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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
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
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3658 001/11818 T Th 10:10am - 11:25am
310 Fayerweather
Daniel Lacker 3.00 83/96
Fall 2024: IEOR E3658
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4721 001/11766  
Ali Hirsa 3.00 74/75
Summer 2024: IEOR E4721
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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

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
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
Course Number Section/Call Number Times/Location Instructor Points Enrollment
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
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