied volatilities, in particular the volatility smile that now characterizes most markets, the mathematics and intuition behind new models that can account for the smile, and their consequences for hedging and valuation
Spring 2024: IEOR E4718
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4718 | 001/11658 | T 7:10pm - 9:40pm 313 Fayerweather |
Amal Moussa | 3.00 | 36/75 |
IEOR E4720 TOPICS IN QUANT FINANCE. 3.00 points.
Prerequisites: (IEOR E4700) and additional prerequisites will be announced depending on offering.
Selected topics of interest in the area of quantitative finance. Offerings vary each year; some topics include energy derivatives, experimental finance, foreign exchange and related derivative instruments, inflation derivatives, hedge fund management, modeling equity derivatives in Java, mortgage-backed securities, numerical solutions of partial differential equations, quantitative portfolio management, risk management, trade and technology in financial markets
Spring 2024: IEOR E4720
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4720 | 001/11609 | M W 1:10pm - 2:25pm 633 Seeley W. Mudd Building |
Fabrizio Lecci | 3.00 | 69/70 |
IEOR E4721 TOPICS IN QUANT FINANCE. 3.00 points.
Prerequisites: IEOR E4700: Introduction to Financial Engineering, additional pre-requisites will be announced depending on offering.
Selected topics of interest in the area of quantitative finance. Offerings vary each year; some topics include energy derivatives, experimental finance, foreign exchange and related derivative instruments, inflation derivatives, hedge fund management, modeling equity derivatives in Java, mortgage-backed securities, numerical solutions of partial differential equations, quantitative portfolio management, risk management, trade and technology in financial markets
Spring 2024: IEOR E4721
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4721 | 001/11766 | |
Ali Hirsa | 3.00 | 74/75 |
Summer 2024: IEOR E4721
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4721 | 001/12347 | |
Ali Hirsa | 3.00 | 35/60 |
IEOR E4722 TOPICS IN QUANT FINANCE. 3.00 points.
Prerequisites: IEOR E4707 Refer to course syllabus.
Stochastic control has broad applications in almost every walk of life, including finance, revenue management, energy, health care and robotics. Classical, model-based stochastic control theory assumes that the system dynamics and reward functions are known and given, whereas modern, model-free stochastic control problems call for reinforcement learning to learn optimal policies in an unknown environment. This course covers model-based stochastic control and model-free reinforcement learning, both in continuous time with continuous state space and possibly continuous control (action) space. It includes the following topics: Shortest path problem, calculus of variations and optimal control; formulation of stochastic control; maximum principle and backward stochastic differential equations; dynamic programming and Hamilton-Jacobi-Bellman (HJB) equation; linear-quadratic control and Riccati equations; applications in high-frequency trading; exploration versus exploitation in reinforcement learning; policy evaluation and martingale characterization; policy gradient; q-learning; applications in diffusion models for generative AI
Fall 2024: IEOR E4722
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4722 | 001/15903 | T Th 2:40pm - 3:55pm 524 Seeley W. Mudd Building |
Xunyu Zhou | 3.00 | 15/51 |
IEOR E4723 TOPICS IN QUANTATIVE FINANCE. 1.50 point.
Course Points: 1.5
ESG (Environmental, Social and Corporate Governance) Finance is a rapidly growing area of Investment Management – and Finance more broadly – that has received a lot of attention in the past several years from the investor community, financial regulatory agencies, and the general public alike. This course provides an introduction to ESG Finance from a financial engineer’s perspective. This course also discusses proliferation of newly available data sources and the associated quantitative techniques necessary to process those. A major component of this course is a discussion of Climate Risk, an area of particular focus due to its increasing general importance. The course includes an overview of both recent research and the evolving regulatory landscape in the climate risk space. An in-depth discussion of financial impact assessment of various climate risk-driven scenarios (climate risk stress testing) concludes the course
Fall 2024: IEOR E4723
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4723 | 001/14573 | T 7:10pm - 9:40pm 644 Seeley W. Mudd Building |
Cyril Shmatov | 1.50 | 19/40 |
IEOR E4724 TOPICS IN QUANTATIVE FINANCE. 3.00 points.
In this course, we will cover the basics of mathematical modeling of interest rates and credit derivatives. In the first part, we will cover basic interest rate derivatives, the Heath-Jarrow-Morton (HJM) framework, classic short rate models (for both interest rates and default intensities), and the numerical techniques used in practice for their calibration. In the second part, we will cover the basics of single-name derivatives modeling, and we will discuss pricing simple credit derivatives. We will also discuss correlation products and the most common techniques used for their pricing. In the third part, we will discuss some recent research papers addressing the use of adjoint algorithmic differentiation for the calculation of risk for interest rate and credit derivatives
Fall 2024: IEOR E4724
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4724 | 001/14581 | W 6:00pm - 8:30pm 140 Uris Hall |
Luca Capriotti | 3.00 | 29/50 |
IEOR E4725 Topics in Quantitative Finance: Numerical Solutions of Partial Differential Equation. 3 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: (IEOR E4706) and (IEOR E4707) IEOR E4706 and IEOR E4707.
Networks are ubiquitous in our modern society. Economic and social networks have been used extensively to model a variety of situations, in which individual decision-makers are affected by the choices of their peers in the network. This course will introduce the main mathematical models for the study of these networks. It will discuss game theoretical and dynamic optimization techniques, which can be used to analyze a wide variety of these networks, including their resilience to shocks, the diffusion of information leading to social contagion, and how the strategic behavior of agents shapes the performance of the network
IEOR E4726 TOPICS IN QUANTATIVE FINANCE. 3.00 points.
Selected topics of interest in the area of quantitative finance. Offerings vary each year; some topics include energy derivatives, experimental finance, foreign exchange and related derivative instruments, inflation derivatives, hedge fund management, modeling equity derivatives in Java, mortgage-backed securities, numerical solutions of partial differential equations, quantitative portfolio management, risk management, trade and technology in financial markets
IEOR E4727 TOPICS IN QUANTATIVE FINANCE. 3.00 points.
Prerequisites: Refer to course syllabus.
