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

Antonius (Ton) Dieker

Director of Finance and Operations

Shi Yee Lee

Senior Associate Director of Academic and Student Affairs

Christine Chan

Director of Career Placement

Lucy Mahbub

Director of Undergraduate Programs

Yi Zhang

Director of Financial Engineering

Ali Hirsa

Director of Management Science and Engineering

Hardeep Johar

Director of Business Analytics

Hardeep Johar

Director of Industrial Engineering

Fabrizio Lecci

Director of Operations Research

Fabrizio Lecci

Director of Doctoral Programs

Yuri Faenza
Henry Lam

Professors

Vineet Goyal
Daniel Bienstock
Agostino Capponi
Ton Dieker
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
Christian Kroer
Daniel Lacker
Henry Lam

Assistant Professors

Anish Agarwal
Eric Balkanski
Anran Hu
Cédric Josz
Christian Kroer
Tianyi Lin
Bento Natura
Wenpin Tang
Kaizheng Wang
Lily Xu

Senior Lecturer in Discipline

Hardeep Johar
Yi Zhang

Lecturers in Discipline

Yaren Kaya
Eric Stratman
Uday Menon

Adjunct Faculty

Amit Arora
Dave Begun
Luca Capriotti
Nicolas Chikhani
Krzysztof Choromanski
Naftali Cohen
Siddhartha Dastidar
Owen Davis
Kosrow Dehnad
David DeRosa
Sebastien Donadio
Tony Effik
Daniel Fernandez
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
Ali Sadighian
Cyril Shmatov
Andrei Simion
Rodney Sunada-Wong
Maya Waisman
Nadejda Zaets

For up-to-date course offerings, please visit ieor.columbia.edu

Course Descriptions

CEOR E4011 INFRASTRUCTURE SYSTEMS OPTIMIZATION. 3.00 points.

Lect.: 3.

Prerequisites: Basic linear algebra. Basic probability and statistics.
Engineering economic concepts. Basic spreadsheet analysis and programming skills. Subject to instructor's permission. Infrastructure design and systems concepts, analysis, and design under competing/conflicting objectives, transportation network models, traffic assignments, optimization, and the simplex algorithm

Fall 2025: CEOR E4011
Course Number Section/Call Number Times/Location Instructor Points Enrollment
CEOR 4011 001/12623 W 7:00pm - 9:30pm
Room TBA
Xuan Di 3.00 4/30

CSOR E4231 ANALYSIS OF ALGORITHMS I. 3.00 points.

Prerequisites: COMS W3134 AND COMS W3136 OR COMS W3137 AND COMS W3203
Prerequisites: COMS W3134, COMS W3136, or COMS W3137, and COMS W3203. Introduction to the design and analysis of efficient algorithms. Topics include models of computation, efficient sorting and searching, algorithms for algebraic problems, graph algorithms, dynamic programming, probabilistic methods, approximation algorithms, and NP-completeness

Spring 2025: CSOR E4231
Course Number Section/Call Number Times/Location Instructor Points Enrollment
CSOR 4231 001/14592 M W 11:40am - 12:55pm
303 Seeley W. Mudd Building
Rachel Cummings 3.00 45/55

CSOR W4246 ALGORITHMS FOR DATA SCIENCE. 3.00 points.

Prerequisites: COMS W1007 Basic knowledge in programming (e.g. at the level of COMS W1007), a basic grounding in calculus and linear algebra.
Corequisites: COMS W4121

Methods for organizing data, e.g. hashing, trees, queues, lists,priority queues. Streaming algorithms for computing statistics on the data. Sorting and searching. Basic graph models and algorithms for searching, shortest paths, and matching. Dynamic programming. Linear and convex programming. Floating point arithmetic, stability of numerical algorithms, Eigenvalues, singular values, PCA, gradient descent, stochastic gradient descent, and block coordinate descent. Conjugate gradient, Newton and quasi-Newton methods. Large scale applications from signal processing, collaborative filtering, recommendations systems, etc.

Fall 2025: CSOR W4246
Course Number Section/Call Number Times/Location Instructor Points Enrollment
CSOR 4246 001/10994 T Th 11:40am - 12:55pm
Room TBA
Eleni Drinea 3.00 0/120
CSOR 4246 002/10995 T Th 1:10pm - 2:25pm
Room TBA
Eleni Drinea 3.00 0/120

DROM B8000 OPTIMIZATION & SIMULATION BOOTCAMP. 0.00 points.

Fall 2025: DROM B8000
Course Number Section/Call Number Times/Location Instructor Points Enrollment
DROM 8000 060/11861  
Michael Miller 0.00 0/120

DROM B8106 Operations Strategy. 3.00 points.

Prerequisites: DROM B5101 OR DROM B6101
Operations Strategy

Spring 2025: DROM B8106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
DROM 8106 060/16806 Th 9:00am - 12:15pm
640 Geffen Hall
Medini Singh 3.00 63/65
DROM 8106 062/16807 Th 2:20pm - 5:35pm
640 Geffen Hall
Medini Singh 3.00 57/65
Summer 2025: DROM B8106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
DROM 8106 001/10978 M T W Th S 9:00am - 5:00pm
440 Kravis Hall
Medini Singh 3.00 65/65

DROM B8107 Service Operations Management. 3.00 points.

Prerequisites: DROM B6102 OR DROM B5102

Fall 2025: DROM B8107
Course Number Section/Call Number Times/Location Instructor Points Enrollment
DROM 8107 061/16471 Th 2:20pm - 5:35pm
640 Geffen Hall
Medini Singh 3.00 0/65

DROM B8116 Risk Management. 3.00 points.

Spring 2025: DROM B8116
Course Number Section/Call Number Times/Location Instructor Points Enrollment
DROM 8116 060/16805 M W 6:00pm - 7:30pm
640 Geffen Hall
Evan Picoult 3.00 69/74

DROM B8123 Demand Analytics. 3.00 points.

Lect: 3.Not offered during 2024-2025 academic year.

Prerequisites: (IEOR E3608) or (IEOR E4004) and (IEOR E4106) or

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. 

DROM B8131 Sports Analytics. 3.00 points.

Summer 2025: DROM B8131
Course Number Section/Call Number Times/Location Instructor Points Enrollment
DROM 8131 001/10966 M T W Th F 9:00am - 5:00pm
520 Geffen Hall
Mark Broadie 3.00 74/74
Fall 2025: DROM B8131
Course Number Section/Call Number Times/Location Instructor Points Enrollment
DROM 8131 001/16371 F M 2:20pm - 5:35pm
840 Kravis Hall
Mark Broadie 3.00 0/74

DROM B8153 People Analytics: Creating Business Value from Data. 1.50 point.

DROM B8510 MANAGERIAL NEGOTIATIONS. 3.00 points.

DROM B8816 Quantitative Pricing & Revenue. 1.50 point.

Prerequisites: Familiar with the content covered in the managerial statistics, business analytics, managerial economics and marketing core courses. Knowledge in managerial statistics, probability, probability distributions, expected value calculations, etc
Quantitative pricing and revenue analytics collectively refers to the set of practices and tools that firms in various industries use to quantitatively model consumer preferences, segment their market, and tactically optimize (often in micro targeted or personalized manner) their product assortment, pricing, and promotion strategies. The origins of this field, often referred to as revenue management as it is also called, are in the airline industry during the late 80s. The prototypical question is how a firm should set and update pricing and product availability decisions across its various selling channels in order to maximize its profitability. In the airline industry, as most of us know, tickets for the same flight may be sold at many different fares, the availability of which is changing as a function of purchase restrictions, the forecasted future demand, and the number of unsold seats. The adoption of such systems has transformed the transportation and hospitality industries, and is increasingly important in retail, telecommunications, entertainment, financial services, health care, manufacturing, as well as on-line advertising, online retailing, and online markets. In parallel, pricing and revenue optimization has become a rapidly expanding practice in consulting services, and a growing area of software and IT development. We will be doing a hands-on dive into the above tools in the context of 2-3 case studies and datasets, in conjunction with lectures to set the stage. The case studies will cover markdown pricing for a retailer, demand and inventory data for a self-storage company, customer research data of a mortgage lender, and peak load pricing data for a highway toll booth.Through this course, students will be able to model and identify opportunities for revenue optimization in different business contexts. As the ensuing outline reveals, most of the topics covered in the course are either directly or indirectly related to customer segmentation, demand modeling, and tactical price optimization.TextbookOne recommended book for the course is by Robert Phillips titled "Pricing and Revenue Optimization. This will primarily be done in teams, much of it in class, and with the help of the TA(s) and the professor. Sample code will be shared for various parts of these analyses. Course deliverables align. Apart from class participation (30% of the total grade), the other course deliverables consist of a set of in-class (homework) assignments (40%) and a take-home final exam (30%).Class participation: I will routinely ask that you review some material, or watch some short recor

EEOR E4650 CONVEX OPTIMIZATION FOR ENG. 3.00 points.

Lect: 3.

Prerequisites: (ELEN E3801) or ELEN E3801; or instructor's permission.
Theory of convex optimization; numerical algorithms; applications in circuits, communications, control, signal processing and power systems

Spring 2025: EEOR E4650
Course Number Section/Call Number Times/Location Instructor Points Enrollment
EEOR 4650 001/19102 M 4:10pm - 6:40pm
633 Seeley W. Mudd Building
Marco Moretti 3.00 10/60
Fall 2025: EEOR E4650
Course Number Section/Call Number Times/Location Instructor Points Enrollment
EEOR 4650 001/11267 M W 10:10am - 11:25am
Room TBA
3.00 15/60

EEOR E6616 CONVEX OPTIMIZATION. 3.00 points.

Lect: 2.5.

