IEOR E Fieldwork. 0 points.

IEOR E2261 Introduction to Accounting and Finance. 3 points.

Lect: 3.

Prerequisites: (ECON UN1105)

For undergraduates only. This course is required for all undergraduate students majoring in IE, OR:EMS, OR:FE and OR. This course examines the fundamental concepts of financial accounting and finance, from the perspective of both managers and investors. Key topics covered in this course include principles of accrual accounting; recognizing and recording accounting transactions; preparation and analysis of financial statements, including balance sheets, income statements, cash flow statements, and statements of owners' equity; 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 2018: IEOR E2261
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 2261 001/65260 F 10:10am - 12:40pm
304 Barnard Hall
Anthony Webster 3 105/120
Spring 2019: IEOR E2261
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 2261 001/27550 F 10:10am - 12:40pm
Room TBA
Anthony Webster 3 95/100

IEOR E3106 Stochastic Systems and Applications. 3 points.

Lect: 3.

Prerequisites: (IEOR E3658) and (IEOR E4307)

For undergraduates only. This course is required for all undergraduate students majoring in IE, OR:EMS, OR:FE and OR.  This class must be taken during (or before) the fifth semester. 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: queuing, 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 advisors.

Fall 2018: IEOR E3106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3106 001/71977 T Th 10:10am - 11:25am
209 Havemeyer Hall
Dylan Possamai 3 91/100
IEOR 3106 R01/65088 F 1:00pm - 2:00pm
Room TBA
3 0/0

IEOR E3402 Production and Inventory Planning. 4 points.

Lect: 3. Recit: 1.

Prerequisites: (IEOR E3608) and (IEOR E3658) and (IEOR E4307)

For undergraduates only. This course is required for all undergraduate students majoring in IE, OR:EMS, OR:FE and OR. This class must be taken during (or before) the sixth semester. This course equips students with knowledge of fundamental issues in production and inventory planning and control in manufacturing firms while developing students' modeling and analytical skills. The course is targeted toward engineering students planning careers in technical consulting, business analysis in operations, logistics, supply-chain and revenue-management functions, positions in general management and future entrepreneurs. The course will cover inventory management and production planning; material requirements planning; aggregate planning of production, inventory, and work force; multi-echelon integrated production-inventory systems; and production scheduling. Students will have an opportunity to participate in a computer-simulation game where, as operations managers for a company, they work in teams to manage capacity, inventories, scheduling, and purchasing of parts. The recitation section is required.

Spring 2019: IEOR E3402
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3402 001/25649 T Th 10:10am - 11:25am
Room TBA
Van Anh Truong 4 84/100
IEOR 3402 R01/24265  
4 0/0

IEOR E3404 Simulation Modeling and Analysis.

Not offered during 2018-19 academic year.

Prerequisites: (IEOR E3658) and (IEOR E4307) and 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 2019: IEOR E3404
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3404 001/27733 T Th 2:40pm - 3:55pm
Room TBA
Yi Zhang 83/100

IEOR E3608 Foundations of optimization. 4 points.

Lect: 3. Recit: 1.

Prerequisites: (MATH UN2010)
Corequisites: COMS W3134,COMS W3137

For undergraduates only. This course is required for all undergraduate students majoring in IE, OR:EMS, OR:FE and OR. This class must be taken during (or before) the fifth semester. Introduction to mathematical programming models and computational techniques. Linear programming and the simplex method, dynamic programming, implicit enumeration for integer programs; production planning applications. IEOR E3608 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 advisors. Recitation section required.

Fall 2018: IEOR E3608
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3608 001/63734 T Th 4:10pm - 5:25pm
451 Computer Science Bldg
Jay Sethuraman 4 95/100
IEOR 3608 R01/16777 F 12:00pm - 1:00pm
Room TBA
4 0/0

IEOR E3609 Advanced optimization. 3 points.

Lect: 3.

For undergraduates only. This course is required for all undergraduate students majoring in IE, OR:EMS, OR:FE and OR. 

IEOR E3658 Probability for engineers. 3 points.

Lect: 3.

Prerequisites: Solid knowledge of calculus, including multiple variable integration.

For undergraduates only. Required for the OR:FE concentration. Must be taken during (or before) the third semester. Students who take IEOR E3658 may not take W4150 due to significant overlap. Recommended: strong mathematical skills. Introductory course to probability theory, and does not assume any prior knowledge of the subject. Teaches foundations required to use probability in applications, but the 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.

Fall 2018: IEOR E3658
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3658 001/70871 T Th 11:40am - 12:55pm
405 Milbank Hall
Daniel Lacker 3 94/150
IEOR 3658 R01/76769 F 3:00pm - 4:00pm
Room TBA
3 0/0

IEOR E3900 Undergraduate Research or Project. 1-3 points.

Prerequisites: approval by a faculty member who agrees to supervise the work.

Independent work involving experiments, computer programming, analytical investigation, or engineering design.

Summer 2018: IEOR E3900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3900 001/62191  
Shipra Agrawal 1-3 0/20
IEOR 3900 002/73497  
Daniel Bienstock 1-3 0/20
IEOR 3900 003/77696  
Agostino Capponi 1-3 0/20
IEOR 3900 004/86846  
Emanuel Derman 1-3 0/20
IEOR 3900 005/90896  
Antonius Dieker 1-3 0/20
IEOR 3900 006/86529  
Adam Elmachtoub 1-3 0/20
IEOR 3900 007/12796  
Yuri Faenza 1-3 0/20
IEOR 3900 008/27197  
Donald Goldfarb 1-3 0/20
IEOR 3900 009/18546  
Vineet Goyal 1-3 0/20
IEOR 3900 010/61780  
Ali Hirsa 1-3 0/20
IEOR 3900 011/83441  
Garud Iyengar 1-3 0/20
IEOR 3900 012/24779  
Hardeep Johar 1-3 0/20
IEOR 3900 013/81756  
Soulaymane Kachani 1-3 0/20
IEOR 3900 014/61246  
Daniel Lacker 1-3 0/20
IEOR 3900 015/68546  
Henry Lam 1-3 0/20
IEOR 3900 016/76396  
Dylan Possamai 1-3 0/20
IEOR 3900 017/81447  
Jay Sethuraman 1-3 0/20
IEOR 3900 018/87096  
Karl Sigman 1-3 0/20
IEOR 3900 019/91246  
Clifford Stein 1-3 0/20
IEOR 3900 020/93596  
Van Anh Truong 1-3 0/20
IEOR 3900 021/98146  
Ward Whitt 1-3 0/20
IEOR 3900 022/81279  
David Yao 1-3 0/20
IEOR 3900 023/12192  
Xunyu Zhou 1-3 0/20
IEOR 3900 024/13346  
Jenny Mak 1-3 0/20
Fall 2018: IEOR E3900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3900 001/26901  
Shipra Agrawal 1-3 0/20
IEOR 3900 002/75427  
Daniel Bienstock 1-3 0/20
IEOR 3900 003/76526  
Agostino Capponi 1-3 1/20
IEOR 3900 004/60319  
Emanuel Derman 1-3 0/20
IEOR 3900 005/73905  
Antonius Dieker 1-3 0/20
IEOR 3900 006/70113  
Adam Elmachtoub 1-3 0/20
IEOR 3900 007/76604  
Yuri Faenza 1-3 0/20
IEOR 3900 008/14282  
Donald Goldfarb 1-3 0/20
IEOR 3900 009/13324  
Vineet Goyal 1-3 0/20
IEOR 3900 010/71162  
Ali Hirsa 1-3 0/20
IEOR 3900 011/16986  
Garud Iyengar 1-3 0/20
IEOR 3900 012/69666  
Hardeep Johar 1-3 0/20
IEOR 3900 013/27161  
Soulaymane Kachani 1-3 2/20
IEOR 3900 014/65494  
Daniel Lacker 1-3 0/20
IEOR 3900 015/10344  
Henry Lam 1-3 1/20
IEOR 3900 016/65774  
Dylan Possamai 1-3 0/20
IEOR 3900 017/63361  
Jay Sethuraman 1-3 0/20
IEOR 3900 018/64515  
Karl Sigman 1-3 0/20
IEOR 3900 019/13737  
Clifford Stein 1-3 0/20
IEOR 3900 020/12818  
Van Anh Truong 1-3 1/20
IEOR 3900 021/21987  
Ward Whitt 1-3 0/20
IEOR 3900 022/13552  
David Yao 1-3 0/20
IEOR 3900 023/63838  
Xunyu Zhou 1-3 0/20
IEOR 3900 024/76180  
Jenny Mak 1-3 0/20
Spring 2019: IEOR E3900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3900 001/26372  
Shipra Agrawal 1-3 0/10
IEOR 3900 002/74833  
Daniel Bienstock 1-3 0/10
IEOR 3900 003/17036  
Agostino Capponi 1-3 0/10
IEOR 3900 004/61031  
Emanuel Derman 1-3 0/10
IEOR 3900 005/13203  
Antonius Dieker 1-3 0/10
IEOR 3900 006/19098  
Adam Elmachtoub 1-3 0/10
IEOR 3900 007/21286  
Yuri Faenza 1-3 0/10
IEOR 3900 008/67785  
Donald Goldfarb 1-3 0/10
IEOR 3900 009/20248  
Vineet Goyal 1-3 0/10
IEOR 3900 010/65579  
Ali Hirsa 1-3 0/10
IEOR 3900 011/13682  
Garud Iyengar 1-3 0/10
IEOR 3900 012/61486  
Hardeep Johar 1-3 0/10
IEOR 3900 013/22935  
Soulaymane Kachani 1-3 0/10
IEOR 3900 014/24624  
Daniel Lacker 1-3 0/10
IEOR 3900 015/26283  
Henry Lam 1-3 0/10
IEOR 3900 016/28461  
Dylan Possamai 1-3 0/10
IEOR 3900 017/64858  
Jay Sethuraman 1-3 0/10
IEOR 3900 018/14274  
Karl Sigman 1-3 0/10
IEOR 3900 019/76136  
Clifford Stein 1-3 0/10
IEOR 3900 020/60841  
Van Anh Truong 1-3 0/10
IEOR 3900 021/18116  
Ward Whitt 1-3 0/10
IEOR 3900 022/61574  
David Yao 1-3 0/10
IEOR 3900 023/75750  
Yi Zhang 1-3 0/10
IEOR 3900 024/24727  
Xunyu Zhou 1-3 0/10
IEOR 3900 025/23500  
Jenny Mak 1-3 0/10