Selected topics of interest in the area of quantitative finance. Offerings vary each year; some topics include energy derivatives, experimental finance, foreign exchange and related derivative instruments, inflation derivatives, hedge fund management, modeling equity derivatives in Java, mortgage-backed securities, numerical solutions of partial differential equations, quantitative portfolio management, risk management, trade and technology in financial markets
IEOR E4728 TOPICS IN QUANTITATIVE FINANCE. 1.50 point.
The search for better performance has led investors to explore Alternative Investments that are outside the traditional categories of exchange traded equities, Treasury Bonds, and other investment-grade fixed income products. The field of Alternative Investments covers a wide range of products such as convertible bonds, Preferred Shares, Hedge Funds, Venture Capital, and Cryptocurrencies. There is a growing need in the market for students with knowledge of these products and the practical and theoretical know how of valuing and risk managing these investments given that each product has it own nuances and anomalies. This course presents and studies some major Alternative Investment products and ways to evaluate and risk manage them
Fall 2024: IEOR E4728
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4728 | 001/14574 | Th 7:10pm - 9:40pm 627 Seeley W. Mudd Building |
Khosrow Dehnad | 1.50 | 32/50 |
IEOR E4729 TOPICS IN QUANTATIVE FINANCE. 1.50 point.
NOTE: If you have previously completed IEOR 4733 Algorithmic Trading or IEOR 4729 Model Based Trading, please note that while this version of 4729 has many new elements, it materially overlaps with these two classes and is intended to replace both.
Selected topics of interest in the area of quantitative finance. Offerings vary each year; some topics include energy derivatives, experimental finance, foreign exchange and related derivative instruments, inflation derivatives, hedge fund management, modeling equity derivatives in Java, mortgage-backed securities, numerical solutions of partial differential equations, quantitative portfolio management, risk management, trade and technology in financial markets
IEOR E4731 CREDIT RISK/CREDIT DERIVATIVES. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4701) and (IEOR E4707)
Introduction to quantitative modeling of credit risk, with a focus on the pricing of credit derivatives. Focus on the pricing of single-name credit derivatives (credit default swaps) and collateralized debt obligations (CDOs). Detail topics include default and credit risk, multiname default barrier models and multiname reduced form models
Fall 2024: IEOR E4731
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4731 | 001/14572 | M W 1:10pm - 2:25pm 524 Seeley W. Mudd Building |
Agostino Capponi | 3.00 | 4/50 |
IEOR 4731 | V01/17638 | |
Agostino Capponi | 3.00 | 2/99 |
IEOR E4732 COMPUT METHODS IN FINANCE. 3.00 points.
Prerequisites: (IEOR E4700)
MS IEOR students only. Application of various computational methods/techniques in quantitative/computational finance. Transform techniques: fast Fourier transform for data de-noising and pricing, finite difference methods for partial differential equations (PDE), partial integro-differential equations (PIDE), Monte-Carlo simulation techniques in finance, and calibration techniques, filtering and parameter estimation techniques. Computational platform will be C /Java/Python/Matlab/R
Spring 2024: IEOR E4732
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4732 | 001/11764 | Th 7:10pm - 9:40pm 415 Schapiro Cepser |
Alireza Javaheri | 3.00 | 7/40 |
IEOR E4733 ALGORITHMIC TRADING. 3.00 points.
Prerequisites: IEOR E4700
Prerequisite(s): IEOR E4700. Large and amorphous collection of subjects ranging from the study of market microstructure, to the analysis of optimal trading strategies, to the development of computerized, high-frequency trading strategies. Analysis of these subjects, the scientific and practical issues they involve, and the extensive body of academic literature they have spawned. Attempt to understand and uncover the economic and financial mechanisms that drive and ultimately relate them
Spring 2024: IEOR E4733
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4733 | 001/11765 | W 7:10pm - 9:40pm 833 Seeley W. Mudd Building |
Sebastien Donadio | 3.00 | 95/120 |
IEOR E4734 FOR EXCH/RELATD DERIVATVS INST. 1.50 point.
1.5.
Prerequisites: (IEOR E4700)
Foreign exchange market and its related derivative instruments—the latter being forward contracts, futures, options, and exotic options. What is unusual about foreign exchange is that although it can rightfully claim to be the largest of all financial markets, it remains an area where very few have any meaningful experience. Virtually everyone has traded stocks, bonds, and mutual funds. Comparatively few individuals have ever traded foreign exchange. In part that is because foreign exchange is an interbank market. Ironically the foreign exchange markets may be the best place to trade derivatives and to invent new derivatives—given the massive two-way flow of trading that goes through bank dealing rooms virtually 24 hours a day. And most of that is transacted at razor-thin margins, at least comparatively speaking, a fact that makes the foreign exchange market an ideal platform for derivatives. The emphasis is on familiarizing the student with the nature of the foreign exchange market and those factors that make it special among financial markets, enabling the student to gain a deeper understanding of the related market for derivatives on foreign exchange
Fall 2024: IEOR E4734
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4734 | 001/14583 | Th 4:10pm - 6:40pm 1127 Seeley W. Mudd Building |
David DeRosa | 1.50 | 55/60 |
IEOR 4734 | V01/17667 | |
David DeRosa | 1.50 | 1/99 |
IEOR E4735 Structured and Hybrid Products. 3 points.
Lect: 3.
Prerequisites: (IEOR E4700)
Conceptual and practical understanding of structured and hybrid products from the standpoint of relevant risk factors, design goals and characteristics, pricing, hedging and risk management. Detailed analysis of the underlying cash-flows, embedded derivative instruments and various structural features of these transactions, both from the investor and issuer perspectives, and analysis of the impact of the prevailing market conditions and parameters on their pricing and risk characteristics. Numerical methods for valuing and managing risk of structured/hybrid products and their embedded derivatives and their application to equity, interest rates, commodities and currencies, inflation and credit-related products. Conceptual and mathematical principles underlying these techniques, and practical issues that arise in their implementations in the Microsoft Excel/VBA and other programming environments. Special contractual provisions often encountered in structured and hybrid transactions, and attempt to incorporate yield curves, volatility smile, and other features of the underlying processes into pricing and implementation framework for these products.
Fall 2024: IEOR E4735
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4735 | 001/14576 | Th 7:10pm - 9:40pm 329 Pupin Laboratories |
Alireza Javaheri | 3 | 53/100 |
IEOR E4736 EVENT DRIVEN FINANCE. 3.00 points.