Prerequisites: (IEOR E6613) and (EEOR E4650) EEOR E4650 AND IEOR E6613
Convex sets and functions, and operations preserving convexity. Convex optimization problems. Convex duality. Applications of convex optimization problems ranging from signal processing and information theory to revenue management. Convex optimization in Banach spaces. Algorithms for solving constrained convex optimization problems

Spring 2025: EEOR E6616
Course Number Section/Call Number Times/Location Instructor Points Enrollment
EEOR 6616 001/14593 F 10:10am - 12:40pm
627 Seeley W. Mudd Building
Tianyi Lin, Cedric Josz 3.00 16/50

ENGI E4300 Design Justice: Human-Centered Design and Social Justice. 3.00 points.

Prerequisites: IEME E4200 or COMS W4170 Or instructor's permission.

Introduction to Human-Centered Design and Innovation. Unpack the role of design in the market economy for an individual consumer, for a designer/developer and for an enterprise or other organization. Consider how designing in good faith for most can lead to injustice for some. Examine how - to use the PROP framework of the Columbia School of Social Work[1] - power, race, oppression, and privilege can be executed through the design process. Equip students with tools to engage in the design process and to facilitate the engagement of others. Explore strategies for guiding design and innovation towards more just solutions. [1] https://socialwork.columbia.edu/about/dei/dei-mission-statement/

IEME E4200 HUMAN-CENTERED DESIGN AND INNOVATION. 3.00 points.

Prerequisites: Instructor's permission.
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

Spring 2025: IEME E4200
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEME 4200 001/14594 W 10:10am - 11:25am
301 Uris Hall
Harry West 3.00 50/60
IEME 4200 001/14594 W 1:10pm - 2:25pm
None None
Harry West 3.00 50/60
IEME 4200 002/14595 W 10:10am - 11:25am
301 Uris Hall
Harry West 3.00 59/60
IEME 4200 002/14595 W 4:10pm - 5:25pm
None None
Harry West 3.00 59/60
Fall 2025: IEME E4200
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEME 4200 001/11794 T 4:10pm - 6:40pm
Room TBA
Harry West 3.00 16/50

IEME E4810 INTRO-HUMANS IN 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

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 2025: IEOR E1000
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 1000 001/14597 F 1:30pm - 2:30pm
633 Seeley W. Mudd Building
Yi Zhang 1.00 40/60

IEOR E2000 Data Engineering with Python. 3.00 points.

Prerequisites: ENGI E1006; Or competency in Python.
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 2025: IEOR E2000
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 2000 001/14598 M W 2:40pm - 3:55pm
303 Seeley W. Mudd Building
Yi Zhang 3.00 50/50

IEOR E2261 ACCOUNTING AND FINANCE. 3.00 points.

Lect: 3.

Prerequisites: (ECON UN1105) ECON W1105
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 2025: IEOR E2261
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 2261 001/11795 T Th 1:10pm - 2:25pm
Room TBA
Christopher Perez 3.00 120/120

IEOR E3106 STOCHASTIC SYSTEMS AND APPLICATIONS. 3.00 points.

Lect: 3.

Prerequisites: (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 fifth semester.
Corequisites: IEOR E4404

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 2025: IEOR E3106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3106 001/11796 M W 11:40am - 12:55pm
Room TBA
Kaizheng Wang 3.00 65/100

IEOR E3402 PRODUCTN-INVENTORY PLAN-CONTRL. 4.00 points.

Lect: 3. Recit: 1.

Prerequisites: (IEOR E3608) and (IEOR E3658) and IEOR E3608 AND IEOR E3658
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 2025: IEOR E3402
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3402 001/14599 M W 8:40am - 9:55am
833 Seeley W. Mudd Building
Ali Sadighian 4.00 27/90

IEOR E3404 SIMULATION MODELING AND ANALYSIS. 4.00 points.

Prerequisites: Knowledge of a programming language such as Python, C, C++ or Matlab

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 2025: IEOR E3404
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3404 001/14600 M W 5:40pm - 6:55pm
142 Uris Hall
Yi Zhang 4.00 78/90

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 2025: IEOR E3608
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3608 001/11797 T Th 10:10am - 11:25am
Room TBA
Eric Balkanski 3.00 58/100

IEOR E3609 ADVANCED OPTIMIZATION. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E3608) 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 2025: IEOR E3609
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3609 001/14602 T Th 11:40am - 12:55pm
517 Hamilton Hall
Bento Natura 3.00 64/80

IEOR E3658 PROBABILITY FOR ENGINEERS. 3.00 points.

Lect: 3.

Prerequisites: Calculus. For undergraduates only. Required for OR:FE concentration. Must be taken during or before third semester. Students who take IEOR E3658 may not take W4150 due to significant overlap. Recommended: strong mathematical skills.
Corequisites: ELEN E3701

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 2025: IEOR E3658
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3658 001/14603 T Th 10:10am - 11:25am
301 Uris Hall
Kaizheng Wang 3.00 108/120
Fall 2025: IEOR E3658
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3658 001/11798 M W 2:40pm - 3:55pm
Room TBA
Kaizheng Wang 3.00 84/120

IEOR E3700 Research Immersion in OR and Data Analytics. 3.00 points.

Prerequisites: IEOR E3608 AND IEOR E3658 AND IEOR E4307; For IEOR undergraduates only.
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 2025: IEOR E3700
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3700 001/14604 T Th 2:40pm - 3:55pm
825 Seeley W. Mudd Building
Eric Balkanski 3.00 10/20

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 2025: IEOR E3900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3900 001/18588  
Anish Agarwal 1.00-3.00 0/40
IEOR 3900 002/18589  
Shipra Agrawal 1.00-3.00 0/40
IEOR 3900 003/18590  
Eric Balkanski 1.00-3.00 0/40
IEOR 3900 004/18591  
Daniel Bienstock 1.00-3.00 0/40
IEOR 3900 005/18592  
Agostino Capponi 1.00-3.00 0/40
IEOR 3900 006/18593  
Rachel Cummings 1.00-3.00 0/40
IEOR 3900 007/18594  
Antonius Dieker 1.00-3.00 0/40
IEOR 3900 008/18595  
Adam Elmachtoub 1.00-3.00 0/40
IEOR 3900 009/18596  
Yuri Faenza 1.00-3.00 0/40
IEOR 3900 010/18597  
Vineet Goyal 1.00-3.00 0/40
IEOR 3900 011/18598  
Ali Hirsa 1.00-3.00 1/40
IEOR 3900 012/18599  
Anran Hu 1.00-3.00 0/40
IEOR 3900 013/18600  
Garud Iyengar 1.00-3.00 0/40
IEOR 3900 014/18601  
Hardeep Johar 1.00-3.00 0/40
IEOR 3900 015/18602  
Cedric Josz 1.00-3.00 0/40
IEOR 3900 016/18603  
Soulaymane Kachani 1.00-3.00 7/40
IEOR 3900 017/18604  
Yaren Kaya 1.00-3.00 0/40
IEOR 3900 018/18605  
Christian Kroer 1.00-3.00 0/40
IEOR 3900 019/18606  
Daniel Lacker 1.00-3.00 0/40
IEOR 3900 020/18607  
Henry Lam 1.00-3.00 0/40
IEOR 3900 021/18608  
Fabrizio Lecci 1.00-3.00 0/40
IEOR 3900 022/18609  
Tianyi Lin 1.00-3.00 1/40
IEOR 3900 023/18610  
Uday Menon 1.00-3.00 0/40
IEOR 3900 024/18611  
Bento Natura 1.00-3.00 0/40
IEOR 3900 025/18612  
Jay Sethuraman 1.00-3.00 0/40
IEOR 3900 026/18613  
Karl Sigman 1.00-3.00 0/40
IEOR 3900 027/18614  
Clifford Stein 1.00-3.00 0/40
IEOR 3900 028/18615  
Wenpin Tang 1.00-3.00 0/40
IEOR 3900 029/18616  
Kaizheng Wang 1.00-3.00 0/40
IEOR 3900 030/18617  
David Yao 1.00-3.00 0/40
IEOR 3900 031/18618  
Yi Zhang 1.00-3.00 8/40
IEOR 3900 032/18619  
Xunyu Zhou 1.00-3.00 0/40
IEOR 3900 033/18620  
Kelly Katsigris 1.00-3.00 0/10
Summer 2025: IEOR E3900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3900 001/11632  
Anish Agarwal 1.00-3.00 0/40
IEOR 3900 002/11633  
Shipra Agrawal 1.00-3.00 0/40
IEOR 3900 003/11634  
Eric Balkanski 1.00-3.00 0/40
IEOR 3900 004/11635  
Daniel Bienstock 1.00-3.00 0/40
IEOR 3900 005/11636  
Agostino Capponi 1.00-3.00 0/40
IEOR 3900 006/11637  
Rachel Cummings 1.00-3.00 0/40
IEOR 3900 007/11638  
Antonius Dieker 1.00-3.00 0/40
IEOR 3900 008/11639  
Adam Elmachtoub 1.00-3.00 0/40
IEOR 3900 009/11640  
Yuri Faenza 1.00-3.00 0/40
IEOR 3900 010/11641  
Vineet Goyal 1.00-3.00 0/40
IEOR 3900 011/11642  
Ali Hirsa 1.00-3.00 0/40
IEOR 3900 012/11643  
Anran Hu 1.00-3.00 0/40
IEOR 3900 013/11644  
Garud Iyengar 1.00-3.00 0/40
IEOR 3900 014/11645  
Hardeep Johar 1.00-3.00 0/40
IEOR 3900 015/11646  
Cedric Josz 1.00-3.00 0/40
IEOR 3900 016/11647  
Soulaymane Kachani 1.00-3.00 0/40
IEOR 3900 017/11648  
Yaren Kaya 1.00-3.00 0/40
IEOR 3900 018/11649  
Christian Kroer 1.00-3.00 0/40
IEOR 3900 019/11650  
Daniel Lacker 1.00-3.00 0/40
IEOR 3900 020/11651  
Henry Lam 1.00-3.00 0/40
IEOR 3900 021/11652  
Fabrizio Lecci 1.00-3.00 0/40
IEOR 3900 022/11653  
Tianyi Lin 1.00-3.00 0/40
IEOR 3900 023/11654  
Uday Menon 1.00-3.00 0/40
IEOR 3900 024/11655  
Bento Natura 1.00-3.00 0/40
IEOR 3900 025/11656  
Jay Sethuraman 1.00-3.00 0/40
IEOR 3900 026/11657  
Karl Sigman 1.00-3.00 0/40
IEOR 3900 027/11658  
Clifford Stein 1.00-3.00 0/40
IEOR 3900 028/11659  
Wenpin Tang 1.00-3.00 0/40
IEOR 3900 029/11660  
Kaizheng Wang 1.00-3.00 0/40
IEOR 3900 030/11661  
Lily Xu 1.00-3.00 0/40
IEOR 3900 031/11662  
David Yao 1.00-3.00 0/40
IEOR 3900 032/11663  
Yi Zhang 1.00-3.00 0/40
IEOR 3900 033/11664  
Xunyu Zhou 1.00-3.00 0/40
IEOR 3900 034/11665  
Kelly Katsigris 1.00-3.00 0/33
Fall 2025: IEOR E3900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3900 001/11504  
Anish Agarwal 1.00-3.00 0/40
IEOR 3900 002/11505  
Shipra Agrawal 1.00-3.00 0/40
IEOR 3900 003/11506  
Eric Balkanski 1.00-3.00 0/40
IEOR 3900 004/11507  
Daniel Bienstock 1.00-3.00 0/40
IEOR 3900 005/11508  
Agostino Capponi 1.00-3.00 0/40
IEOR 3900 006/11509  
Rachel Cummings 1.00-3.00 0/40
IEOR 3900 007/11510  
Antonius Dieker 1.00-3.00 0/40
IEOR 3900 008/11511  
Adam Elmachtoub 1.00-3.00 0/40
IEOR 3900 009/11512  
Yuri Faenza 1.00-3.00 0/40
IEOR 3900 010/11513  
Vineet Goyal 1.00-3.00 0/40
IEOR 3900 011/11514  
Ali Hirsa 1.00-3.00 0/40
IEOR 3900 012/11515  
Anran Hu 1.00-3.00 0/40
IEOR 3900 013/11516  
Garud Iyengar 1.00-3.00 0/40
IEOR 3900 014/11517  
Hardeep Johar 1.00-3.00 0/40
IEOR 3900 015/11518  
Cedric Josz 1.00-3.00 0/40
IEOR 3900 016/11519  
Soulaymane Kachani 1.00-3.00 1/40
IEOR 3900 017/11520  
Yaren Kaya 1.00-3.00 0/40
IEOR 3900 018/11521  
Christian Kroer 1.00-3.00 0/40
IEOR 3900 019/11522  
Daniel Lacker 1.00-3.00 0/40
IEOR 3900 020/11523  
Henry Lam 1.00-3.00 0/40
IEOR 3900 021/11524  
Fabrizio Lecci 1.00-3.00 0/40
IEOR 3900 022/11525  
Tianyi Lin 1.00-3.00 0/40
IEOR 3900 023/11526  
Uday Menon 1.00-3.00 0/40
IEOR 3900 024/11527  
Bento Natura 1.00-3.00 1/40
IEOR 3900 025/11528  
Jay Sethuraman 1.00-3.00 0/40
IEOR 3900 026/11529  
Karl Sigman 1.00-3.00 0/40
IEOR 3900 027/11530  
Clifford Stein 1.00-3.00 0/40
IEOR 3900 028/11531  
Wenpin Tang 1.00-3.00 0/40
IEOR 3900 029/11532  
Wenpin Tang 1.00-3.00 0/40
IEOR 3900 030/11533  
Kaizheng Wang 1.00-3.00 0/40
IEOR 3900 032/11536  
David Yao 1.00-3.00 0/40
IEOR 3900 033/11538  
Yi Zhang 1.00-3.00 2/40