IEOR E3999 FIELDWORK. 1 point.

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.

Summer 2018: IEOR E3999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3999 001/94255  
Karl Sigman, Kristen Maynor 1 17
Fall 2018: IEOR E3999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 3999 001/71942  
Karl Sigman, Kristen Maynor 1 0/30

IEOR E4000 Operations Management. 0 points.

Lect: 3.

Prerequisites: Probability theory and linear programming.

The Professional Development and Leadership course aims to enhance and expand Columbia Engineering graduate students’ interpersonal, professional and leadership skills, through six modules, including: (1) professional portfolio; (2) communication skills; (3) business etiquette and networking; (4) leadership, followership and teamwork; (5) life management; and (6) ethics and integrity. Students in the course will build upon and enhance their interpersonal and intrapersonal skills to further distinguishing themselves in the classroom and in their careers. This course is offered at the Pass/D/Fail grading option.

IEOR E4003 Corporate finance for engineers. 3 points.

Lect: 3.

This course is 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 2018: IEOR E4003
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4003 001/11766 Th 7:10pm - 9:40pm
614 Schermerhorn Hall
Maya Waisman 3 92/120

IEOR E4004 Optimization models and methods. 3 points.

Lect: 3.

This is 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. 

Summer 2018: IEOR E4004
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4004 D01/27948  
Nourhan Sakr, Shipra Agrawal 3 2
Fall 2018: IEOR E4004
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4004 001/74758 M W 11:40am - 12:55pm
310 Fayerweather
Shipra Agrawal 3 84/95
IEOR 4004 002/22379 T Th 4:10pm - 5:25pm
312 Mathematics Building
Yuri Faenza 3 108/115
IEOR 4004 003/29908 M W 4:10pm - 5:25pm
301 Pupin Laboratories
Donald Goldfarb 3 93/150
IEOR 4004 004/92074 M W 10:10am - 11:25am
614 Schermerhorn Hall
Donald Goldfarb 3 120/120
IEOR 4004 D01/11747  
Shipra Agrawal 3 11/95
IEOR 4004 R01/75437 F 2:00pm - 3:00pm
Room TBA
3 0/0
IEOR 4004 R02/71879 F 2:00pm - 3:00pm
Room TBA
3 0/150
IEOR 4004 R03/65456 F 2:00pm - 3:00pm
501 Northwest Corner
3 0/150
Spring 2019: IEOR E4004
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4004 001/64595 T Th 5:40pm - 6:55pm
303 Seeley W. Mudd Building
Raghav Singal 3 0/40
IEOR 4004 R01/20351  
3 0/0

IEOR E4007 Optimization Models and Methods for Financial Engineering. 3 points.

Lect: 3.

Prerequisites: Linear algebra.

This graduate course is only for MS Program in FE 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 2018: IEOR E4007
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4007 001/70217 M W 8:40am - 9:55am
833 Seeley W. Mudd Building
Garud Iyengar 3 119/120
IEOR 4007 R01/29826 F 10:00am - 11:00am
Room TBA
3 0/0
IEOR 4007 V01/67300 M W 8:40am - 9:55am
833 Seeley W. Mudd Building
Garud Iyengar 3 2/85

IEOR E4008 Computation Discrete Opt. 3 points.

Not offered during 2018-19 academic year.

Discrete optimization is a powerful tool for modelling a wide range of problems in science, engineering, and many other areas of technological everyday life. It deals with problems where the decisions to be made are discrete, for instance: which cities should be connected with a road, how many airplanes should we build, or to whom should a highly-requested job be given.

IEOR E4009 Non-linear optimization. 3 points.

Lect.: 2.5.Not offered during 2018-19 academic year.

Prerequisites: A course on optimization models and methods (at the level of IEOR 4004) and a course on linear algebra.

Covers unconstrained and constrained nonlinear optimization involving continuous functions. Additionally, fundamental concepts such as optimality conditions and convergence, principal focus on practical optimization methods. 

IEOR E4100 Statistics and Simulation. 1 point.

Lecture 1.5

Prerequisites: Understanding of single- and multi-variable calculus.

Probability simulation. Statistics, build on knowledge in probability and simulation. Point and interval estimation, hypothesis testing, regression. This course is 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 2018: IEOR E4100
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4100 001/68962 T Th 5:40pm - 6:55pm
717 Hamilton Hall
Henry Lam 1 10/30
IEOR 4100 002/23333 M W 1:10pm - 2:25pm
833 Seeley W. Mudd Building
Benjamin Cousins 1 13/20

IEOR E4101 Probability, Statistics and Simulation. 3 points.

Prerequisites: Understanding of singe and multi-variable 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 treatment and finance. This course is a specialized version of IEOR E4575 for MSE and MSBA students. 

Fall 2018: IEOR E4101
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4101 001/65356 T Th 5:40pm - 6:55pm
717 Hamilton Hall
Henry Lam 3 73/90
IEOR 4101 002/26446 M W 1:10pm - 2:25pm
833 Seeley W. Mudd Building
Benjamin Cousins 3 94/110
IEOR 4101 R01/18833 F 9:00am - 10:00am
Room TBA
3 0/0

IEOR E4102 Stochastic Models for Management Science and Engineering. 3 points.

Prerequisites: IEOR E4101

Introduction to stochastic processes and model, 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. This course is a specialized version of IEOR E4106 for MSE students. 

Spring 2019: IEOR E4102
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4102 001/61729 M W 4:10pm - 5:25pm
Room TBA
Henry Lam 3 0/85

IEOR E4106 Stochastic Models. 3 points.