Lect: 3.
Prerequisites: (IEOR E4706 and IEOR E4707) equivalent.
The course takes a long deep look at the actual behavior of real stocks and options in the presence of commonplace, but singular events, such as earnings take-overs, hard-to-borrowness, expirations, etc. The course introduces concepts to propose trading schema (we organize tests via the very extensive and robust IVY options/stock database) and carry out tests efficiently and accurately. It exposes students to the striking differences between the model-based (static, thermodynamic/SDE model solutions) behavior predicted for stocks and options and their real (often quite different) behavior. They will become familiar with computational techniques for modeling and testing proposals for trading strategies.
IEOR E4737 AI Applications in Finance. 3.00 points.
Data, models, visuals; various facets of AI, applications in finance; areas: fund, manager, security selection, asset allocation, risk management within asset management; fraud detection and prevention; climate finance and risk; data-driven real estate finance; cutting-edge techniques: machine learning, deep learning in computational, quantitative finance; concepts: explainability, interpretability, adversarial machine learning, resilience of AI systems; industry utilization
IEOR E4739 PROGRAMMING FOR FE 2. 3.00 points.
Lect: 2.5.
Prerequisites: (IEOR E4738)
Developing effective software implementations in C programming language; modeling of portfolio optimization; modeling of price impact trading models; review of synchronization of programs using the file system; review of synchronization of programs using threads; review of synchronization of programs using sockets; implementation of high-performance simulations in finance
IEOR E4741 Programming for Financial Engineering. 3.00 points.
Covers C programming language, applications, and features for financial engineering, and quantitative finance applications. Note: restricted to IEOR MS FE students only
Fall 2024: IEOR E4741
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4741 | 001/14570 | W 7:10pm - 9:40pm 633 Seeley W. Mudd Building |
Sebastien Donadio | 3.00 | 23/60 |
IEOR E4742 Deep Learning for OR and FE. 3.00 points.
Selected topics of interest in area of quantitative finance. Some topics include energy derivatives, experimental finance, foreign exchange and related derivative instruments, inflation derivatives, hedge fund management, modeling equity derivatives in Java, mortgage-backed securities, numerical solutions of partial differential equations, quantitative portfolio management, risk management, trade and technology in financial markets. Note: open to IEOR students only
Fall 2024: IEOR E4742
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4742 | 001/14584 | |
Ali Hirsa | 3.00 | 83/85 |
IEOR E4743 Financial Correlations – Modeling, Trading, Risk Management & AI. 3.00 points.
Introduction to math finance, knowledge of working as a "Quant" in investment banking, hedge funds, algo shop, HFT firm, Fed, Exchange, SEC, IMF, back office, mutual fund, as a trader in risk management, product development, model validation, compliance, reporting, academia. Open only to master's students in IEOR department
IEOR E4744 Modeling & Market Making in Foreign Exchange. 1.50 point.
Introduction to topics in modeling and market making in foreign exchange, such as spots markets, forward markets, vanilla option markets, exotic derivative markets, and algorithmic index markets. Open only to master's students in IEOR department
IEOR E4745 Applied Financial Risk Management. 3.00 points.
Prerequisites: Probability and statistics, instruments of the financial markets, and asset pricing models
Prerequisites: see notes re: points
Introduces risk management principles, practical implementation and applications, standard market, liquidity, and credit risk measurement techniques, and their drawbacks and limitations. Note: restricted to IEOR students only
Fall 2024: IEOR E4745
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4745 | 001/14567 | T Th 2:40pm - 3:55pm 209 Havemeyer Hall |
Allan Malz | 3.00 | 54/110 |
IEOR 4745 | V01/17558 | |
Allan Malz | 3.00 | 0/99 |
IEOR E4798 Financial Engineering Practitioners Seminar Series. 0.00 points.
Degree requirement for all MSFE first-year students. Topics in Financial Engineering. Past seminar topics include Evolving Financial Intermediation, Measuring and Using Trading Algorithms Effectively, Path-Dependent Volatility, Artificial Intelligence and Data Science in modern financial decision making, Risk-Based Performance Attribution, and Financial Machine Learning. Meets select Monday evenings
Spring 2024: IEOR E4798
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4798 | 001/11814 | M 7:00pm - 9:00pm 301 Uris Hall |
Cindy Borgen, Winsor Yang, Ali Hirsa | 0.00 | 0/110 |
Fall 2024: IEOR E4798
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4798 | 001/17658 | M 7:00pm - 9:00pm 501 Schermerhorn Hall |
Ali Hirsa, Cindy Borgen | 0.00 | 123/140 |
IEOR E4799 MSFE Quantitative and Computational Bootcamp. 0.00 points.
Primer on quantitative and mathematical concepts. Required of all incoming MSFE students
Fall 2024: IEOR E4799
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4799 | 060/15461 | |
Sebastien Donadio, Michael Miller | 0.00 | 123/250 |
IEOR E4899 Research Training. 0.00 points.
Research training course. Recommended in preparation for laboratory related research
IEOR E4900 MASTERS RESEARCH OR PROJECT. 1.00-3.00 points.
Prerequisites: Approval by a faculty member who agrees to supervise the work.