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. Only for IEOR undergraduate students who need relevant work experience as part of their program of study.
Final reports are required. This course may not be taken for pass/fail credit or audited

Spring 2025: IEOR E3999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3999 001/14605  
Cindy Borgen, Yi Zhang 1.00-2.00 5/50
Summer 2025: IEOR E3999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3999 001/11563  
Yi Zhang, Cindy Borgen 1.00-2.00 20/200
Fall 2025: IEOR E3999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3999 001/13385  
Yi Zhang, Cindy Borgen 1.00-2.00 0/40

IEOR E4003 CORPORATE FINANCE FOR ENGINEERS. 3.00 points.

Lect: 3.

Prerequisites: Probability theory and linear programming. Required for all undergraduate students majoring in IE, OR:EMS, OR:FE, and OR.
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 2025: IEOR E4003
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4003 001/13386 T Th 2:40pm - 3:55pm
Room TBA
Christopher Perez 3.00 52/100

IEOR E4004 OPTIMIZATION MODELS AND METHODS. 3.00 points.

Lect: 3.

Prerequisites: Refer to course syllabus.
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 2025: IEOR E4004
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4004 001/14606 M W 1:10pm - 2:25pm
301 Uris Hall
Daniel Bienstock 3.00 159/150
IEOR 4004 002/14607 T Th 8:40am - 9:55am
209 Havemeyer Hall
Vineet Goyal 3.00 34/110
IEOR 4004 V02/18100  
Vineet Goyal 3.00 1/99
Fall 2025: IEOR E4004
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4004 001/11799 M W 10:10am - 11:25am
Room TBA
Yuri Faenza 3.00 0/110
IEOR 4004 002/11800 M W 2:40pm - 3:55pm
Room TBA
Yaren Kaya 3.00 0/110
IEOR 4004 003/11801 T Th 4:10pm - 5:25pm
Room TBA
Yaren Kaya 3.00 0/96

IEOR E4007 OPT MODELS & METHODS FOR FE. 3.00 points.

Lect: 3.

Prerequisites: Linear algebra. This graduate course is only for M.S. Program in Financial Engineering students.
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 2025: IEOR E4007
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4007 001/11802 M W 10:10am - 11:25am
Room TBA
Tianyi Lin 3.00 1/140

IEOR E4008 COMPUTATION DISCRETE OPT. 3.00 points.

Prerequisites: Linear programming, basic probability theory.

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 2025: IEOR E4008
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4008 001/14608 M W 10:10am - 11:25am
233 Seeley W. Mudd Building
Yuri Faenza 3.00 14/40

IEOR E4100 STATISTICS & SIMULATION. 1.50 point.

Lecture 1.5

Prerequisites: Understanding of single- and multivariable 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 2025: IEOR E4100
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4100 001/13410  
1.50 0/90

IEOR E4101 PROBABILITY STAT & SIMULATION. 3.00 points.

Prerequisites: Understanding of single- and multivariable calculus. MSE and MSBA students only.
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 2025: IEOR E4101
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4101 001/11803 T Th 2:40pm - 3:55pm
Room TBA
Henry Lam 3.00 0/110
IEOR 4101 002/11804 M W 2:40pm - 3:55pm
Room TBA
Yi Zhang 3.00 0/60
IEOR 4101 003/11805 M W 5:40pm - 6:55pm
Room TBA
Yi Zhang 3.00 0/100

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 2025: IEOR E4102
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4102 001/14609 M W 2:40pm - 3:55pm
614 Schermerhorn Hall
Antonius Dieker 3.00 90/100

IEOR E4106 STOCHASTIC MODELS. 3.00 points.

Lect: 3.

Prerequisites: (STAT GU4001) or IEOR E4150 This graduate course is only for IE and OR students. Also required for students in the Undergraduate Advanced Track.
Corequisites: IEOR E4403

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 2025: IEOR E4106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4106 001/14611 M W 2:40pm - 3:55pm
301 Pupin Laboratories
Karl Sigman 3.00 136/180
IEOR 4106 V01/18102  
Karl Sigman 3.00 7/99
Summer 2025: IEOR E4106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4106 D01/11944  
Karl Sigman 3.00 5/99
Fall 2025: IEOR E4106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4106 001/11806 M W 1:10pm - 2:25pm
Room TBA
David Yao 3.00 5/120

IEOR E4108 SUPPLY CHAIN ANALYTICS. 3.00 points.

Prerequisites: IEOR E3402 or instructor's permission. MS IEOR students only.

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.

IEOR E4111 OPERATIONS CONSULTING. 3.00 points.

Prerequisites: Probability and statistics at the level of IEOR E3658 and E4307 or STAT GU4001, and Deterministic Models at the level of IEOR E3608 or IEOR E4004, or instructor permission. For MS-MS&E students only.

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 2025: IEOR E4111
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4111 001/14612 Th 7:10pm - 9:40pm
501 Northwest Corner
Soulaymane Kachani 3.00 0/0
Fall 2025: IEOR E4111
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4111 001/11807  
Soulaymane Kachani 3.00 0/110

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

Summer 2025: IEOR E4150
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4150 D01/12060  
Antonius Dieker 3.00 4/99
Fall 2025: IEOR E4150
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4150 001/11808 M W 8:40am - 9:55am
Room TBA
Eric Stratman 3.00 0/164
IEOR 4150 002/11890 T Th 2:40pm - 3:55pm
Room TBA
Antonius Dieker 3.00 0/75

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 2025: IEOR E4199
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4199 001/11891  
Michael Miller 0.00 0/250

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 2025: IEOR E4207
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4207 001/11809 M 4:10pm - 6:40pm
Room TBA
Leon Gold 3.00 32/52

IEOR E4208 SEM IN HUMAN FACTORS DESIGN. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E4207) or IEOR E4207; IEOR E4207 or 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

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 2025: IEOR E4212
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4212 001/11810 M W 2:40pm - 3:55pm
Room TBA
Hardeep Johar 3.00 43/45

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 2025: IEOR E4307
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4307 001/11811 M W 1:10pm - 2:25pm
Room TBA
Fabrizio Lecci 3.00 64/90

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

IEOR E4402 Corporate Finance, Accounting & Investment Banking. 3.00 points.