Lect: 3.

Prerequisites: (STAT GU4001)

This graduate course is only for MS&E, IE and OR students. This is also required for students in the Undergraduate Advanced Track. 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.

Summer 2018: IEOR E4106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4106 D01/14546  
Karl Sigman 3 5
Fall 2018: IEOR E4106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4106 001/63138 T Th 4:10pm - 5:25pm
501 Schermerhorn Hall
Karl Sigman 3 168/180
IEOR 4106 D01/23959  
Karl Sigman 3 4
IEOR 4106 R01/65195 F 3:00pm - 4:00pm
Room TBA
3 0/0
Spring 2019: IEOR E4106
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4106 001/16185 M W 4:10pm - 5:25pm
Room TBA
David Yao 3 0/120
IEOR 4106 R01/17084  
3 0/0

IEOR E4108 Supply Chain Management and Design. 3 points.

Prerequisites: IEOR 3402, IEOR 4000 or permission of instructor

Supply chain management, Model design of a supply chain network, inventories, stock systems, commonly used inventory models, supply contracts, value of information and information sharing, risk pooling, design for postponement, managing product variety, information technology and supply chain management; international and

Fall 2018: IEOR E4108
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4108 001/76549 T Th 9:00am - 10:15am
301 Uris Hall
Awi Federgruen 3 22/60

IEOR E4111 Operations Consulting. 3 points.

Prerequisites: (IEOR E3658) and (IEOR E4307) or (STAT GU4001) and Deterministic Models at the level of IEOR E3608 or IEOR E4004, or instructor permission.

This course is for MS-MS&E students only. This course 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. The course is 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.

Fall 2018: IEOR E4111
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4111 001/66355 Th 7:10pm - 9:40pm
501 Northwest Corner
Soulaymane Kachani 3 84/95
Spring 2019: IEOR E4111
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4111 001/11622 Th 7:10pm - 9:40pm
Room TBA
Soulaymane Kachani 3 0/85

IEOR E4150 Introduction to probability and statistics. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

Prerequisites: Calculus, including multiple integration.

This course 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: point and confidence interval estimation, hypothesis tests, linear regression.

Fall 2018: IEOR E4150
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4150 001/76924 M W 11:40am - 12:55pm
501 Northwest Corner
Antonius Dieker 3 109/180

IEOR E4207 Human Factors: Performance. 3 points.

Lect: 3.

Prerequisites: Refer to course syllabus.

This course is required for undergraduate students majoring in IE. This course provides a survey of human performance engineering in the design of consumer products, user interfaces and work processes. The goal of the course is to provide the student with the ability to specify human performance variables affecting user performance, safety and satisfaction for a variety of products and task requirements. Topics include task analysis, information processing, anthropometry, control and display design, human computer interaction, usability testing, usability cost/ benefit analysis, forensics, motivation, group dynamics and personnel selection. Course requirements include a research paper and a (group) product redesign project. At the end of the course students will have a deeper understanding of the research and psychological principles underlying human performance capabilities and limitations. The hope is that this course will encourage students to become more of "a user advocate" in their future endeavors.

Fall 2018: IEOR E4207
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4207 001/77578 M 4:10pm - 6:40pm
603 Hamilton Hall
Leon Gold 3 25/50

IEOR E4208 Seminar in Human Factors Design. 3 points.

Lect: 3.

Prerequisites: (IEOR E4207) or IEOR E4207: Human Factors: Performance or the instructor's permission.

This course is an elective undergraduate students majoring in IE. This course is an advance seminar in the field of human factors. A significant part of the course will explore methodologies and tools that facilitate the integration of psychological and human factor research in the design of new products and processes. The first part of the seminar will discuss methodological issues associated with human factor research and product evaluation. The second part of the seminary will address specific "user centered" methodologies (ISO, ANSI) that support the design process. The third part of the course will explore alternative product evaluation techniques. Students will be required to critique scientific research articles in class, and to perform a usability evaluation of a redesigned product. This is a seminar and therefore class participation is important. The opportunity to pursue individual interests in human factors (e.g. consumer, financial and medical product design, human computer interaction, stress, error analysis, usability evaluation, augmented cognition) is strongly encouraged.

Spring 2019: IEOR E4208
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4208 001/28376 M 4:10pm - 6:40pm
Room TBA
Leon Gold 3 9/40

IEOR E4211 Applied consulting. 0 points.

Prerequisites: (IEOR E3658) and (IEOR E4307) or (IEOR E4150) or (STAT GU4001) and familiarity with R or SAS.

Basic and advanced techniques in commercial and government consulting. Case studies supported by lectures focused on collecting and analyzing skills, client/market data, client interview techniques, and application of quantitative and qualitative methodologies. Exposure to critical skills on workplan development, interview techniques, presentation deck preparation, costing, and application of analytic techniques to solve complex problems. 

Spring 2019: IEOR E4211
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4211 001/12903 T Th 1:10pm - 2:25pm
Room TBA
0 40/60

IEOR E4307 Statistics and data analysis. 3 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.

Spring 2019: IEOR E4307
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4307 001/26964 T Th 11:40am - 12:55pm
Room TBA
Antonius Dieker 3 37/120

IEOR E4403 Quantitative corporate finance. 3 points.

Lect: 3.

Prerequisites: Probability theory and linear programming.

This course is 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 and businesses. Deterministic mathematical programming models for capital budgeting. Concepts in utility theory, game theory and real options analysis. 

Fall 2018: IEOR E4403
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4403 001/15127 F 10:10am - 12:40pm
451 Computer Science Bldg
David DeRosa 3 38/100

IEOR E4404 Simulation. 4 points.

Lect: 3. Recit: 1.

Prerequisites: (IEOR E3658) and (IEOR E4307) or (STAT GU4001) and computer programming.
Corequisites: IEOR E3106,IEOR E4106

This course is required for MSIE and MSOR. Graduate students must register for 3 points. Undergraduate students must register for 4 points. Generation of random numbers from given distributions; variance reduction; statistical output analysis; introduction to simulation languages; application to financial, telecommunications, computer, and production systems. Students who have taken IEOR E4703 Monte Carlo simulation may not register for this course for credit. Recitation section required.

Summer 2018: IEOR E4404
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4404 D01/74494  
Karl Sigman 4 2
Fall 2018: IEOR E4404
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4404 001/69442 M W 5:40pm - 6:55pm
207 Mathematics Building
Yi Zhang 4 127/130
IEOR 4404 D01/22743  
Karl Sigman 4 2/150
IEOR 4404 R01/24416 F 2:00pm - 3:00pm
Room TBA
4 0/0
Spring 2019: IEOR E4404
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4404 001/20931 T Th 5:40pm - 6:55pm
Room TBA
Yi Zhang 4 1/150
IEOR 4404 R01/62263  
4 0/0

IEOR E4405 Scheduling. 3 points.

Lect: 3.

Prerequisites: (IEOR E3608) and (IEOR E3658) and (IEOR E4307) and computer programming.

This course is 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 2019: IEOR E4405
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4405 001/18951 T Th 11:40am - 12:55pm
303 Seeley W. Mudd Building
Clifford Stein 3 54/100

IEOR E4407 Game Theoretic Models of Operations. 3 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.

This course is 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 2018: IEOR E4407
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4407 001/16409 M W 10:10am - 11:25am
303 Seeley W. Mudd Building
Vineet Goyal 3 72/86
IEOR 4407 R01/70287 F 10:00am - 11:00am
Room TBA
3 0/0

IEOR E4408 Resource Allocation: Models, Algorithms, and Applications. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

Prerequisites: (IEOR E3608) or (IEOR E4004) and basic knowledge of nonlinear and integer programming.

Overview of resource allocation models. Single resource allocation with concave returns; equitable resource allocation; lexicographic minmax/maxmin optimization; extensions to substitutable resources; multi-period resource allocation; equitable allocation in multicommodity network flow models; equitable content distribution in networks; equitable resource allocation with discrete decision variables. 