Prerequisite(s): Approval by a faculty member who agrees to supervise the work. Independent work involving experiments, computer programming, analytical investigation, or engineering design
Spring 2024: IEOR E4900
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4900 | 001/11997 | |
Anish Agarwal | 1.00-3.00 | 0/40 |
IEOR 4900 | 002/12000 | |
Shipra Agrawal | 1.00-3.00 | 1/40 |
IEOR 4900 | 003/12001 | |
Eric Balkanski | 1.00-3.00 | 0/40 |
IEOR 4900 | 004/12003 | |
Daniel Bienstock | 1.00-3.00 | 0/40 |
IEOR 4900 | 005/12004 | |
Agostino Capponi | 1.00-3.00 | 0/40 |
IEOR 4900 | 006/12006 | |
Rachel Cummings | 1.00-3.00 | 0/40 |
IEOR 4900 | 007/12007 | |
Antonius Dieker | 1.00-3.00 | 0/40 |
IEOR 4900 | 008/12008 | |
Christopher Dolan | 1.00-3.00 | 0/40 |
IEOR 4900 | 009/12013 | |
Adam Elmachtoub | 1.00-3.00 | 0/40 |
IEOR 4900 | 010/12014 | |
Yuri Faenza | 1.00-3.00 | 0/40 |
IEOR 4900 | 011/12015 | |
Donald Goldfarb | 1.00-3.00 | 0/40 |
IEOR 4900 | 012/12016 | |
Vineet Goyal | 1.00-3.00 | 0/40 |
IEOR 4900 | 013/12017 | |
Ali Hirsa | 1.00-3.00 | 7/40 |
IEOR 4900 | 014/12020 | |
Garud Iyengar | 1.00-3.00 | 0/40 |
IEOR 4900 | 015/12023 | |
Hardeep Johar | 1.00-3.00 | 0/40 |
IEOR 4900 | 016/12028 | |
Cedric Josz | 1.00-3.00 | 0/40 |
IEOR 4900 | 017/12031 | |
Soulaymane Kachani | 1.00-3.00 | 0/40 |
IEOR 4900 | 018/12034 | |
Yaren Kaya | 1.00-3.00 | 0/40 |
IEOR 4900 | 019/12035 | |
Christian Kroer | 1.00-3.00 | 0/40 |
IEOR 4900 | 020/12037 | |
Daniel Lacker | 1.00-3.00 | 0/40 |
IEOR 4900 | 021/12038 | |
Henry Lam | 1.00-3.00 | 0/40 |
IEOR 4900 | 022/12039 | |
Fabrizio Lecci | 1.00-3.00 | 0/40 |
IEOR 4900 | 023/12041 | |
Uday Menon | 1.00-3.00 | 0/40 |
IEOR 4900 | 024/12043 | |
Jay Sethuraman | 1.00-3.00 | 0/40 |
IEOR 4900 | 025/12046 | |
Karl Sigman | 1.00-3.00 | 0/40 |
IEOR 4900 | 026/12048 | |
Clifford Stein | 1.00-3.00 | 0/40 |
IEOR 4900 | 027/12049 | |
Wenpin Tang | 1.00-3.00 | 0/40 |
IEOR 4900 | 028/12062 | |
Kaizheng Wang | 1.00-3.00 | 0/40 |
IEOR 4900 | 029/12076 | |
David Yao | 1.00-3.00 | 0/40 |
IEOR 4900 | 030/12089 | |
Yi Zhang | 1.00-3.00 | 0/40 |
IEOR 4900 | 031/12100 | |
Xunyu Zhou | 1.00-3.00 | 0/40 |
IEOR 4900 | 032/12110 | |
Chris Lee, Carmen Ng | 1.00-3.00 | 0/40 |
Summer 2024: IEOR E4900
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4900 | 001/12373 | |
Anish Agarwal | 1.00-3.00 | 0/40 |
IEOR 4900 | 002/12408 | |
Shipra Agrawal | 1.00-3.00 | 0/40 |
IEOR 4900 | 003/12411 | |
Eric Balkanski | 1.00-3.00 | 0/40 |
IEOR 4900 | 004/12414 | |
Daniel Bienstock | 1.00-3.00 | 0/40 |
IEOR 4900 | 005/12417 | |
Agostino Capponi | 1.00-3.00 | 1/40 |
IEOR 4900 | 006/12420 | |
Rachel Cummings | 1.00-3.00 | 0/40 |
IEOR 4900 | 007/12423 | |
Antonius Dieker | 1.00-3.00 | 0/40 |
IEOR 4900 | 008/12427 | |
Christopher Dolan | 1.00-3.00 | 0/40 |
IEOR 4900 | 009/12428 | |
Adam Elmachtoub | 1.00-3.00 | 0/40 |
IEOR 4900 | 010/12430 | |
Yuri Faenza | 1.00-3.00 | 0/40 |
IEOR 4900 | 011/12432 | |
Donald Goldfarb | 1.00-3.00 | 0/40 |
IEOR 4900 | 012/12436 | |
Vineet Goyal | 1.00-3.00 | 0/40 |
IEOR 4900 | 013/12435 | |
Ali Hirsa | 1.00-3.00 | 1/40 |
IEOR 4900 | 014/12434 | |
Anran Hu | 1.00-3.00 | 0/40 |
IEOR 4900 | 015/12433 | |
Garud Iyengar | 1.00-3.00 | 0/40 |
IEOR 4900 | 016/12431 | |
Hardeep Johar | 1.00-3.00 | 0/40 |
IEOR 4900 | 017/12429 | |
Cedric Josz | 1.00-3.00 | 0/40 |
IEOR 4900 | 018/12425 | |
Soulaymane Kachani | 1.00-3.00 | 0/40 |
IEOR 4900 | 019/12426 | |
Yaren Kaya | 1.00-3.00 | 0/40 |
IEOR 4900 | 020/12421 | |
Christian Kroer | 1.00-3.00 | 0/40 |
IEOR 4900 | 021/12416 | |
Daniel Lacker | 1.00-3.00 | 0/40 |
IEOR 4900 | 022/12413 | |
Henry Lam | 1.00-3.00 | 0/40 |
IEOR 4900 | 023/12403 | |
Fabrizio Lecci | 1.00-3.00 | 0/40 |
IEOR 4900 | 024/12404 | |
Tianyi Lin | 1.00-3.00 | 0/40 |
IEOR 4900 | 025/12405 | |
Jay Sethuraman | 1.00-3.00 | 0/40 |
IEOR 4900 | 026/12407 | |
Karl Sigman | 1.00-3.00 | 0/40 |
IEOR 4900 | 027/12409 | |
Clifford Stein | 1.00-3.00 | 0/40 |
IEOR 4900 | 028/12412 | |
Wenpin Tang | 1.00-3.00 | 0/40 |
IEOR 4900 | 029/12415 | |
Kaizheng Wang | 1.00-3.00 | 0/40 |
IEOR 4900 | 030/12418 | |
David Yao | 1.00-3.00 | 0/40 |
IEOR 4900 | 031/12419 | |
Yi Zhang | 1.00-3.00 | 0/40 |
IEOR 4900 | 032/12422 | |