Prerequisites: Covers primary financial theories and alternative theories underlying Corporate Finance, such as CAPM, Miller Modigliani, Fama French factors, Smart Beta, etc.
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 2025: IEOR E4402
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4402 001/14613 W 7:10pm - 9:40pm
833 Seeley W. Mudd Building
Rodney Sunada-Wong 3.00 65/100
Fall 2025: IEOR E4402
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4402 001/11812 W 5:40pm - 7:55pm
Room TBA
Rodney Sunada-Wong 3.00 51/110

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

IEOR E4404 SIMULATION. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E3658) and (IEOR E4307) or (STAT GU4001) and Required for all undergraduate students majoring in IE, OR:EMS, OR:FE, and OR. Also required for MSOR.
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 2025: IEOR E4404
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4404 001/14614 T Th 2:40pm - 3:55pm
501 Northwest Corner
Henry Lam 3.00 129/150
IEOR 4404 V01/18104  
Henry Lam 3.00 1/99
Summer 2025: IEOR E4404
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4404 D01/11945  
Karl Sigman 3.00 3/99
Fall 2025: IEOR E4404
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4404 001/11813 T Th 4:10pm - 5:25pm
Room TBA
Henry Lam 3.00 56/110

IEOR E4405 PRODUCTION SCHEDULING. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E3608) and (IEOR E3658) and IEOR E3608 AND IEOR E3658; 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 2025: IEOR E4405
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4405 001/14615 T Th 8:40am - 9:55am
330 Uris Hall
Clifford Stein 3.00 22/60

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 2025: IEOR E4407
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4407 001/11814 M W 4:10pm - 5:25pm
Room TBA
Jay Sethuraman 3.00 18/75

IEOR E4412 QUALITY CONTROL AND MANAGEMENT. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E3658) 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 E4418 TRANSPORTATION ANALYTICS & LOGISTICS. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E3608 or IEOR E4404 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.

Spring 2025: IEOR E4418
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4418 001/14616 T Th 10:10am - 11:25am
313 Fayerweather
Adam Elmachtoub 3.00 30/75
IEOR 4418 V01/19141  
Adam Elmachtoub 3.00 1/99
Fall 2025: IEOR E4418
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4418 001/14647 T Th 11:40am - 12:55pm
Room TBA
Adam Elmachtoub 3.00 2/75

IEOR E4500 APPLICATIONS PROGRAMMNG FOR FE. 3.00 points.

Lect: 3.

Prerequisites: Computer programming or instructor’s approval. Required for undergraduate students majoring in OR:FE.
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 2025: IEOR E4500
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4500 001/11815 M W 10:10am - 11:25am
Room TBA
Anran Hu 3.00 52/100

IEOR E4501 TOOLS FOR ANALYTICS. 3.00 points.

Corequisites: IEOR E4523

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 2025: IEOR E4501
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4501 001/14617 M 7:10pm - 9:40pm
303 Seeley W. Mudd Building
Lynn Root 3.00 18/75
Fall 2025: IEOR E4501
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4501 001/11816 M 7:10pm - 9:40pm
Room TBA
Lynn Root 3.00 0/100

IEOR E4502 Python for Analytics. 0.00 points.

Zero-credit course. Primer on Python for analytics concepts. Required for MSBA students

IEOR E4505 OPERATION RES IN PUBLIC POLICY. 3.00 points.

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 2025: IEOR E4505
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4505 001/14618 M W 11:40am - 12:55pm
312 Mathematics Building
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 2025: IEOR E4506
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4506 001/11817 M 7:10pm - 9:40pm
Room TBA
Anthony Effik 3.00 55/70

IEOR E4507 HEALTHCARE OPERATIONS MGT. 3.00 points.

Prerequisites: (IEOR E3608) and (IEOR E3658) and (IEOR E4307) For senior undergraduate Engineering students: SIEO W3600: Introduction to Probability and Statistics and IEOR E3608: Introduction to Mathematical Programming; For Engineering graduate students (MS or PhD): Probability and Statistics at the level of SIEO W4150, and Deterministic Models at the level of IEOR E4004. For Healthcare Management students: P8529: Analytic Methods for Health Services Management.

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.

Fall 2025: IEOR E4507
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4507 001/11892 M W 4:10pm - 5:25pm
Room TBA
Yaren Kaya, Eric Stratman 3.00 15/50

IEOR E4510 PROJECT MANAGEMENT. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E4004) or (IEOR E3608) 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 2025: IEOR E4510
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4510 001/14620 F 10:10am - 12:40pm
501 Northwest Corner
David Begun 3.00 64/80

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 2025: IEOR E4511
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4511 001/14621 M 9:00am - 11:30am
301 Uris Hall
Michael Robbins 3.00 60/80
IEOR 4511 V01/20281  
Michael Robbins 3.00 2/99
Fall 2025: IEOR E4511
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4511 001/11818 M 9:00am - 11:30am
Room TBA
Michael Robbins 3.00 8/150

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

Fall 2025: IEOR E4520
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4520 001/12906 W 4:10pm - 6:40pm
Room TBA
Ebad Jahangir 3.00 7/40

IEOR E4521 SYSTEM ENGI TOOLS/METHODS. 3.00 points.

Prerequisites: B.S. in engineering or applied sciences; probability and statistics, optimization, linear algebra, and basic economics.
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

Spring 2025: IEOR E4521
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4521 D01/20243  
Ebad Jahangir 3.00 5/99

IEOR E4523 DATA ANALYTICS. 3.00 points.

Lect: 3.

Prerequisites: IEOR E4522 OR IEOR E4501
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 2025: IEOR E4523
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4523 001/14622 T Th 4:10pm - 5:25pm
833 Seeley W. Mudd Building
Uday Menon 3.00 21/80
IEOR 4523 V01/18106  
Uday Menon 3.00 1/99
Fall 2025: IEOR E4523
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4523 001/11819 T Th 2:40pm - 3:55pm
Room TBA
Uday Menon 3.00 0/85
IEOR 4523 002/11820 T Th 4:10pm - 5:25pm
Room TBA
Uday Menon 3.00 0/85
IEOR 4523 003/11821 T Th 11:40am - 12:55pm
Room TBA
Uday Menon 3.00 0/85

IEOR E4524 ANALYTICS IN PRACTICE. 3.00 points.

Lect: 3.

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 2025: IEOR E4524
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4524 001/14624 Th 7:10pm - 9:40pm
417 International Affairs Bldg
Hardeep Johar 3.00 195/200
IEOR 4524 002/14625 F 1:00pm - 4:00pm
326 Uris Hall
Yaren Kaya 3.00 12/30

IEOR E4525 MACHINE LEARNING FE & OPR. 3.00 points.

Prerequisites: Optimization, applied probability, statistics, and knowledge of or experience in computer programming.
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 2025: IEOR E4525
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4525 001/14626 F 10:10am - 12:40pm
833 Seeley W. Mudd Building
Christian Kroer 3.00 35/100
Fall 2025: IEOR E4525
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4525 001/11822 F 10:10am - 12:40pm
Room TBA
Christian Kroer 3.00 30/120

IEOR E4526 ANALYTICS ON THE CLOUD. 3.00 points.

Prerequisites: IEOR E4501 and IEOR E4523 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 2025: IEOR E4526
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4526 001/11823 M 10:10am - 12:55pm
303 Seeley W. Mudd Building
Hardeep Johar 3.00 38/60

IEOR E4530 TOPICS IN OPERATIONS RESEARCH. 3.00 points.

Prerequisites: A course in probability and statistics 4101/4150 or equivalent, basic python programming.
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

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

Spring 2025: IEOR E4532
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4532 001/14627 F 9:00am - 5:00pm
702 Hamilton Hall
Casandra Campbell 1.50 65/68
Fall 2025: IEOR E4532
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4532 001/11824 F 9:00am - 5:00pm
Room TBA
Michelle Glaser 1.50 70/72

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 2025: IEOR E4533
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4533 001/14628 F Sa S 9:00am - 5:00pm
303 Uris Hall
Nicolas Chikhani 1.50 65/67
Fall 2025: IEOR E4533
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4533 001/11825 F Sa S 9:00am - 5:00pm
Room TBA
Nicolas Chikhani 1.50 61/65

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 2025: IEOR E4534
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4534 001/11826 M W 11:40am - 12:55pm
Room TBA
Fabrizio Lecci 3.00 72/71

IEOR E4540 DATA MINING. 3.00 points.

Prerequisites: Linear Algebra, Calculus, Probability, and some basic programming.
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 2025: IEOR E4540
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4540 001/14629 W 7:10pm - 9:40pm
633 Seeley W. Mudd Building
Krzysztof Choromanski 3.00 69/70
IEOR 4540 V01/18108  
Krzysztof Choromanski 3.00 6/99
Fall 2025: IEOR E4540
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4540 001/11827 W 7:10pm - 9:40pm
Room TBA
Krzysztof Choromanski 3.00 71/73

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

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

Prerequisites: IEOR E4004 AND IEOR E4106 AND IEOR E4150; or instructor's permission.
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

IEOR E4571 TOPICS IN OPERATIONS RESEARCH. 3.00 points.