IEOR E4412 Quality Control and Management. 3 points.

Lect: 3.

Prerequisites: (IEOR E3658) and (IEOR E4307) or (STAT GU4001)

This course is 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 service. 

Spring 2019: IEOR E4412
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4412 001/77027 M W 5:40pm - 6:55pm
Room TBA
Sufian Ikhmeis 3 14/70

IEOR E4418 Transportation analytics and logistics. 3 points.

Lect: 3.

Prerequisites: (IEOR E3608 or IEOR E4404 or IEOR E4007 or CSOR W4231 or CSOR W4246) and (IEOR E3106 or IEOR E4307 or SIEO W3600 or IEOR E4100 or IEOR E4101 or IEOR E4150 or STAT GR5701 or STAT GR5703) or permission of instructor.

Transportation, primarily focused on the movement of people, and logistics, primarily focused on the movement of goods, are two of the most fundamental challenges to modern society. To address many problems in these areas, a wide array of mathematical models and analytics tools have been developed. This class will introduce many of the foundational tools used in transportation and logistics problems, relying on ideas from linear optimization, integer optimization, stochastic processes, statistics, and simulation. We will address problems such as optimizing the routes of cars and delivery trucks, positioning emergency vehicles, and controlling traffic behavior. Moreover, we will discuss modern issues such as bicycle sharing, on-demand car and delivery services, and humanitarian logistics. Concepts will be reinforced with technical content as well as real-world data and examples. Prerequisites: A course in probability/statistics (e.g., IEOR 3106, IEOR 4307, SIEO 3600, IEOR 4100, IEOR 4101, IEOR 4150, STAT 5701, STAT 5703). A course in optimization (e.g., IEOR 3608, IEOR 4004, IEOR 4007, CSOR 4231, CSOR 4246).

Spring 2019: IEOR E4418
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4418 001/12128 M W 5:40pm - 6:55pm
Room TBA
Adam Elmachtoub 3 23/80

IEOR E4500 Applications Programming for Financial Engineering. 3 points.

Lect: 3.

Prerequisites: Computer programming or instructor's approval.

This course is required for undergraduate students majoring in OR:FE. In this course 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 will 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 will review topics of interest to OR/FE in a holistic fashion.

Fall 2018: IEOR E4500
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4500 001/71361 T Th 5:40pm - 6:55pm
833 Seeley W. Mudd Building
Daniel Bienstock 3 95/120
IEOR 4500 R01/77506 F 9:00am - 10:00am
Room TBA
3 0/0
Spring 2019: IEOR E4500
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4500 001/77011 M W 5:40pm - 6:55pm
Room TBA
Daniel Bienstock 3 3/120

IEOR E4501 TOOLS FOR ANALYTICS. 3 points.

This goal of this course is to provide students with the computing tools that are necessary for data and business analytics. Students will be introduced to the basics of the Python programming language with special emphasis on the data analysis and visualization libraries available in the language (pandas, numpy, scikit-learn, bokeh). They will learn the basics skills for gathering and processing data for analytical exercises using APIs, SQL, and by deconstructing JSON data objects, and will also gain basic familiarity with data manipulation using the Unix shell.

Fall 2018: IEOR E4501
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4501 001/91096 M 7:30pm - 10:00pm
417 International Affairs Bldg
Paul Bulkley-Logston 3 96/200
IEOR 4501 002/83247 T 7:30pm - 10:00pm
501 Schermerhorn Hall
Paul Bulkley-Logston 3 165/189

IEOR E4505 Operations Research in Public Policy. 3 points.

Prerequisites: (IEOR E3608) or (IEOR E4004) and (IEOR E3106) or (IEOR E4106)

This course 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. The course will draw on a variety techniques such as linear and integer programming, statistical and probabilistic methods, decision analysis, risk analysis, and analysis & control of dynamic systems.

Spring 2019: IEOR E4505
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4505 001/64572 T Th 8:40am - 9:55am
303 Seeley W. Mudd Building
Jay Sethuraman 3 27/80

IEOR E4506 Design Digital Operating Models. 3 points.

Focus on the fast evolving sectors of ecommerce, advertising technology, and marketing technology, as venture capitalists chase returns in the ever increasing automation of the marketing, sales, and advertising functions. Understand industry dynamics, algorithms, patents, and business models at the core of the most successful players in the business.  Explore and define the different types of data in the industry and how they are used.

Fall 2018: IEOR E4506
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4506 001/17196 M 7:10pm - 9:40pm
413 Kent Hall
Anthony Effik 3 51/60

IEOR E4507 Healthcare operations management. 3 points.

Not offered during 2018-19 academic year.

Prerequisites: (IEOR E3608) and (IEOR E3658) and (IEOR E4307)

Develops modeling, analytical and managerial skills of Engineering students. Enables students to master an array of fundamental Operations Management tools adapted to the management of manufacturing and service systems in banks, hospitals, factories, and government. Special emphasis is placed on healthcare systems. Through real-world business cases, students learn to identify, model and analyze operational improvements and innovations in a range of business contexts, especially healthcare contexts.
,

Fall 2018: IEOR E4507
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4507 001/66297 T Th 8:40am - 9:55am
517 Hamilton Hall
Van Anh Truong 3 15/80

IEOR E4510 Project Management. 3 points.

Lect: 3.

Prerequisites: (IEOR E4004) or (IEOR E3608)

Management of complex project 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 2019: IEOR E4510
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4510 001/71623 M 7:10pm - 9:40pm
Room TBA
Moshe Rosenwein 3 42/120

IEOR E4520 Applied Systems Engineering. 3 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-work flow at the top of every major engineering project.

Summer 2018: IEOR E4520
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4520 D01/65583  
Ebad Jahangir 3 7
Fall 2018: IEOR E4520
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4520 001/21449 W 4:10pm - 6:00pm
209 Havemeyer Hall
Ebad Jahangir 3 33/95
IEOR 4520 V01/13831 W 4:10pm - 6:00pm
209 Havemeyer Hall
Ebad Jahangir 3 3

IEOR E4522 Python for Operations Research. 1 point.

Lect: 1.5.Not offered during 2018-19 academic year.

IEOR Students Only; Priority to MSOR Students. Introduction to programming in Python, providing a working knowledge of how to use Python to extract knowledge and information from data. Overview of Python libraries for data analysis. Fundamental course for MSOR students in order to engage in higher level analytics courses.

IEOR E4523 Data Analytics. 3 points.

Lect: 3.

Corequisites: IEOR E4522

Co-requisite: IEOR E4501 Tools for Analytics. 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, Scikit­learn, 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.

 

Fall 2018: IEOR E4523
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4523 001/29996 M 8:40am - 11:10am
1127 Seeley W. Mudd Building
Hardeep Johar 3 69/70
IEOR 4523 002/64474 W 7:10pm - 9:40pm
1024 Seeley W. Mudd Building
Yair Avgar 3 39/70
IEOR 4523 V01/64868 M 8:40am - 11:10am
1024 Seeley W. Mudd Building
Hardeep Johar 3 2
Spring 2019: IEOR E4523
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4523 001/60039 Th 1:10pm - 3:40pm
Room TBA
Uday Menon 3 0/75

IEOR E4524 Analytics in Practice. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

Prerequisites: (IEOR E4522) or (IEOR E4578) and (IEOR E4523)

MSOR 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, come with the sources of data pre¬-identified, and have been structured so that they can be completed in one semester. This is a client facing class with numerous on-site client visits; students should keep their Fridays clear for this purpose.

IEOR E4525 Machine Learning for Financial Engineering and Operations. 3 points.

Prerequisites: optimization, applied probability, statistics or simulation.