Xunyu Zhou | 1.00-3.00 | 0/40 |
IEOR 4900 | 033/12424 | |
Chris Lee, Jiaqi Li | 1.00-3.00 | 0/40 |
Fall 2024: IEOR E4900
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4900 | 001/13958 | |
Anish Agarwal | 1.00-3.00 | 0/40 |
IEOR 4900 | 002/13960 | |
Shipra Agrawal | 1.00-3.00 | 0/40 |
IEOR 4900 | 003/13961 | |
Eric Balkanski | 1.00-3.00 | 0/40 |
IEOR 4900 | 004/13962 | |
Daniel Bienstock | 1.00-3.00 | 0/40 |
IEOR 4900 | 005/13964 | |
Agostino Capponi | 1.00-3.00 | 1/40 |
IEOR 4900 | 006/15547 | |
Rachel Cummings | 1.00-3.00 | 0/40 |
IEOR 4900 | 007/15548 | |
Antonius Dieker | 1.00-3.00 | 0/40 |
IEOR 4900 | 008/15549 | |
Christopher Dolan | 1.00-3.00 | 0/40 |
IEOR 4900 | 009/15550 | |
Adam Elmachtoub | 1.00-3.00 | 0/40 |
IEOR 4900 | 010/15551 | |
Yuri Faenza | 1.00-3.00 | 1/40 |
IEOR 4900 | 011/15552 | |
Donald Goldfarb | 1.00-3.00 | 0/40 |
IEOR 4900 | 012/15553 | |
Vineet Goyal | 1.00-3.00 | 0/40 |
IEOR 4900 | 013/15554 | |
Ali Hirsa | 1.00-3.00 | 2/40 |
IEOR 4900 | 014/15555 | |
Anran Hu | 1.00-3.00 | 0/40 |
IEOR 4900 | 015/15556 | |
Garud Iyengar | 1.00-3.00 | 0/40 |
IEOR 4900 | 016/15557 | |
Hardeep Johar | 1.00-3.00 | 0/40 |
IEOR 4900 | 017/15558 | |
Cedric Josz | 1.00-3.00 | 0/40 |
IEOR 4900 | 018/15562 | |
Soulaymane Kachani | 1.00-3.00 | 2/40 |
IEOR 4900 | 019/15563 | |
Yaren Kaya | 1.00-3.00 | 1/40 |
IEOR 4900 | 020/15564 | |
Christian Kroer | 1.00-3.00 | 0/40 |
IEOR 4900 | 021/15565 | |
Daniel Lacker | 1.00-3.00 | 0/40 |
IEOR 4900 | 022/15568 | |
Henry Lam | 1.00-3.00 | 0/40 |
IEOR 4900 | 023/15569 | |
Fabrizio Lecci | 1.00-3.00 | 0/40 |
IEOR 4900 | 024/15570 | |
Tianyi Lin | 1.00-3.00 | 0/40 |
IEOR 4900 | 025/15573 | |
Jay Sethuraman | 1.00-3.00 | 1/40 |
IEOR 4900 | 026/15574 | |
Karl Sigman | 1.00-3.00 | 0/40 |
IEOR 4900 | 027/15572 | |
Clifford Stein | 1.00-3.00 | 0/40 |
IEOR 4900 | 028/15571 | |
Wenpin Tang | 1.00-3.00 | 0/40 |
IEOR 4900 | 029/15567 | |
Kaizheng Wang | 1.00-3.00 | 0/40 |
IEOR 4900 | 030/15566 | |
David Yao | 1.00-3.00 | 0/40 |
IEOR 4900 | 031/15561 | |
Yi Zhang | 1.00-3.00 | 0/40 |
IEOR 4900 | 032/15560 | |
Xunyu Zhou | 1.00-3.00 | 0/40 |
IEOR 4900 | 033/15559 | |
Jiaqi Li, Chris Lee | 1.00-3.00 | 0/40 |
IEOR E4998 MANAG TECH INNOV & ENTREPRENEURSHIP. 3.00 points.
Lect: 3.
A required course for undergraduate students majoring in OR:EMS. Focus on the management and consequences of technology-based innovation. Explores how new industries are created, how existing industries can be transformed by new technologies, the linkages between technological development and the creation of wealth and the management challenges of pursuing strategic innovation
Spring 2024: IEOR E4998
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4998 | 001/11616 | F 10:10am - 12:40pm 517 Hamilton Hall |
Gerard Neumann | 3.00 | 51/80 |
IEOR E4999 FIELDWORK. 1.00-1.50 points.
Prerequisites: Obtained internship and approval from faculty advisor.
Only for IEOR graduate students who need relevant work experience as part of their program of study. Final reports required. May not be taken for pass/fail credit or audited
Spring 2024: IEOR E4999
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 4999 | 001/11768 | |
Ali Hirsa, Chris Lee | 1.00-1.50 | 1/150 |
IEOR 4999 | 002/11767 | |
Hardeep Johar, Chris Lee | 1.00-1.50 | 2/150 |
IEOR 4999 | 003/11769 | |
Chris Lee, Fabrizio Lecci | 1.00-1.50 | 1/150 |
Summer 2024: IEOR E4999
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4999 | 001/12341 | |
Jiaqi Li, Ali Hirsa | 1.00-1.50 | 44/600 |
IEOR 4999 | 002/12344 | |
Jiaqi Li, Hardeep Johar | 1.00-1.50 | 98/600 |
IEOR 4999 | 003/12345 | |
Fabrizio Lecci, Jiaqi Li | 1.00-1.50 | 44/600 |
Fall 2024: IEOR E4999
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 4999 | 001/18867 | |
Ali Hirsa, Jiaqi Li, Chris Lee | 1.00-1.50 | 10/300 |
IEOR 4999 | 002/18870 | |
Hardeep Johar, Jiaqi Li, Chris Lee | 1.00-1.50 | 44/300 |
IEOR 4999 | 003/18872 | |
Jiaqi Li, Chris Lee, Fabrizio Lecci | 1.00-1.50 | 15/300 |
IEOR E6003 Prof Dev for PHDS:3rd Yr . 3.00-3.50 points.
IEOR E6004 Professional Development and Leadership for PhDs - Fourth Year and Beyond. 3.00 points.
IEOR E6602 NONLINEAR & CONVEX PROGRAMMING. 3.00 points.
Lect: 3.