Prerequisites: IEOR E4004 AND IEOR E4106 AND IEOR E4150; IEOR E4150, IEOR E4004, and IEOR E4106, or instructor's permission.
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

Spring 2025: IEOR E4571
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4571 001/14630 T 1:10pm - 3:40pm
616 Martin Luther King Building
Robert Kramer, Khosrow Dehnad 3.00 35/50
Fall 2025: IEOR E4571
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4571 001/11829 W 1:10pm - 3:40pm
Room TBA
Khosrow Dehnad, Robert Kramer 3.00 13/50

IEOR E4572 TOPICS IN OPERATIONS RESEARCH. 3.00 points.

Lect: 3.,Points: 1.5

Prerequisites: IEOR E4004 AND IEOR E4106 AND IEOR E4150; or instructor's permission.
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 2025: IEOR E4572
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4572 001/14631 T Th 11:40am - 12:55pm
313 Fayerweather
Uday Menon 3.00 10/70
Fall 2025: IEOR E4572
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4572 001/16090 W 7:00pm - 9:30pm
Room TBA
Robert Kramer 3.00 0/50

IEOR E4573 TOPICS IN OR. 3.00 points.

Points: 1.5

Prerequisites: IEOR E4004 AND IEOR E4106 AND IEOR E4150; IEOR E4150, IEOR E4004, and IEOR E4106, or instructor's permission.
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 2025: IEOR E4573
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4573 001/14633 M 7:00pm - 9:30pm
402 Chandler
Andrei Simion, Robert Kramer 3.00 78/100
Fall 2025: IEOR E4573
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4573 001/11893 W 5:40pm - 8:10pm
Room TBA
Mahir Yavuz, Robert Kramer 3.00 60/60

IEOR E4574 TOPICS IN OR. 3.00 points.

Prerequisites: IEOR E4004 AND IEOR E4106 AND IEOR E4150; IEOR E4150, IEOR E4004, and IEOR E4106, or instructor's permission.
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 2025: IEOR E4574
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4574 001/17306 T 6:00pm - 8:30pm
303 Seeley W. Mudd Building
Grace Lin 3.00 22/60
IEOR 4574 V01/20282  
Grace Lin 3.00 2/1
Fall 2025: IEOR E4574
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4574 001/13669 F 2:40pm - 5:10pm
Room TBA
Robert Kramer, Ciro Greco 3.00 45/60

IEOR E4575 TOPICS IN OPERATIONS RESEARCH. 3.00 points.

Note to students: 1.5 credits

Prerequisites: IEOR E4004IEOR E4106IEOR E4150 or instructor's permission. 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.

Spring 2025: IEOR E4575
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4575 001/14634 Th 7:10pm - 9:40pm
Room TBA
Uday Menon, Christine Chan 3.00 194/200
Fall 2025: IEOR E4575
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4575 001/11894  
3.00 0/30

IEOR E4576 TOPICS IN OPERATIONS RESEARCH. 3.00 points.

1.5 pts

Prerequisites: IEOR E4004 AND IEOR E4106 AND IEOR E4150; IEOR E4150, IEOR E4004, and IEOR E4106, or instructor's permission.
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 2025: IEOR E4576
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4576 001/11830 M 7:10pm - 9:40pm
Room TBA
Naftali Cohen 3.00 4/52

IEOR E4577 TOPICS IN OPERATIONS RESEARCH. 1.50 point.

Points: 1.5

Prerequisites: IEOR E4004 AND IEOR E4106 AND IEOR E4150; IEOR E4150, IEOR E4004, and IEOR E4106, or instructor's permission
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 2025: IEOR E4577
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4577 001/11831 M 7:10pm - 9:40pm
Room TBA
Amit Arora 1.50 11/60

IEOR E4578 TOPICS IN OPERATION RESEARCH. 3.00 points.

Prerequisites: IEOR E4004 AND IEOR E4106 AND IEOR E4150; IEOR E4150, IEOR E4004, and IEOR E4106, or instructor's permission.
A project-based course in Forecasting, predicting a time series into the future, to prepare students for real-world applications including articulating the business case, value creation, problem statement, and the iterative development of solutions including building a data pipeline, exploration, modeling, and visualizations. The course will use Statistical methods, Machine Learning, and Deep Learning with Transformer-based methods to predict a time series. It will use nuggets of signal processing to augment Machine Learning models to characterize and filter orders of dynamics in the time series data

Spring 2025: IEOR E4578
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4578 001/14635 Th 7:00pm - 9:30pm
614 Schermerhorn Hall
Syed Haider, Robert Kramer 3.00 63/85
Fall 2025: IEOR E4578
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4578 001/11832 T 6:00pm - 8:30pm
Room TBA
Owen Davis 3.00 8/60

IEOR E4579 TOPICS IN OR. 3.00 points.

Prerequisites: IEOR E4004 AND IEOR E4106 AND IEOR E4150; IEOR E4150, IEOR E4004, and IEOR E4106, or instructor's permission.
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 2025: IEOR E4579
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4579 001/14636 T 6:00pm - 8:30pm
633 Seeley W. Mudd Building
Gary Kazantsev 3.00 49/70

IEOR E4599 MSBA Quantitative Bootcamp. 0.00 points.

Primer on quantitative and mathematical concepts. Required for all incoming MSBA students

IEOR E4601 DYNAMIC PRICING/REVENUE MGMT. 3.00 points.

Lect: 3.

Prerequisites: (STAT GU4001) and (IEOR E4004) IEOR E4004 AND STAT W4001
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

Spring 2025: IEOR E4601
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4601 001/14637 T Th 11:40am - 12:55pm
413 Kent Hall
Vineet Goyal 3.00 19/70

IEOR E4602 QUANTITATIVE RISK MANAGEMENT. 3.00 points.

Lect: 3.

Prerequisites: (STAT GU4001) and (IEOR E4106) IEOR E4106 AND STAT W4001
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 2025: IEOR E4602
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4602 001/11834 M W 11:40am - 12:55pm
Room TBA
Agostino Capponi 3.00 45/58

IEOR E4620 PRICING MODELS FOR FIN ENGIN. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E4700) 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 2025: IEOR E4620
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4620 001/11835 T 7:10pm - 9:40pm
Room TBA
Michael Miller 3.00 36/70

IEOR E4630 ASSET ALLOCATION. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E4700) 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 2025: IEOR E4630
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4630 001/14638 T Th 4:10pm - 5:25pm
501 Schermerhorn Hall
Christopher Perez 3.00 80/110
IEOR 4630 V01/20359  
Christopher Perez 3.00 1/99

IEOR E4650 BUSINESS ANALYTICS. 3.00 points.

Prerequisites: IEOR E4150 AND STAT W4001
This course focuses on how to identify, evaluate, and capture business analytic opportunities that create value. The course covers basic analytic methods alongside case studies on organizations that successfully deployed these techniques. The first part of the course is on using data to develop insights and predictive capabilities with machine learning techniques. The second part focuses on the use of A/B testing, causal inference, ethics, and optimization to support decision-making

Spring 2025: IEOR E4650
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4650 001/14639 M W 10:10am - 11:25am
313 Fayerweather
Adam Elmachtoub 3.00 65/75
Fall 2025: IEOR E4650
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4650 001/11836 W 9:00am - 11:30am
Room TBA
Charles Guetta 3.00 0/250
IEOR 4650 002/11837 T Th 10:10am - 11:25am
Room TBA
Adam Elmachtoub 3.00 25/80

IEOR E4700 INTRO TO FINANCIAL ENGINEERING. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E3106) or (IEOR E4106) IEOR E4106 OR IEOR E3106
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 2025: IEOR E4700
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4700 001/14640 T Th 10:10am - 11:25am
209 Havemeyer Hall
David Yao 3.00 80/100
Fall 2025: IEOR E4700
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4700 001/11838 M W 11:40am - 12:55pm
Room TBA
Xunyu Zhou 3.00 18/100

IEOR E4701 STOCHASTIC MODELS FOR FIN ENG. 3.00 points.

Lect: 3.

Prerequisites: (STAT GU4001) STAT W4001
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 2025: IEOR E4701
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4701 001/11839 M W 1:10pm - 2:25pm
Room TBA
Daniel Lacker 3.00 1/140

IEOR E4703 MONTE CARLO SIMULATION METHODS. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E4701) 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 2025: IEOR E4703
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4703 001/14642 M W 8:40am - 9:55am
428 Pupin Laboratories
Ali Hirsa 3.00 118/125
IEOR 4703 V01/18109  
Ali Hirsa 3.00 1/99

IEOR E4706 FOUNDATIONS FR FINANCIAL ENGIN. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E4701) and (IEOR E4702) and Linear algebra
Corequisites: IEOR E4709

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 2025: IEOR E4706
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4706 001/11840 T Th 11:40am - 12:55pm
Room TBA
Wenpin Tang 3.00 1/140

IEOR E4707 FE CONTINUOUS TIME MODELS. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E4701)
Corequisites: IEOR E4709

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 2025: IEOR E4707
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4707 001/14643 T Th 2:40pm - 3:55pm
428 Pupin Laboratories
Xunyu Zhou 3.00 119/125
IEOR 4707 V01/18111  
Xunyu Zhou 3.00 1/99

IEOR E4709 STATISTICAL ANALYSIS AND TIME SERIES. 3.00 points.

Lect: 3.

Prerequisites: IEOR E4702 Probability
Corequisites: IEOR E4706,IEOR E4707

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 2025: IEOR E4709
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4709 001/14644 M W 10:10am - 11:25am
428 Pupin Laboratories
Agostino Capponi 3.00 121/140
IEOR 4709 V01/18112  
Agostino Capponi 3.00 3/99

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 2025: IEOR E4711
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4711 001/11841 M 6:00pm - 8:30pm
Room TBA
Siddhartha Ghosh Dastidar 3.00 43/70

IEOR E4718 INTRO-IMPLIED VOLATILITY SMILE. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E4706) and IEOR E4706; 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 2025: IEOR E4718
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4718 001/14645 Th 7:10pm - 9:40pm
209 Havemeyer Hall
Amal Moussa 3.00 71/75

IEOR E4720 TOPICS IN QUANT FINANCE. 3.00 points.