Introduction to Machine Learning, practical implementation ML algorithms and applications to financial engineering and operations. Probabilistic Tools of Machine Learning, Learning theory, Classification, Resampling Methods and Regularization, Support Vector Machines (SVMs), Unsupervised Learning, Dimensionality Reduction and Clustering algorithms, EM Algorithm, and Neural Networks and Deep Learning

Fall 2018: IEOR E4525
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4525 001/17696 F 10:10am - 12:40pm
501 Schermerhorn Hall
Manuel Balsera 3 47/160
Spring 2019: IEOR E4525
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4525 001/74094 F 10:10am - 12:40pm
Room TBA
Manuel Balsera 3 0/150

IEOR E4526 Analytics on the Cloud. 3 points.

Not offered during 2018-19 academic year.

To introduce students to the programming issues around working with clouds for data analytics. The class will learn how to work with the infrastructure of cloud platforms, and discussion about distributed computing, the focus of the course is on programming. Topics covered will include MapReduce, parallelism, the rewriting of algorithms (statistical, OR, and machine learning) for the cloud, and the basics of porting applications so that they run on the cloud.

IEOR E4540 Data Mining. 3 points.

The course will cover major statistical learning methods for data mining under both supervised and unsupervised settings. Topics covered include linear regression and classi
fication, model selection and regularization, tree-based methods, support vector machines, and unsupervised learning. Students will learn about the principles underlying each method, how to determine which methods are most suited to applied settings, concepts behind model fi
tting and parameter tuning, and how to apply methods in practice and assess their performance. We will emphasize roles of statistical modeling and optimization in data mining. 

 

Fall 2018: IEOR E4540
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4540 001/61147 M 7:10pm - 9:40pm
310 Fayerweather
Krzysztof Choromanski 3 33/85
Spring 2019: IEOR E4540
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4540 001/72803 T 7:10pm - 9:40pm
Room TBA
Krzysztof Choromanski 3 24/80

IEOR E4550 Entrepreneurial Business Creation for Engineers. 3 points.

Lect: 3.

Prerequisites: (IEOR E2261)

This course is required for undergraduate students majoring in OR:EMS. Introduce basic concepts and methodologies that are used by the nonengineering part of the world in creating, funding, investing in, relating to, and operating entrepreneurial ventures. The first half of the course focuses on the underpinning principles and skills required in recognizing, analyzing, evaluating, and nurturing a business idea.The second half focuses on basic legal knowledge necessary in creating a business entity, defending your business assets, and in promoting effective interaction with other individuals and organizations. 

Fall 2018: IEOR E4550
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4550 001/22818 M 4:10pm - 6:40pm
633 Seeley W. Mudd Building
David Gulley 3 34/70
IEOR 4550 V01/21527 M 4:10pm - 6:40pm
633 Seeley W. Mudd Building
David Gulley 3 2

IEOR E4555 Design and Agile Project Management Engineering Lab. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

An intensive, team and project­-based seminar in which students will learn: (1) a multi-­disciplinary approach to evidence ­based product design;(2) agile project planning and execution; (3) rapid MVP prototyping; and (4) launch strategy formulation and implementation. Focuses on the practical use of design thinking, design studio, and iterative design sprint methodologies. Systematic approach to Lean User Research, User Experience (UX), and User Interface (UI) design and deployment are integral components of the course curriculum. Mix of startup and enterprise projects that are either application ­drive, data­ driven, or a combination of both. Teams are fully supported in devising prototypes and actualizing their proposed solutions. Note: This course is by application only.

IEOR E4561 Launch Your Startup: Tech. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

Tools and knowledge to develop a comprehensive new venture that is scalable, repeatable and capital efficient. Covering customer discovery, market sizing, pricing, competition, distribution, funding, developing a minimal viable product and other facets of creating a new ventures. A company blueprint and final investor pitch are deliverables. 

IEOR E4570 Entrepreneurship Bootcamp for Engineers. 1 point.

1.5 points

This course is designed as an introductory exposure to entrepreneurial concepts and practical skills for engineering students who wish to explore entrepreneurship conceptually or as a future endeavor in their careers. The class will be a mix of lecture, guest speakers from the entrepreneurship community, and work-shopping concepts we cover. Grades will be based on class participation and engagement as well as final pitch in which students describe their key takeaways & insights gleaned from the process.

Fall 2018: IEOR E4570
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4570 001/25546  
Adam Royalty 1 17/45
Spring 2019: IEOR E4570
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4570 001/27819  
Adam Royalty 1 0/40
IEOR 4570 002/74671  
Adam Royalty 1 0/25

IEOR E4571 Personalization: Theory & Application. 3 points.

Personalization is a key lever for enhancing customer experience across industry verticals, thereby driving user loyalty and consumer value. It is therefore no surprise that personalization is also increasingly one of the core responsibilities of data science teams, and a key focus for many of the machine learning algorithms in the sector. This course will focus on common personalization algorithms and theory, including behaviorbased and content-based recommendation, commonly encountered issues in scaling and coldstarts, and state of the art research. It will also look at how businesses use, and misuse, these techniques in real world applications.

Fall 2018: IEOR E4571
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4571 001/91349 W 7:00pm - 9:30pm
608 Schermerhorn Hall
Brett Vintch 3 34/35

IEOR E4572 Data Analytics for Operations Research. 3 points.

Lect: 3.

Prerequisites: Mathematical and scientific programming. Data visualization. Introduction to analysis of social networks using computational techniques in network analysis and natural language processing. BS IEOR Program students only.

Fall 2018: IEOR E4572
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4572 001/71513 M W 2:40pm - 3:55pm
209 Havemeyer Hall
Hardeep Johar 3 47/80
Spring 2019: IEOR E4572
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4572 001/68867 T 7:10pm - 9:40pm
Room TBA
3 0/60

IEOR E4573 Financial Decision Models for Engineers. 3 points.


,Financial Decision Models for Engineers is aimed at IEOR students with an interest in financially-oriented applications of foundational IEOR subjects.  The course builds on students’ knowledge of probability, statistics, simulation, optimization, and large data analytics, as well as the financial material covered Accounting and Finance and IEOR E4003/4403.  The course focuses on rigorous analysis and modeling of real-world problems, with an emphasis on understanding modeling assumptions and limitations. 

,


,The class cycles through a variety of finance-oriented topics and solution methodologies, such as (for example): real options solved with simulation models; optimal project costing and scheduling with random variable (RV) task durations and costs; DCF entity valuations with RV costs, revenues and free cash flows; decision tree evaluation with time value and RV cash flows; and single and multi-period portfolio optimization.  

Fall 2018: IEOR E4573
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4573 001/83097 W 4:10pm - 6:40pm
310 Fayerweather
Anthony Webster 3 9/80
Spring 2019: IEOR E4573
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4573 001/60674 T 1:10pm - 3:40pm
Room TBA
3 0/60

IEOR E4575 Mathematics for Business Analytics Bootcamp. 0 points.

IEOR E4576 Derivatives Marketing & Structuring. 1 point.

1.5 pts

The availability of data, technical information, and open source software has greatly impacted the job market for quants. While machines have started to replace some trading positions such as market making in very liquid instruments, there is still a growing need for structuring where derivative instruments are used to help companies and institutions to manage their risks.


Structuring skills are also in demand at Corporate Treasuries where the emphasis is on using derivatives to manage various financial exposures such as interest rates, Foreign Exchange (FX), or commodities etc. Treasuries of companies usually do not engage in developing pricing modules but apply FE techniques to their hedging, funding, and investment activities to ensure that they receive the best price from the market. Moreover, the accounting treatment of derivatives is also of utmost importance for public companies as it impacts their income statement and ROE and ROA. 


Similarly, all major banks and investment houses have teams of Derivatives Marketers and structures who help companies and customers in developing and selecting the optimum risk management tools.


This course should give students an edge in their job search and also expand the universe of their opportunities to cover Corporate Treasuries.

IEOR E4577 Intellectual property for entrepreneurs and managers. 0 points.

Lect: 3.Not offered during 2018-19 academic year.

An overview of commercial opportunities in intellectual property, with a focus on technology patents for the business or tech entrepreneur.

IEOR E4578 Corporate Finance, Accounting & Investment Banking. 0 points.