Prerequisites: PhD-level Linear Programming.
Convex sets and functions, convex duality and optimality conditions. Computational methods: steepest descent, Newton and quasi-Newton methods for unconstrained problems, active set, penalty set, interior point, augmented Lagrangian and sequential quadratic programming methods for constrained problems. Introduction to nondifferentiable optimization and bundle methods
IEOR E6608 INTEGER PROGRAMMING. 3.00 points.
.
Category: MIA, MPA
Not offered during 2023-2024 academic year.
IEOR E6613 Optimization, I. 4.5 points.
Prerequisites: Refer to course syllabus.
Theory and geometry of linear programming. The simplex method. Duality theory, sensitivity analysis, column generation and decomposition. Interior point methods. Introduction to nonlinear optimization: convexity, optimality conditions, steepest descent and Newton's method, active set and barrier methods.
Fall 2024: IEOR E6613
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 6613 | 001/14599 | T Th 10:10am - 11:25am 644 Seeley W. Mudd Building |
Vineet Goyal | 4.5 | 28/40 |
IEOR E6614 OPTIMIZATION II. 4.50 points.
Lect: 3.
Prerequisites: Refer to course syllabus.
An introduction to combinatorial optimization, network flows and discrete algorithms. Shortest path problems, maximum flow problems. Matching problems, bipartite and cardinality nonbipartite. Introduction to discrete algorithms and complexity theory: NP-completeness and approximation algorithms
Spring 2024: IEOR E6614
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 6614 | 001/11953 | M W 10:10am - 11:25am 829 Seeley W. Mudd Building |
Shipra Agrawal | 4.50 | 26/40 |
IEOR E6616 CONVEX OPTIMIZATION. 3.00 points.
IEOR E6617 Machine Learning and High-Dimensional Data Analysis in Operations Research. 3.00 points.
Discusses recent advances in fields of machine learning: kernel methods, neural networks (various generative adversarial net architectures), and reinforcement learning (with applications in robotics). Quasi Monte Carlo methods in the context of approximating RBF kernels via orthogonal transforms (instances of the structured technique). Will discuss techniques such as TD(0), TD(λ), LSTDQ, LSPI, DQN
Fall 2024: IEOR E6617
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 6617 | 001/14598 | M 7:10pm - 9:40pm 524 Seeley W. Mudd Building |
Krzysztof Choromanski | 3.00 | 54/55 |
IEOR 6617 | V01/17559 | |
Krzysztof Choromanski | 3.00 | 7/99 |
IEOR E6704 QUEUING THEORY & APPLICATIONS. 3.00 points.
IEOR E6706 QUEUEING NETWORKS. 3.00 points.
IEOR E6711 STOCHASTIC MODELING I. 4.50 points.
Prerequisites: (STAT GU4001) or Refer to course syllabus.
Advanced treatment of stochastic modeling in the context of queueing, reliability, manufacturing, insurance risk, financial engineering and other engineering applications. Review of elements of probability theory; exponential distribution; renewal theory; Wald’s equation; Poisson processes. Introduction to both discrete and continuous-time Markov chains; introduction to Brownian motion
Fall 2024: IEOR E6711
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 6711 | 001/14603 | T Th 11:40am - 12:55pm 829 Seeley W. Mudd Building |
Henry Lam | 4.50 | 31/40 |
IEOR E6712 STOCHASTIC MODELING II. 4.50 points.
Prerequisites: (IEOR E6711) or Refer to course syllabus.
Continuation of IEOR E6711, covering further topics in stochastic modeling in the context of queueing, reliability, manufacturing, insurance risk, financial engineering, and other engineering applications. Topics from among generalized semi-Markov processes; processes with a non-discrete state space; point processes; stochastic comparisons; martingales; introduction to stochastic calculus
Spring 2024: IEOR E6712
|
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 6712 | 001/11950 | T Th 11:40am - 12:55pm 415 Schapiro Cepser |
Antonius Dieker | 4.50 | 20/40 |
IEOR E8100 ADVANCED TOPICS IN IEOR. 3.00 points.
Prerequisites: Faculty adviser's permission.
Selected topics in IEOR. Content varies from year to year. May be repeated for credit
Spring 2024: IEOR E8100
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 8100 | 002/11959 | M W 11:40am - 12:55pm 829 Seeley W. Mudd Building |
Anish Agarwal | 3.00 | 27/30 |
Fall 2024: IEOR E8100
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 8100 | 001/14606 | W 10:10am - 12:40pm Room TBA |
Xunyu Zhou | 3.00 | 10/30 |
IEOR 8100 | 002/14608 | M W 11:40am - 12:55pm 337 Seeley W. Mudd Building |
Shipra Agrawal | 3.00 | 20/30 |
IEOR 8100 | 004/14610 | F 10:10am - 12:40pm 825 Seeley W. Mudd Building |
Adam Elmachtoub | 3.00 | 17/30 |
IEOR 8100 | 005/15872 | Th 2:40pm - 5:10pm 516 Hamilton Hall |
Martin Reiman | 3.00 | 4/30 |
IEOR 8100 | 006/17498 | T Th 10:10am - 11:25am 522d Kent Hall |
Clifford Stein | 3.00 | 11/13 |
IEOR E9101 RESEARCH. 1.00-6.00 points.