Prerequisites: (IEOR E4700) and IEOR E4700; 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

IEOR E4721 TOPICS IN QUANT FINANCE. 1.50 point.

Prerequisites: IEOR E4700; 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 2025: IEOR E4721
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4721 001/18250 W 4:10pm - 6:40pm
501 Schermerhorn Hall
Sridhar Gollamudi 1.50 8/50

IEOR E4722 TOPICS IN QUANT FINANCE. 3.00 points.

Prerequisites: IEOR E4700 Additional prerequisites announced depending on offering.

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.

IEOR E4723 TOPICS IN QUANTATIVE FINANCE. 1.50 point.

Course Points: 1.5

Prerequisites: IEOR E4700; Additional Prerequisites will be announced depending on offering
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 2025: IEOR E4723
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4723 001/11842 T 7:10pm - 9:40pm
Room TBA
Cyril Shmatov 1.50 27/40

IEOR E4724 TOPICS IN QUANTATIVE FINANCE. 3.00 points.

Prerequisites: IEOR E4700; Additional prerequisites will be announced depending on offering
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 2025: IEOR E4724
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4724 001/11843 W 5:40pm - 8:10pm
Room TBA
Luca Capriotti 3.00 18/50

IEOR E4725 Topics in Quantitative Finance: Numerical Solutions of Partial Differential Equation. 3 points.

Lect: 3.

Prerequisites: (IEOR E4706) and (IEOR E4707) IEOR E4700; Additional Prerequisites will be announced depending on offering

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 E4728 TOPICS IN QUANTITATIVE FINANCE. 1.50 point.

Prerequisites: IEOR E4700; Additional prerequisites will be announced depending on offering
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 2025: IEOR E4728
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4728 001/11844 Th 1:10pm - 3:40pm
Room TBA
Khosrow Dehnad 1.50 20/50

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.

Prerequisites: IEOR E4700 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.

IEOR E4731 CREDIT RISK/CREDIT DERIVATIVES. 3.00 points.

Lect: 3.

Prerequisites: (IEOR E4701) and (IEOR E4707) 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

IEOR E4732 COMPUT METHODS IN FINANCE. 3.00 points.

Prerequisites: (IEOR E4700) 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 2025: IEOR E4732
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4732 001/14646 Th 7:10pm - 9:40pm
829 Seeley W. Mudd Building
Alireza Javaheri 3.00 10/40

IEOR E4733 ALGORITHMIC TRADING. 3.00 points.

Prerequisites: IEOR E4700 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 2025: IEOR E4733
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4733 001/14648 T Th 1:10pm - 2:25pm
309 Havemeyer Hall
Christopher Perez 3.00 90/110
IEOR 4733 V01/20360  
Christopher Perez 3.00 3/99

IEOR E4734 FOR EXCH/RELATD DERIVATVS INST. 1.50 point.

1.5.

Prerequisites: (IEOR E4700) 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 2025: IEOR E4734
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4734 001/11845 Th 4:10pm - 6:40pm
Room TBA
David DeRosa 1.50 30/60

IEOR E4735 Structured and Hybrid Products. 3 points.

Lect: 3.

Prerequisites: (IEOR E4700) Refer to course syllabus.

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 2025: IEOR E4735
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4735 001/11846 Th 7:10pm - 9:40pm
Room TBA
Alireza Javaheri 3 32/100

IEOR E4737 AI Applications in Finance. 3.00 points.

Prerequisites: Proficiency in Python & Tensor, good understanding of calculus, knowledge of linear/matrix algebra, and basic knowledge of statistics

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

Spring 2025: IEOR E4737
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4737 001/14649 F 1:00pm - 5:00pm
207 Mathematics Building
Ali Hirsa 3.00 90/85
IEOR 4737 001/14649 Sa 9:00am - 1:00pm
207 Mathematics Building
Ali Hirsa 3.00 90/85
Summer 2025: IEOR E4737
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4737 001/11553 F 1:00pm - 5:00pm
633 Seeley W. Mudd Building
Ali Hirsa 3.00 54/60
IEOR 4737 001/11553 Sa 9:00am - 5:00pm
633 Seeley W. Mudd Building
Ali Hirsa 3.00 54/60
IEOR 4737 V01/11931  
Ali Hirsa 3.00 10/99

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 2025: IEOR E4741
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4741 001/11847 W 7:10pm - 9:40pm
Room TBA
Sebastien Donadio 3.00 9/60

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 2025: IEOR E4742
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4742 001/11848 F 1:00pm - 5:00pm
Room TBA
Ali Hirsa 3.00 61/85
IEOR 4742 001/11848 Sa 9:00am - 6:00pm
Room TBA
Ali Hirsa 3.00 61/85

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 probability and statistics, instruments of the financial markets, and asset pricing models.
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 2025: IEOR E4745
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4745 001/11849 T Th 2:40pm - 3:55pm
Room TBA
Allan Malz 3.00 47/110

IEOR E4798 Financial Engineering Practitioners Seminar Series. 0.00 points.

Prerequisites: First year MSFE Students
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 2025: IEOR E4798
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4798 001/14650 M 7:00pm - 9:00pm
501 Schermerhorn Hall
Ali Hirsa, Winsor Yang, Cindy Borgen 0.00 0/130
Fall 2025: IEOR E4798
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4798 001/11850 M 7:00pm - 9:00pm
Room TBA
Ali Hirsa, Cindy Borgen 0.00 0/140

IEOR E4799 MSFE Quantitative and Computational Bootcamp. 0.00 points.

Primer on quantitative and mathematical concepts. Required of all incoming MSFE students