Prerequisites: Must be registered in one of the MS IEOR Programs

This course, “Introduction to Corporate Finance, Accounting and Investment Banking”, previously called “Quantitative Corporate Finance”, is designed for students considering working in Investment Banking or in the Finance department of a Corporation, and who have limited knowledge of Corporate Finance or Accounting. 

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This course will review the primary financial theories and alternative theories underlying Corporate Finance, such as CAPM, Miller Modigliani, Fama French factors, Smart Beta, etc. By completing this course, you will gain the core skills to interpret financial statements, build cash flow models, value projects, value companies, and make Corporate Finance decisions. 

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Among the topics covered: the cost of capital, dividend policy, debt policy, the impact of taxes, Shareholder / Debtholder agency costs, dual-class shares, and how option pricing theory can be used to analyze management behavior. We will study the application of theory in real-world situations by analyzing the financial activities of companies such as General Electric, Google, Snapchat, Spotify and Tesla.  In addition, you will learn about a variety of investment banking activities, including equity underwriting, syndicated lending, venture capital, private equity investing and private equity secondaries.

Fall 2018: IEOR E4578
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4578 001/83297 W 4:10pm - 6:40pm
1127 Seeley W. Mudd Building
Rodney Sunada-Wong 0 35/80
IEOR 4578 V01/18147 W 4:10pm - 6:40pm
1127 Seeley W. Mudd Building
Rodney Sunada-Wong 0 7/80
Spring 2019: IEOR E4578
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4578 001/71331 F 10:00am - 1:00pm
Room TBA
Orin Herskowitz 0 1/50

IEOR E4579 Professional Development for Industrial Engineering & Operations Research. 0 points.

Students will engage, learn and share their experiences in order to make meaning of professional development. The instructional team hopes that the students will obtain the following: gain familiarity and insight to the US job market and US career culture; recognize the skills necessary to compete effectively; increase student professional intelligence, develop own professional self and identify developmental needs; obtain information on employment trends, resources and networking opportunities; refine resume writing, interviewing, and job search skills; establish a collaborative relationship with the instructional team and provide constructive feedback where appropriate to enhance the student's professional development.

IEOR E4600 Applied Integer Programming. 3 points.

Lect: 3.

Prerequisites: Linear programming, linear algebra, and computer programming.

This course is required for undergraduate students majoring in OR. This course covers applications of mathematical programming techniques, especially integer programming, with emphasis on software implementation. This course also covers topics of modeling and solution of problems in supply chain, logistics, routing. Particular emphasis is placed on optimization modeling systems, such as AMPL and OPL and state-of-the-art solvers.

IEOR E4601 Dynamic Pricing and Revenue Management. 3 points.

Lect: 3.

Prerequisites: (STAT GU4001) and (IEOR E4004)

Focus on capacity allocation, dynamic pricing and revenue management. Perishable and/or limited product and pricing implications. Applications to various industries including service, airlines, hotel, resource rentals, etc.

Spring 2019: IEOR E4601
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4601 001/19213 T Th 4:10pm - 5:25pm
303 Seeley W. Mudd Building
Van Anh Truong 3 9/80
IEOR 4601 R01/76740  
3 0/0

IEOR E4602 Quantitative Risk Management. 3 points.

Lect: 3.

Prerequisites: (STAT GU4001) and (IEOR E4106)

Risk management models and tools; measure risk using statistical and stochastic methods, hedging and diversification. Examples of this 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.

Spring 2019: IEOR E4602
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4602 001/71033 T Th 1:10pm - 2:25pm
Room TBA
3 0/80

IEOR E4611 Decision Models and Applications. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

Prerequisites: (IEOR E3608) and (IEOR E4004) or (IEOR E3658) and (IEOR E4307) and (STAT GU4001) or the equivalent. For graduate students: instructor's permission is required.
Corequisites: IEOR E4404

Students are introduced to deterministic and stochastic decision tools used by leading corporations and applied researchers, and apply these software packages to complex, real-world problems in engineering and finance. Building on a basic theoretical understanding of optimization, simulation and game theory obtained in prerequisite classes, students master commercial decision modeling programs such as Premium Solver Professional (linear, integer and non-linear optimization), TreePlan (decision-trees), Crystal Ball (simulation), and OptQuest (optimization under uncertainty). Students are also welcome to complete most modeling assignments with Matlab. After students have mastered the course software, its limitations and the frameworks for applying it, they work in small teams to address (as a mid-term project) one large-scale deterministic project and (as an end-of-semester project) one similarly-complex stochastic problem. While addressing their first projects, students learn effective presentation and project reporting skills, suitable for communicating with CFOs and CEOs. Students present their project analyses to a small panel of industry experts and executives. Throughout the course, the importance of outside-the-model considerations, model limitations and sources of modeling error are stressed, and general frameworks for approaching particular problem types are developed.

IEOR E4615 Service Engineering. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

Prerequisites: (SIEO W3600) and (IEOR E3106) or (IEOR E4106) or equivalent.

Focus on service systems viewed as stochastic networks, exploiting the theoretical framework of queueing theory. Includes multi-disciplinary perspectives involving Statistics, Psychology and Marketing. Significant emphasis on data analysis, exploiting data from banks hospitals and call centers to demonstrate the use of decision support tools. Analytical models, flow models of service networks, Little’s law , measuring methods in face-to-face and computerized systems, forecasting methods, stability of service systems, operational quality of service, economies of scale, staffing, complex service networks, skill based routing.

IEOR E4620 Pricing Models for Financial Engineering. 3 points.

Lect: 3.

Prerequisites: (IEOR E4700)

This course is 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 2018: IEOR E4620
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4620 001/74461 T 7:10pm - 9:40pm
1024 Seeley W. Mudd Building
Michael Miller 3 27/70

IEOR E4630 Asset Allocation. 3 points.

Lect: 3.

Prerequisites: (IEOR E4700)

Models for pricing and hedging equity, fixed-income, credit-derivative securities, standard tools for hedging and risk management, models and theoretical foundations for pricing equity options (standard European, American equity options, Asian options), standard Black-Scholes model (with multiasset extension), asset allocation, portfolio optimization, investments over longtime horizons, and pricing of fixed-income derivatives (Ho-Lee, Black-Derman-Toy, Heath-Jarrow-Morton interest rate model). 

Spring 2019: IEOR E4630
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4630 001/18122 T 7:10pm - 9:40pm
303 Seeley W. Mudd Building
Alireza Javaheri 3 15/100

IEOR E4650 Business analytics. 3 points.

Lect: 3. Recit: 1.

Prerequisites: (STAT GU4001) or (IEOR E4150)

In this course, you will learn how to identify, evaluate, and capture business analytic opportunities that create value. Toward this end, you will learn basic analytical methods and analyze case studies on organizations that successfully deployed these techniques. In the first part of the course, we focus on how to use data to develop insights and predictive capabilities using machine learning and data mining techniques. In the second part, we focus on the use of optimization and simulation to support prescriptive decision-making in the presence of a large number of alternatives and business constraints. Finally, throughout the course, we explore the challenges that can arise in implementing analytical approaches within an organization.

Fall 2018: IEOR E4650
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4650 001/67557 T 10:00am - 1:00pm
1127 Seeley W. Mudd Building
Charles Guetta 3 50/80
IEOR 4650 002/23626 T 2:30pm - 5:30pm
403 International Affairs Bldg
Charles Guetta 3 76/88
IEOR 4650 R01/16069 F 10:00am - 11:00am
Room TBA
3 0/0
Spring 2019: IEOR E4650
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4650 001/22937 M W 11:40am - 12:55pm
Room TBA
Adam Elmachtoub 3 0/75
IEOR 4650 002/66329 M W 1:10pm - 2:25pm
Room TBA
Adam Elmachtoub 3 0/75

IEOR E4700 Introduction to Financial Engineering. 3 points.

Lect: 3.

Prerequisites: (IEOR E3106) or (IEOR E4106)

This course is 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. 