Before registering, the student must submit an outline of the proposed work for approval by the supervisor and the chair of the Department. Advanced study in a specialized field under the supervision of a member of the department staff. May be repeated for credit
Summer 2024: IEOR E9101
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
IEOR 9101 | 001/12454 | |
Anish Agarwal | 1.00-6.00 | 0/20 |
IEOR 9101 | 002/12460 | |
Shipra Agrawal | 1.00-6.00 | 0/20 |
IEOR 9101 | 003/12464 | |
Eric Balkanski | 1.00-6.00 | 0/20 |
IEOR 9101 | 004/12466 | |
Daniel Bienstock | 1.00-6.00 | 0/20 |
IEOR 9101 | 005/12468 | |
Agostino Capponi | 1.00-6.00 | 0/20 |
IEOR 9101 | 006/12470 | |
Rachel Cummings | 1.00-6.00 | 0/20 |
IEOR 9101 | 007/12471 | |
Antonius Dieker | 1.00-6.00 | 0/20 |
IEOR 9101 | 008/12472 | |
Christopher Dolan | 1.00-6.00 | 0/20 |
IEOR 9101 | 009/12473 | |
Adam Elmachtoub | 1.00-6.00 | 0/20 |
IEOR 9101 | 010/12474 | |
Yuri Faenza | 1.00-6.00 | 0/20 |
IEOR 9101 | 011/12475 | |
Donald Goldfarb | 1.00-6.00 | 0/20 |
IEOR 9101 | 012/12476 | |
Vineet Goyal | 1.00-6.00 | 0/20 |
IEOR 9101 | 013/12477 | |
Ali Hirsa | 1.00-6.00 | 0/20 |
IEOR 9101 | 014/12478 | |
Anran Hu | 1.00-6.00 | 0/20 |
IEOR 9101 | 015/12479 | |
Garud Iyengar | 1.00-6.00 | 0/20 |
IEOR 9101 | 016/12480 | |
Hardeep Johar | 1.00-6.00 | 0/20 |
IEOR 9101 | 017/12481 | |
Cedric Josz | 1.00-6.00 | 0/20 |
IEOR 9101 | 018/12461 | |
Soulaymane Kachani | 1.00-6.00 | 0/20 |
IEOR 9101 | 019/12462 | |
Yaren Kaya | 1.00-6.00 | 0/20 |
IEOR 9101 | 020/12463 | |
Christian Kroer | 1.00-6.00 | 0/20 |
IEOR 9101 | 021/12465 | |
Daniel Lacker | 1.00-6.00 | 0/20 |
IEOR 9101 | 022/12467 | |
Henry Lam | 1.00-6.00 | 0/20 |
IEOR 9101 | 023/12469 | |
Fabrizio Lecci | 1.00-6.00 | 0/20 |
IEOR 9101 | 024/12482 | |
Tianyi Lin | 1.00-6.00 | 0/20 |
IEOR 9101 | 025/12484 | |
Jay Sethuraman | 1.00-6.00 | 0/20 |
IEOR 9101 | 026/12485 | |
Karl Sigman | 1.00-6.00 | 0/20 |
IEOR 9101 | 027/12486 | |
Clifford Stein | 1.00-6.00 | 0/20 |
IEOR 9101 | 028/12487 | |
Wenpin Tang | 1.00-6.00 | 0/20 |
IEOR 9101 | 029/12488 | |
Kaizheng Wang | 1.00-6.00 | 0/20 |
IEOR 9101 | 030/12489 | |
David Yao | 1.00-6.00 | 0/20 |
IEOR 9101 | 031/12490 | |
Yi Zhang | 1.00-6.00 | 0/20 |
IEOR 9101 | 032/12491 | |
Xunyu Zhou | 1.00-6.00 | 0/20 |
IEOR 9101 | 033/12492 | |
Winsor Yang | 1.00-6.00 | 0/20 |
Fall 2024: IEOR E9101
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
IEOR 9101 | 001/15575 | |
Anish Agarwal | 1.00-6.00 | 1/20 |
IEOR 9101 | 002/15576 | |
Shipra Agrawal | 1.00-6.00 | 0/20 |
IEOR 9101 | 003/15577 | |
Eric Balkanski | 1.00-6.00 | 0/20 |
IEOR 9101 | 004/15578 | |
Daniel Bienstock | 1.00-6.00 | 0/20 |
IEOR 9101 | 005/15580 | |
Agostino Capponi | 1.00-6.00 | 3/20 |
IEOR 9101 | 006/15581 | |
Rachel Cummings | 1.00-6.00 | 0/20 |
IEOR 9101 | 007/15582 | |
Antonius Dieker | 1.00-6.00 | 1/20 |
IEOR 9101 | 008/15586 | |
Christopher Dolan | 1.00-6.00 | 0/20 |
IEOR 9101 | 009/15587 | |
Adam Elmachtoub | 1.00-6.00 | 1/20 |
IEOR 9101 | 010/15588 | |
Yuri Faenza | 1.00-6.00 | 0/20 |
IEOR 9101 | 011/15590 | |
Donald Goldfarb | 1.00-6.00 | 0/20 |
IEOR 9101 | 012/15593 | |
Vineet Goyal | 1.00-6.00 | 1/20 |
IEOR 9101 | 013/15594 | |
Ali Hirsa | 1.00-6.00 | 1/20 |
IEOR 9101 | 014/15596 | |
Anran Hu | 1.00-6.00 | 0/20 |
IEOR 9101 | 015/15598 | |
Garud Iyengar | 1.00-6.00 | 0/20 |
IEOR 9101 | 016/15599 | |
Hardeep Johar | 1.00-6.00 | 0/20 |
IEOR 9101 | 017/15601 | |
Cedric Josz | 1.00-6.00 | 0/20 |
IEOR 9101 | 018/15602 | |
Soulaymane Kachani | 1.00-6.00 | 0/20 |
IEOR 9101 | 019/15604 | |
Yaren Kaya | 1.00-6.00 | 0/20 |
IEOR 9101 | 020/15605 | |
Christian Kroer | 1.00-6.00 | 3/20 |
IEOR 9101 | 021/15606 | |
Daniel Lacker | 1.00-6.00 | 0/20 |
IEOR 9101 | 022/15607 | |
Henry Lam | 1.00-6.00 | 1/20 |
IEOR 9101 | 023/15603 | |
Fabrizio Lecci | 1.00-6.00 | 0/20 |
IEOR 9101 | 024/15600 | |
Tianyi Lin | 1.00-6.00 | 0/20 |
IEOR 9101 | 025/15597 | |
Jay Sethuraman | 1.00-6.00 | 0/20 |
IEOR 9101 | 026/15595 | |
Karl Sigman | 1.00-6.00 | 0/20 |
IEOR 9101 | 027/15592 | |
Clifford Stein | 1.00-6.00 | 1/20 |
IEOR 9101 | 028/15591 | |
Wenpin Tang | 1.00-6.00 | 0/20 |
IEOR 9101 | 029/15589 | |
Kaizheng Wang | 1.00-6.00 | 2/20 |
IEOR 9101 | 030/15585 | |
David Yao | 1.00-6.00 | 0/20 |
IEOR 9101 | 031/15584 | |
Yi Zhang | 1.00-6.00 | 0/20 |
IEOR 9101 | 032/15583 | |
Xunyu Zhou | 1.00-6.00 | 0/20 |
IEOR 9101 | 033/15579 | |
Winsor Yang | 1.00-6.00 | 6/20 |
IEOR E9800 DOCTORAL RESEARCH INSTRUCTION. 3.00-12.00 points.