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 2025: IEOR E4900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4900 001/18544  
Anish Agarwal 1.00-3.00 0/40
IEOR 4900 002/18545  
Shipra Agrawal 1.00-3.00 0/40
IEOR 4900 003/18546  
Eric Balkanski 1.00-3.00 0/40
IEOR 4900 004/18547  
Daniel Bienstock 1.00-3.00 0/40
IEOR 4900 005/18548  
Agostino Capponi 1.00-3.00 0/40
IEOR 4900 006/18549  
Rachel Cummings 1.00-3.00 0/40
IEOR 4900 007/18550  
Antonius Dieker 1.00-3.00 0/40
IEOR 4900 008/18551  
Adam Elmachtoub 1.00-3.00 0/40
IEOR 4900 009/18552  
Yuri Faenza 1.00-3.00 0/40
IEOR 4900 010/18553  
Vineet Goyal 1.00-3.00 1/40
IEOR 4900 011/18554  
Ali Hirsa 1.00-3.00 2/40
IEOR 4900 012/18555  
Anran Hu 1.00-3.00 0/40
IEOR 4900 013/18556  
Garud Iyengar 1.00-3.00 0/40
IEOR 4900 014/18557  
Hardeep Johar 1.00-3.00 1/40
IEOR 4900 015/18558  
Cedric Josz 1.00-3.00 0/40
IEOR 4900 017/18560  
Yaren Kaya 1.00-3.00 0/40
IEOR 4900 018/18561  
Christian Kroer 1.00-3.00 0/40
IEOR 4900 019/18563  
Daniel Lacker 1.00-3.00 0/40
IEOR 4900 020/18564  
Henry Lam 1.00-3.00 0/40
IEOR 4900 021/18565  
Fabrizio Lecci 1.00-3.00 0/40
IEOR 4900 022/18566  
Tianyi Lin 1.00-3.00 0/40
IEOR 4900 023/18567  
Uday Menon 1.00-3.00 0/40
IEOR 4900 024/18568  
Bento Natura 1.00-3.00 0/40
IEOR 4900 025/18569  
Jay Sethuraman 1.00-3.00 0/40
IEOR 4900 026/18570  
Karl Sigman 1.00-3.00 0/40
IEOR 4900 027/18571  
Clifford Stein 1.00-3.00 0/40
IEOR 4900 028/18572  
Wenpin Tang 1.00-3.00 0/40
IEOR 4900 029/18573  
Kaizheng Wang 1.00-3.00 0/40
IEOR 4900 030/18574  
David Yao 1.00-3.00 0/40
IEOR 4900 031/18575  
Yi Zhang 1.00-3.00 0/40
IEOR 4900 032/18576  
Xunyu Zhou 1.00-3.00 0/40
IEOR 4900 033/18577  
Chris Lee 1.00-3.00 0/20
Summer 2025: IEOR E4900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4900 001/11564  
Anish Agarwal 1.00-3.00 0/40
IEOR 4900 002/11565  
Shipra Agrawal 1.00-3.00 0/40
IEOR 4900 003/11566  
Eric Balkanski 1.00-3.00 0/40
IEOR 4900 004/11567  
Daniel Bienstock 1.00-3.00 0/40
IEOR 4900 005/11568  
Agostino Capponi 1.00-3.00 1/40
IEOR 4900 006/11569  
Rachel Cummings 1.00-3.00 0/40
IEOR 4900 007/11570  
Antonius Dieker 1.00-3.00 0/40
IEOR 4900 008/11571  
Adam Elmachtoub 1.00-3.00 0/40
IEOR 4900 009/11572  
Yuri Faenza 1.00-3.00 0/40
IEOR 4900 010/11573  
Vineet Goyal 1.00-3.00 0/40
IEOR 4900 011/11574  
Ali Hirsa 1.00-3.00 2/40
IEOR 4900 012/11575  
Anran Hu 1.00-3.00 0/40
IEOR 4900 013/11576  
Garud Iyengar 1.00-3.00 0/40
IEOR 4900 014/11577  
Hardeep Johar 1.00-3.00 0/40
IEOR 4900 015/11578  
Cedric Josz 1.00-3.00 0/40
IEOR 4900 016/11579  
Soulaymane Kachani 1.00-3.00 0/40
IEOR 4900 017/11580  
Yaren Kaya 1.00-3.00 0/40
IEOR 4900 018/11581  
Christian Kroer 1.00-3.00 0/40
IEOR 4900 019/11582  
Daniel Lacker 1.00-3.00 0/40
IEOR 4900 020/11583  
Henry Lam 1.00-3.00 0/40
IEOR 4900 021/11584  
Fabrizio Lecci 1.00-3.00 0/40
IEOR 4900 022/11585  
Tianyi Lin 1.00-3.00 0/40
IEOR 4900 023/11586  
Uday Menon 1.00-3.00 0/40
IEOR 4900 024/11587  
Bento Natura 1.00-3.00 0/40
IEOR 4900 025/11588  
Jay Sethuraman 1.00-3.00 0/40
IEOR 4900 026/11589  
Karl Sigman 1.00-3.00 0/40
IEOR 4900 027/11590  
Clifford Stein 1.00-3.00 0/40
IEOR 4900 028/11591  
Wenpin Tang 1.00-3.00 0/40
IEOR 4900 029/11592  
Kaizheng Wang 1.00-3.00 1/40
IEOR 4900 030/11593  
Lily Xu 1.00-3.00 0/40
IEOR 4900 031/11594  
David Yao 1.00-3.00 0/40
IEOR 4900 032/11595  
Yi Zhang 1.00-3.00 0/40
IEOR 4900 033/11596  
Xunyu Zhou 1.00-3.00 0/40
IEOR 4900 034/11597  
Chris Lee 1.00-3.00 0/40
IEOR 4900 035/12989  
Charles Guetta 1.00-3.00 1/1
Fall 2025: IEOR E4900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4900 001/11540  
Anish Agarwal 1.00-3.00 0/40
IEOR 4900 002/11541  
Shipra Agrawal 1.00-3.00 0/40
IEOR 4900 003/11542  
Eric Balkanski 1.00-3.00 0/40
IEOR 4900 004/11543  
Daniel Bienstock 1.00-3.00 0/40
IEOR 4900 005/11544  
Agostino Capponi 1.00-3.00 0/40
IEOR 4900 006/11545  
Rachel Cummings 1.00-3.00 0/40
IEOR 4900 007/11546  
Antonius Dieker 1.00-3.00 0/40
IEOR 4900 008/11547  
Adam Elmachtoub 1.00-3.00 0/40
IEOR 4900 009/11548  
Yuri Faenza 1.00-3.00 0/40
IEOR 4900 010/11549  
Vineet Goyal 1.00-3.00 0/40
IEOR 4900 011/11550  
Ali Hirsa 1.00-3.00 0/40
IEOR 4900 012/11551  
Anran Hu 1.00-3.00 0/40
IEOR 4900 013/11552  
Garud Iyengar 1.00-3.00 0/40
IEOR 4900 014/11553  
Hardeep Johar 1.00-3.00 0/40
IEOR 4900 015/11554  
Cedric Josz 1.00-3.00 0/40
IEOR 4900 016/11555  
Soulaymane Kachani 1.00-3.00 0/40
IEOR 4900 017/11556  
Yaren Kaya 1.00-3.00 0/40
IEOR 4900 018/11557  
Christian Kroer 1.00-3.00 0/40
IEOR 4900 019/11558  
Daniel Lacker 1.00-3.00 0/40
IEOR 4900 020/11559  
Henry Lam 1.00-3.00 0/40
IEOR 4900 021/11560  
Fabrizio Lecci 1.00-3.00 0/40
IEOR 4900 022/11561  
Tianyi Lin 1.00-3.00 0/40
IEOR 4900 023/11562  
Uday Menon 1.00-3.00 0/40
IEOR 4900 024/11563  
Bento Natura 1.00-3.00 0/40
IEOR 4900 025/11564  
Jay Sethuraman 1.00-3.00 0/40
IEOR 4900 026/11565  
Karl Sigman 1.00-3.00 0/40
IEOR 4900 027/11566  
Clifford Stein 1.00-3.00 0/40
IEOR 4900 028/11567  
Wenpin Tang 1.00-3.00 0/40
IEOR 4900 029/11568  
Wenpin Tang 1.00-3.00 0/40
IEOR 4900 030/11569  
Kaizheng Wang 1.00-3.00 0/40
IEOR 4900 031/11570  
Lily Xu 1.00-3.00 0/40
IEOR 4900 032/11571  
David Yao 1.00-3.00 0/40
IEOR 4900 033/11572  
Yi Zhang 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 2025: IEOR E4998
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4998 001/14651 Th 11:40am - 2:10pm
Cin Alfred Lerner Hall
Gerard Neumann 3.00 74/85

IEOR E4999 FIELDWORK. 1.00-1.50 points.

Prerequisites: Obtained internship and approval from faculty adviser.
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 2025: IEOR E4999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4999 001/14652  
Ali Hirsa, Chris Lee 1.00-1.50 2/150
IEOR 4999 002/14653  
Hardeep Johar, Chris Lee 1.00-1.50 4/150
IEOR 4999 003/14655  
Chris Lee, Fabrizio Lecci 1.00-1.50 1/150
Summer 2025: IEOR E4999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4999 001/11554  
Jiaqi Li, Ali Hirsa 1.00-1.50 49/600
IEOR 4999 002/11555  
Jiaqi Li, Hardeep Johar 1.00-1.50 92/600
IEOR 4999 003/11556  
Fabrizio Lecci, Jiaqi Li 1.00-1.50 29/600
Fall 2025: IEOR E4999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4999 001/11534  
Ali Hirsa, Jiaqi Li, Chris Lee 1.00-1.50 0/300
IEOR 4999 002/11537  
Hardeep Johar, Jiaqi Li, Chris Lee 1.00-1.50 5/300
IEOR 4999 003/11539  
Jiaqi Li, Chris Lee, Fabrizio Lecci 1.00-1.50 0/300

IEOR E6608 INTEGER PROGRAMMING. 3.00 points.

N/A

IEOR E6613 Optimization, I. 4.5 points.

Prerequisites: Linear algebra

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 2025: IEOR E6613
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 6613 001/11851 T Th 10:10am - 11:25am
Room TBA
Vineet Goyal 4.5 0/40

IEOR E6614 OPTIMIZATION II. 4.50 points.

Lect: 3.

Prerequisites: Linear algebra
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 2025: IEOR E6614
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 6614 001/14656 M W 10:10am - 11:25am
825 Seeley W. Mudd Building
Shipra Agrawal 4.50 18/40

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 2025: IEOR E6617
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 6617 001/11852 M 7:10pm - 9:40pm
Room TBA
Krzysztof Choromanski 3.00 0/55

IEOR E6711 STOCHASTIC MODELING I. 4.50 points.

Prerequisites: (STAT GU4001) or STAT W4001; STAT GU4001 or equivalent.
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 2025: IEOR E6711
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 6711 001/11853 T Th 11:40am - 12:55pm
Room TBA
Karl Sigman 4.50 0/40

IEOR E6712 STOCHASTIC MODELING II. 4.50 points.

Prerequisites: (IEOR E6711) or IEOR E6711; IEOR E6711 or equivalent.
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

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 2025: IEOR E8100
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 8100 001/14658 M W 10:10am - 11:25am
303 Seeley W. Mudd Building
Rachel Cummings 3.00 11/20
IEOR 8100 002/14659 M W 11:40am - 12:55pm
602 Northwest Corner
Yuri Faenza 3.00 10/20
IEOR 8100 003/14660 T 10:10am - 12:40pm
516 Hamilton Hall
Anran Hu 3.00 13/20
IEOR 8100 004/14661 T Th 10:10am - 11:25am
644 Seeley W. Mudd Building
Jay Sethuraman, Tianyi Lin 3.00 6/20
IEOR 8100 005/14662 M W 1:10pm - 2:25pm
825 Seeley W. Mudd Building
Bento Natura 3.00 1/20
IEOR 8100 006/14663 M W 2:40pm - 3:55pm
212a Lewisohn Hall
Wenpin Tang 3.00 12/20
IEOR 8100 007/14664 M W 4:10pm - 5:25pm
142 Uris Hall
Antonius Dieker 3.00 12/20
Fall 2025: IEOR E8100
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 8100 001/11854 M 2:40pm - 5:10pm
Room TBA
Xunyu Zhou 3.00 0/30
IEOR 8100 002/11855 M W 1:10pm - 2:25pm
Room TBA
Agostino Capponi 3.00 0/30
IEOR 8100 003/11858 T Th 11:40am - 12:55pm
Room TBA
Eric Balkanski 3.00 1/30
IEOR 8100 004/11856 M W 10:10am - 11:25am
Room TBA
Christian Kroer 3.00 0/30
IEOR 8100 005/11857 T 2:40pm - 5:10pm
Room TBA
Rachel Cummings 3.00 2/30
IEOR 8100 006/14954 W 2:40pm - 5:10pm
Room TBA
David Yao 3.00 0/20