Fall 2018: IEOR E4700
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4700 001/15830 T 8:40am - 11:10am
303 Seeley W. Mudd Building
David Yao 3 42/85
IEOR 4700 R01/12083 F 10:00am - 11:00am
603 Hamilton Hall
3 0/0
Spring 2019: IEOR E4700
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4700 001/16971 M W 11:40am - 12:55pm
Room TBA
David Yao 3 27/150
IEOR 4700 R01/28274  
3 0/0

IEOR E4701 Stochastic Models for Financial Engineering. 3 points.

Lect: 3.

Prerequisites: (STAT GU4001)

This graduate course is only for MS Program in FE 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 2018: IEOR E4701
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4701 001/64994 T Th 8:40am - 9:55am
833 Seeley W. Mudd Building
Daniel Lacker 3 118/120

IEOR E4703 Monte Carlo Simulation. 3 points.

Lect: 3.

Prerequisites: (IEOR E4701)

This graduate course is only for MS Program in FE 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 2019: IEOR E4703
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4703 001/17636 T Th 4:10pm - 5:25pm
Room TBA
Ali Hirsa 3 0/120

IEOR E4706 Foundations of Financial Engineering. 3 points.

Lect: 3.

Prerequisites: (IEOR E4701) and (IEOR E4702) and linear algebra.

This graduate course is only for MS Program in FE 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 2018: IEOR E4706
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4706 001/24866 T Th 4:10pm - 5:25pm
428 Pupin Laboratories
Dylan Possamai 3 120/120
IEOR 4706 R01/12743 F 2:00pm - 3:00pm
Room TBA
3 0/0
IEOR 4706 V01/72563 T Th 4:10pm - 5:25pm
428 Pupin Laboratories
Dylan Possamai 3 3

IEOR E4707 Financial Engineering: Continuous-Time Asset Pricing. 3 points.

Lect: 3.

Prerequisites: (IEOR E4701)

This graduate course is only for MS Program in FE students. Modeling, analysis, and computation of derivative securities. Application of stochastic calculus and stochastic differential equations. Numerical techniques: finite-difference, binomial method, and Monte Carlo.

Spring 2019: IEOR E4707
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4707 001/28140 T Th 5:40pm - 6:55pm
Room TBA
Xunyu Zhou 3 0/120

IEOR E4708 Seminar on Important Papers in Financial Engineering. 3 points.

Lect: 3.

Prerequisites: (IEOR E4703) and (IEOR E4706) and IEOR E4703, E4706, probability and statistics.

Selected topics of special interest for M.S. students interested in financial engineering.

IEOR E4709 Statistical analysis and time series. 3 points.

Lect: 3.

Prerequisites: Probability.
Corequisites: IEOR E4706,IEOR E4702

This graduate course is only for MS Program in FE 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, nonlinear regression and fitting of term structures. 

Spring 2019: IEOR E4709
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4709 001/15904 T Th 10:10am - 11:25am
Room TBA
Agostino Capponi 3 1/125
IEOR 4709 R01/26435  
3 0/0

IEOR E4710 Fixed income and term structure modeling. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

Prerequisites: (IEOR E4706) and (IEOR E4707) and computer programming.

Interest rate models and numerical techniques for pricing and hedging interest rate contracts and fixed income securities. Introduction to interest models in discrete and continuous time including lattice models, single- and multi- factor models, Heath-Jarrow-Morton and market models. Martingale and PDE methods for pricing and hedging interest-rate derivatives. Monte-Carlo methods for term structure models. Additional applications from mortgage modeling and fixed income asset allocation and risk management.

IEOR E4711 Global Capital Markets. 3 points.

Prerequisites: Refer to course syllabus.

Fall: Global Capital Markets, taught by Professor S. Dastidar. This course is an introduction to capital markets and investments. It provides an overview of financial markets and teaches you tools for asset valuation that will be very useful in your future career. The extract below is from last year. While I was keen to have similar content, the class complained last year that the topics 2 and 3 were too esoteric for them. Based on what the class feels, I am probably going to replace it with general content on equities (i.e. replace 2 and 3 with 4). This course then becomes very similar to Capital Markets and Investments offered by the Business School. We will cover: 1. The pricing of fixed income securities (treasury markets, interest rate swaps, futures etc) 2. Discussions on topics in credit, foreign exchange, sovereign and securitized markets (we may drop this) 3. Private markets - private equity and hedge funds, etc. (we may drop this) 4. We shall spend some time on equity markets and their derivatives, time permitting. We will aim to take a hands-on approach in this course. The course is somewhat quantitative in nature; you should be prepared to work with data and spreadsheets. Programming is not required. Nevertheless, this is a basic foundations course, and does not assume much prior knowledge in finance. Consequently, the course emphasizes a few cardinal principles while getting into some institutional detail. The word "Global" in the title implies that the concepts we discuss are relevant to all geographies; we will rarely get into specifics of any particular region.

Fall 2018: IEOR E4711
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4711 001/60559 T 7:00pm - 9:30pm
614 Schermerhorn Hall
Siddhartha Ghosh Dastidar 3 47/80
IEOR 4711 002/26016 W 7:00pm - 9:30pm
717 Hamilton Hall
Siddhartha Ghosh Dastidar 3 20/80

IEOR E4712 Behavioral Finance. 3 points.

Not offered during 2018-19 academic year.

Prerequisites: (IEOR E4700)

Behavioral finance is the application of behavioral psychology to financial decision making. Focus on the portfolio aspect of behavioral finance, and briefly touches others. Compared with the classical theory of portfolio choice, behavioral portfolio choice features human being's psychological biases. It builds both on behavioral preference structures different from mean variance theory and expected utility theory and on systematic biases against rational beliefs such as Bayesian rule.

IEOR E4714 Risk Management, Financial System & Financial Crisis. 1.5 point.

Risk-taking and risk management are at the heart of the financial system, and of the current financial crisis. An introduction to risk management both from an individual financial firm's and from a public policy viewpoint. Overview of the contemporary financial system, focusing on innovations of the past few decades that have changed how financial risk is generated and distributed among market participants, such as the growth of non-bank financial intermediaries, the increased prevalence of leverage and liquidity risk, and the development of structured credit products. Introduction to the basic quantitative tools used in market, credit and liquidity risk management. The two strands of the course are brought together to help understand how the financial crisis arose and is playing out, examining the mechanics of runs and the behavior of asset prices during crises. We also attempt to make sense of the emergency programs deployed by central bankers and other policy makers to address crises historically and today.

IEOR E4715 Commodity Derivatives. 1.5 point.

Commodities markets have been much in the public eye recently as volatility has increased and they changed from markets dominated by physical participants to ones which have a significant investor component. The largest banks either already have profitable commodities franchises already or are actively building them, and money managers and funds are increasingly including these assets in their portfolio mix. The end result is a dramatic increase in focus on these markets from all aspects of the financial markets, including the quantitative end.

IEOR E4718 Beyond black-scholes: the implied volatility smile. 3 points.

Lect: 3.

Prerequisites: (IEOR E4706) and knowledge of derivatives valuation models.

During the past fifteen years the behavior of market options prices have shown systematic deviations from the classic Black-Scholes model. The course 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 of these models for hedging and valuation.

Spring 2019: IEOR E4718
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4718 001/18358 M W 1:10pm - 2:25pm
Room TBA
Emanuel Derman 3 4/80

IEOR E4720 Deep Learning. 1 point.

2

Prerequisites: (IEOR E4700) and additional prerequisites will be announced depending on offering.

Selected topics of interest in the area of quantitative finance. Offerings vary each year; some topics include energy derivatives, experimental finance, foreign exchange and related derivative instruments, inflation derivatives, hedge fund management, modeling equity derivatives in Java, mortgage-backed securities, numerical solutions of partial differential equations, quantitative portfolio management, risk management, trade and technology in financial markets.

Fall 2018: IEOR E4720
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4720 001/92297 T Th 10:10am - 11:25am
214 Pupin Laboratories
Ali Hirsa 1 60/60
Spring 2019: IEOR E4720
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4720 001/71158 T Th 11:40am - 12:55pm
Room TBA
Ali Hirsa 1 0/80

IEOR E4721 Mathematics of Finance for FE Bootcamp. 1.5-3 points.