MEIE E4810 INTRO TO HUMAN SPACE FLIGHT. 3.00 points.
Prerequisites: Department permission and knowledge of MATLAB or equivalent
Introduction to human spaceflight from a systems engineering perspective. Historical and current space programs and spacecraft. Motivation, cost, and rationale for human space exploration. Overview of space environment needed to sustain human life and health, including physiological and psychological concerns in space habitat. Astronaut selection and training processes, spacewalking, robotics, mission operations, and future program directions. Systems integration for successful operation of a spacecraft. Highlights from current events and space research, Space Shuttle, Hubble Space Telescope, and International Space Station (ISS). Includes a design project to assist International Space Station astronauts
MSIE W6408 Inventory Theory. 3 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: Probability theory, dynamic programming.
Construction and analysis of mathematical models used in the design and analysis of inventory systems. Deterministic and stochastic demands and lead times. Optimality of (s, S) policies. Multiproduct and multiechelon systems. Computational methods.
ORCS E4200 Data-driven Decision Modeling. 3.00 points.
Introduction to modeling, estimating, and solving decision-making problems in the context of artificial intelligence and analytics. Potential topics include choice models, quantity models, online learning using multi-armed bandits, dynamic decision modeling, dynamic games, and Bayesian learning theory. Practice both theory and applications using Python programming
Fall 2024: ORCS E4200
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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ORCS 4200 | 001/11995 | M W 2:40pm - 3:55pm 303 Seeley W. Mudd Building |
Tony Dear | 3.00 | 54/70 |
ORCS E4201 Policy for Privacy Technologies. 3.00 points.
Introduction to privacy technologies, their use in practice, and privacy regulations. Potential topics include anonymization, differential privacy, cryptography, secure multi-party computation, and legislation. Course material will be abased in real-world use cases of these tools
ORCS E4529 Reinforcement Learning. 3.00 points.
Markov Decision Processes (MDP) and Reinforcement Learning (RL) problems. Reinforcement Learning algorithms including Q-learning, policy gradient methods, actor-critic method. Reinforcement learning while doing exploration-exploitation dilemma, multi-armed bandit problem. Monte Carlo Tree Search methods, Distributional, Multi-agent, and Causal Reinforcement Learning
Fall 2024: ORCS E4529
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
ORCS 4529 | 001/14542 | M W 1:10pm - 2:25pm 330 Uris Hall |
Shipra Agrawal | 3.00 | 65/60 |
ORCA E2500 FOUNDATIONS OF DATA SCIENCE. 3.00 points.
Prerequisites: MATH UN1101 and MATH UN1102 Some familiarity with programming
Designed to provide an introduction to data science for sophomore SEAS majors. Combines three perspectives: inferential thinking, computational thinking, and real-world applications. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? Teaches critical concepts and skills in computer programming, statistical inference, and machine learning, in conjunction with hands-on analysis of real-world datasets such as economic data, document collections, geographical data, and social networks. At least one project will address a problem relevant to New York City
Spring 2024: ORCA E2500
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
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ORCA 2500 | 001/12040 | T Th 11:40am - 12:55pm 627 Seeley W. Mudd Building |
Uday Menon | 3.00 | 47/50 |
Fall 2024: ORCA E2500
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Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
ORCA 2500 | 001/14541 | T Th 2:40pm - 3:55pm 603 Hamilton Hall |
Clifford Stein | 3.00 | 50/50 |
CSOR E4010 GRAPH THEORY: COMBINATL VIEW. 3.00 points.
Lect: 3.Not offered during 2023-2024 academic year.
Prerequisites: Linear Algebra, or instructor's permission.
An introductory course in graph theory with emphasis on its combinatorial aspects. Basic definitions, and some fundamental topics in graph theory and its applications. Topics include trees and forests graph coloring, connectivity, matching theory and others
ORCS E4200 Data-driven Decision Modeling. 3.00 points.
Introduction to modeling, estimating, and solving decision-making problems in the context of artificial intelligence and analytics. Potential topics include choice models, quantity models, online learning using multi-armed bandits, dynamic decision modeling, dynamic games, and Bayesian learning theory. Practice both theory and applications using Python programming
Fall 2024: ORCS E4200
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
ORCS 4200 | 001/11995 | M W 2:40pm - 3:55pm 303 Seeley W. Mudd Building |
Tony Dear | 3.00 | 54/70 |
ORCA E4500 FOUNDATIONS OF DATA SCIENCE. 3.00 points.
Prerequisites: Note re: Pre-requisites: Calculus I and II; Some familiarity with programming
Designed to provide an introduction to data science for sophomore SEAS majors. Combines three perspectives: inferential thinking, computational thinking, and real-world applications. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? Teaches critical concepts and skills in computer programming, statistical inference, and machine learning, in conjunction with hands-on analysis of real-world datasets such as economic data, document collections, geographical data, and social networks
ORCS E4529 Reinforcement Learning. 3.00 points.
Markov Decision Processes (MDP) and Reinforcement Learning (RL) problems. Reinforcement Learning algorithms including Q-learning, policy gradient methods, actor-critic method. Reinforcement learning while doing exploration-exploitation dilemma, multi-armed bandit problem. Monte Carlo Tree Search methods, Distributional, Multi-agent, and Causal Reinforcement Learning
Fall 2024: ORCS E4529
|
|||||
Course Number | Section/Call Number | Times/Location | Instructor | Points | Enrollment |
---|---|---|---|---|---|
ORCS 4529 | 001/14542 | M W 1:10pm - 2:25pm 330 Uris Hall |
Shipra Agrawal | 3.00 | 65/60 |
ORCS E4201 Policy for Privacy Technologies. 3.00 points.
Introduction to privacy technologies, their use in practice, and privacy regulations. Potential topics include anonymization, differential privacy, cryptography, secure multi-party computation, and legislation. Course material will be abased in real-world use cases of these tools