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

Spring 2025: IEOR E9101
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 9101 001/20328  
Anish Agarwal 1.00-6.00 1/20
IEOR 9101 002/20329  
Shipra Agrawal 1.00-6.00 0/20
IEOR 9101 003/20330  
Eric Balkanski 1.00-6.00 0/20
IEOR 9101 004/20331  
Daniel Bienstock 1.00-6.00 0/20
IEOR 9101 005/20332  
Agostino Capponi 1.00-6.00 3/20
IEOR 9101 006/20333  
Rachel Cummings 1.00-6.00 0/20
IEOR 9101 007/20334  
Antonius Dieker 1.00-6.00 0/20
IEOR 9101 008/20335  
Adam Elmachtoub 1.00-6.00 1/20
IEOR 9101 009/20336  
Yuri Faenza 1.00-6.00 0/20
IEOR 9101 010/20337  
Vineet Goyal 1.00-6.00 0/20
IEOR 9101 011/20338  
Ali Hirsa 1.00-6.00 0/20
IEOR 9101 012/20339  
Anran Hu 1.00-6.00 0/20
IEOR 9101 013/20340  
Garud Iyengar 1.00-6.00 0/20
IEOR 9101 014/20341  
Hardeep Johar 1.00-6.00 0/20
IEOR 9101 015/20342  
Cedric Josz 1.00-6.00 0/20
IEOR 9101 016/20343  
Soulaymane Kachani 1.00-6.00 0/20
IEOR 9101 017/20344  
Yaren Kaya 1.00-6.00 0/20
IEOR 9101 018/20345  
Christian Kroer 1.00-6.00 2/20
IEOR 9101 019/20346  
Daniel Lacker 1.00-6.00 0/20
IEOR 9101 020/20347  
Henry Lam 1.00-6.00 2/20
IEOR 9101 021/20348  
Fabrizio Lecci 1.00-6.00 0/20
IEOR 9101 022/20349  
Tianyi Lin 1.00-6.00 2/20
IEOR 9101 023/20350  
Uday Menon 1.00-6.00 0/20
IEOR 9101 024/20351  
Bento Natura 1.00-6.00 0/20
IEOR 9101 025/20352  
Jay Sethuraman 1.00-6.00 0/20
IEOR 9101 026/20353  
Karl Sigman 1.00-6.00 0/20
IEOR 9101 027/20354  
Clifford Stein 1.00-6.00 0/20
IEOR 9101 028/20355  
Wenpin Tang 1.00-6.00 0/20
IEOR 9101 029/20356  
Kaizheng Wang 1.00-6.00 1/20
IEOR 9101 030/19097  
David Yao 1.00-6.00 0/20
IEOR 9101 031/19096  
Yi Zhang 1.00-6.00 1/20
IEOR 9101 032/20357  
Xunyu Zhou 1.00-6.00 0/20
IEOR 9101 033/20358  
Winsor Yang 1.00-6.00 0/20
IEOR 9101 034/20642  
Lily Xu 1.00-6.00 0/20
Summer 2025: IEOR E9101
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 9101 001/11598  
Anish Agarwal 1.00-6.00 0/20
IEOR 9101 002/11599  
Shipra Agrawal 1.00-6.00 0/20
IEOR 9101 003/11600  
Eric Balkanski 1.00-6.00 0/20
IEOR 9101 004/11601  
Daniel Bienstock 1.00-6.00 0/20
IEOR 9101 005/11602  
Agostino Capponi 1.00-6.00 0/20
IEOR 9101 006/11603  
Rachel Cummings 1.00-6.00 0/20
IEOR 9101 007/11604  
Antonius Dieker 1.00-6.00 0/20
IEOR 9101 008/11605  
Adam Elmachtoub 1.00-6.00 0/20
IEOR 9101 009/11606  
Yuri Faenza 1.00-6.00 0/20
IEOR 9101 010/11607  
Vineet Goyal 1.00-6.00 0/20
IEOR 9101 011/11608  
Ali Hirsa 1.00-6.00 0/20
IEOR 9101 012/11609  
Anran Hu 1.00-6.00 0/20
IEOR 9101 013/11610  
Garud Iyengar 1.00-6.00 0/20
IEOR 9101 014/11611  
Hardeep Johar 1.00-6.00 0/20
IEOR 9101 015/11612  
Cedric Josz 1.00-6.00 0/20
IEOR 9101 016/11613  
Soulaymane Kachani 1.00-6.00 0/20
IEOR 9101 017/11614  
Yaren Kaya 1.00-6.00 0/20
IEOR 9101 018/11615  
Christian Kroer 1.00-6.00 0/20
IEOR 9101 019/11616  
Daniel Lacker 1.00-6.00 0/20
IEOR 9101 020/11617  
Henry Lam 1.00-6.00 0/20
IEOR 9101 021/11618  
Fabrizio Lecci 1.00-6.00 0/20
IEOR 9101 022/11619  
Tianyi Lin 1.00-6.00 0/20
IEOR 9101 023/11620  
Uday Menon 1.00-6.00 0/20
IEOR 9101 024/11621  
Bento Natura 1.00-6.00 0/20
IEOR 9101 025/11622  
Jay Sethuraman 1.00-6.00 0/20
IEOR 9101 026/11623  
Karl Sigman 1.00-6.00 0/20
IEOR 9101 027/11624  
Clifford Stein 1.00-6.00 0/20
IEOR 9101 028/11625  
Wenpin Tang 1.00-6.00 0/20
IEOR 9101 029/11626  
Kaizheng Wang 1.00-6.00 0/20
IEOR 9101 030/11627  
Lily Xu 1.00-6.00 0/20
IEOR 9101 031/11628  
David Yao 1.00-6.00 0/20
IEOR 9101 032/11629  
Yi Zhang 1.00-6.00 0/20
IEOR 9101 033/11630  
Xunyu Zhou 1.00-6.00 0/20
IEOR 9101 034/11631  
Winsor Yang 1.00-6.00 0/20
Fall 2025: IEOR E9101
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 9101 001/10007  
Anish Agarwal 1.00-6.00 0/20
IEOR 9101 002/10008  
Shipra Agrawal 1.00-6.00 0/20
IEOR 9101 003/10009  
Eric Balkanski 1.00-6.00 0/20
IEOR 9101 004/10010  
Daniel Bienstock 1.00-6.00 0/20
IEOR 9101 005/10011  
Agostino Capponi 1.00-6.00 0/20
IEOR 9101 006/10012  
Rachel Cummings 1.00-6.00 0/20
IEOR 9101 007/10013  
Antonius Dieker 1.00-6.00 0/20
IEOR 9101 008/10014  
Adam Elmachtoub 1.00-6.00 0/20
IEOR 9101 009/10015  
Yuri Faenza 1.00-6.00 0/20
IEOR 9101 010/10016  
Vineet Goyal 1.00-6.00 0/20
IEOR 9101 011/10017  
Ali Hirsa 1.00-6.00 0/20
IEOR 9101 012/10018  
Anran Hu 1.00-6.00 0/20
IEOR 9101 013/10019  
Garud Iyengar 1.00-6.00 0/20
IEOR 9101 014/10020  
Hardeep Johar 1.00-6.00 0/20
IEOR 9101 015/10021  
Cedric Josz 1.00-6.00 0/20
IEOR 9101 016/10022  
Soulaymane Kachani 1.00-6.00 0/20
IEOR 9101 017/10023  
Yaren Kaya 1.00-6.00 0/20
IEOR 9101 018/10024  
Christian Kroer 1.00-6.00 1/20
IEOR 9101 019/10025  
Daniel Lacker 1.00-6.00 0/20
IEOR 9101 020/10026  
Henry Lam 1.00-6.00 0/20
IEOR 9101 021/10027  
Fabrizio Lecci 1.00-6.00 0/20
IEOR 9101 022/10028  
Tianyi Lin 1.00-6.00 0/20
IEOR 9101 023/10029  
Uday Menon 1.00-6.00 0/20
IEOR 9101 024/10030  
Bento Natura 1.00-6.00 0/20
IEOR 9101 025/10031  
Jay Sethuraman 1.00-6.00 0/20
IEOR 9101 026/10032  
Karl Sigman 1.00-6.00 0/20
IEOR 9101 027/10033  
Clifford Stein 1.00-6.00 0/20
IEOR 9101 028/10034  
Wenpin Tang 1.00-6.00 0/20
IEOR 9101 029/10035  
Wenpin Tang 1.00-6.00 0/20
IEOR 9101 030/10036  
Kaizheng Wang 1.00-6.00 0/20
IEOR 9101 031/10037  
Lily Xu 1.00-6.00 0/20
IEOR 9101 032/10038  
David Yao 1.00-6.00 0/20
IEOR 9101 033/10039  
Yi Zhang 1.00-6.00 0/20
IEOR 9101 034/10040  
Xunyu Zhou 1.00-6.00 0/20
IEOR 9101 035/12550  
Winsor Yang 1.00-6.00 0/20

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

Spring 2025: MEIE E4810
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MEIE 4810 001/13874 F 1:10pm - 3:40pm
306 Uris Hall
Michael Massimino 3.00 18/23

MRKT B8623 Intro To Product Management. 1.50 point.

ORCA E2500 FOUNDATIONS OF DATA SCIENCE. 3.00 points.

Prerequisites: MATH UN1101 and MATH UN1102 MATH V1101 AND MATH V1102; 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 2025: ORCA E2500
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ORCA 2500 001/14665 T Th 2:40pm - 3:55pm
203 Mathematics Building
Uday Menon 3.00 66/80
Fall 2025: ORCA E2500
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ORCA 2500 001/11859 F 10:10am - 12:40pm
Room TBA
Daniel Fernandez 3.00 97/90

ORCA E4500 FOUNDATIONS OF DATA SCIENCE. 3.00 points.

Prerequisites: MATH V1101 AND MATH V1102; 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 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 2025: ORCS E4200
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ORCS 4200 001/12280 T Th 4:10pm - 5:25pm
Room TBA
Lily Xu 3.00 15/50

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

Spring 2025: ORCS E4201
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ORCS 4201 001/14666 M W 8:40am - 9:55am
303 Seeley W. Mudd Building
Rachel Cummings 3.00 34/40

ORCS E4529 Reinforcement Learning. 3.00 points.

Prerequisites: Probability and statistics, basic optimization e.g., familiarity with linear and convex optimization, gradient descent, basic algorithm design constructs, familiarity with programming in python.
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 2025: ORCS E4529
Course Number Section/Call Number Times/Location Instructor Points Enrollment
ORCS 4529 001/11860 M W 1:10pm - 2:25pm
Room TBA
Shipra Agrawal 3.00 54/60