Prerequisites: IEOR E4700: Introduction to Financial Engineering, additional pre-requisites will be announced depending on offering.

Selected topics of interest in the area of quantitative finance. Offerings vary each year; some topics include: Energy Derivatives, Experimental Finance, Foreign Exchange and Related Derivative Instruments, Inflation Derivatives, Hedge Fund Management, Modeling Equity Derivatives in Java, Mortgage-backed Securities, Numerical Solutions of Partial Differential Equations, Quantitative Portfolio Management, Risk Management, Trade and Technology in Financial Markets.

Fall 2018: IEOR E4721
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4721 001/73460  
Michael Miller 1.5-3 119/120

IEOR E4722 Stochastic Control and Financial Applications. 3 points.

Prerequisites: IEOR E4707 Refer to course syllabus.

This course covers stochastic control theory and applications in finance. It includes the following topics: 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; optimal stopping and variational inequalities; continuous-time expected utility maximization; continuous-time mean-variance portfolio selection and properties of efficient strategies; algorithmic and high frequency trading.

Fall 2018: IEOR E4722
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4722 001/11496 W 10:10am - 12:40pm
270b International Affairs Bldg
Xunyu Zhou 3 7/80

IEOR E4724 Python For Financial Engineering Bootcamp. 0 points.

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

Lect: 3.Not offered during 2018-19 academic year.

Prerequisites: (IEOR E4706) and (IEOR E4707) IEOR E4706 and IEOR E4707.

The course covers derivations and solutions of partial differential equations under variety of underlying stochastic price processes. Students will gain exposure to applications of partial differential equations to security pricing in different financial markets (i.e. equity derivatives, fixed income securities and credit derivative markets).

IEOR E4726 Applied Financial Risk Management. 3 points.

This course introduces risk management principles, with an emphasis on their practical implementation and application. It presents standard market, liquidity and credit risk measurement techniques, as well as their drawbacks and limitations. The course will convey much of the quantitative and technical material by working through calculation examples using market data and simple models. The example also introduce many sources of financial and statistical data, enabling students to better grasp the realities behind abstract financial concepts.


Students will understand risk management techniques from the viewpoint of practitioners, such as banks and other intermediaries. Many of these techniques have been adopted into financial regulatory standards. Especially since the crisis, regulatory standards have exerted great influence over firms’ risk management practices. The course will help understand this interaction, and the role of risk management in regulatory compliance.

Fall 2018: IEOR E4726
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4726 001/26391 T Th 2:40pm - 3:55pm
1127 Seeley W. Mudd Building
Allan Malz 3 59/80

IEOR E4727 Programming for Financial Engineering. 3 points.

Prerequisites: Refer to course syllabus.

This course covers features of the C++ programming language which are essential in financial engineering and its applications. We start by covering basic C++ programming features and then move to some more advance features. We utilize these features for financial engineering and quantitative finance applications.

Fall 2018: IEOR E4727
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4727 001/61006 Th 7:10pm - 9:40pm
833 Seeley W. Mudd Building
Sebastien Donadio 3 52/70

IEOR E4729 Financial Markets, Risk and Institutions. 1.5 point.

Lect: 1.5.

Prerequisites: (IEOR E4701) and (IEOR E4706)

This graduate course is only for MS Program in FE students, offered during the summer session. This core curriculum course introduces students pursuing a graduate degree in financial engineering to the main areas and concepts of modern finance. The course's objective is to provide an introduction to financial institutions, financial markets, and risk management as well as the broadest possible perspective on how financial theory and real-life practice interact, preparing students for successful careers in the financial industry and paving the way for in-depth studies that follow.

Spring 2019: IEOR E4729
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4729 001/77753 Th 7:10pm - 9:40pm
Room TBA
Kenneth Gleason 1.5 0/80

IEOR E4731 Credit risk modeling and derivatives. 3 points.

Lect: 3.

Prerequisites: (IEOR E4701) and (IEOR E4707)

Introduction to quantitative modeling of credit risk, with a focus on the pricing of credit derivatives. Focus on the pricing of single-name credit derivatives (credit default swaps) and collateralized debt obligations (CDOs). Details topics include default and credit risk, multiname default barrier models and multiname reduced form models. 

Fall 2018: IEOR E4731
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4731 001/65527 M W 1:10pm - 2:25pm
1127 Seeley W. Mudd Building
Agostino Capponi 3 31/80
IEOR 4731 V01/73370 M W 1:10pm - 2:25pm
1127 Seeley W. Mudd Building
Agostino Capponi 3 2

IEOR E4732 Computational Methods in Finance. 3 points.

Prerequisites: (IEOR E4700)

Applications to 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, calibration and calibration techniques, filtering and parameter estimation techniques. Computational platform: C++/Java/Python/Matlab/R.

Fall 2018: IEOR E4732
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4732 001/61863 Th 4:10pm - 6:40pm
1127 Seeley W. Mudd Building
Ali Hirsa 3 29/80
IEOR 4732 V01/20311 Th 4:10pm - 6:40pm
1127 Seeley W. Mudd Building
Ali Hirsa 3 4

IEOR E4733 Algorithmic Trading. 3 points.

Prerequisites: 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 2019: IEOR E4733
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4733 001/29084 W 7:10pm - 9:40pm
Room TBA
Sebastien Donadio 3 0/80

IEOR E4734 Foreign Exchange and Its Related Derivative Instruments. 1.5 point.

1.5.

Prerequisites: (IEOR E4700)

Foreign exchange market and its related derivative instruments - the latter being forward contracts, futures, options, and exotic options. What is unusual about foreign exchange is that although it can rightfully claim to be the largest of all financial markets it remains an area where very few have any meaningful experience. Virtually everyone has traded stocks, bonds, and mutual funds. Comparatively few individuals have ever traded foreign exchange. In part that is because foreign exchange is an interbank market. Yet ironically the foreign exchange markets may be the best place to trade derivatives and invent new derivatives - given the massive two-way flow of trading that goes though bank dealing rooms virtually twenty-four 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.

IEOR E4735 Structured and Hybrid Products. 3 points.

Lect: 3.

Prerequisites: (IEOR E4700)

Conceptual and practical understanding of structured and hybrid products from the standpoint of relevant risk factors, design goals and characteristics, pricing, hedging and risk management. Detailed analysis of the underlying cash-flows, embedded derivative instruments and various structural features of these transactions, both from the investor and issuer perspectives, and analysis of the impact of the prevailing market conditions and parameters on their pricing and risk characteristics. Numerical methods for valuing and managing risk of structured/hybrid products and their embedded derivatives and their application to equity, interest rates, commodities and currencies, inflation and credit-related products. Conceptual and mathematical principles underlying these techniques, and practical issues that arise in their implementations in the Microsoft Excel/VBA and other programming environments. Special contractual provisions often encountered in structured and hybrid transactions, and attempt to incorporate yield curves, volatility smile, and other features of the underlying processes into pricing and implementation framework for these products.

Fall 2018: IEOR E4735
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4735 001/97146 Th 7:10pm - 9:40pm
451 Computer Science Bldg
Alireza Javaheri 3 67/80

IEOR E4736 Event-driven finance. 3 points.

Lect: 3.

Prerequisites: (IEOR E4700) or equivalent.

The course takes a long deep look at the actual behavior of real stocks and options in the presence of commonplace, but singular events, such as earnings take-overs, hard-to-borrowness, expirations, etc. The course introduces concepts to propose trading schema (we organize tests via the very extensive and robust IVY options/stock database) and carry out tests efficiently and accurately. It exposes students to the striking differences between the model-based (static, thermodynamic/SDE model solutions) behavior predicted for stocks and options and their real (often quite different) behavior. They will become familiar with computational techniques for modeling and testing proposals for trading strategies. 

IEOR E4738 Programming for FE 1: Tools for Building Financial Data and Risk Systems. 3 points.

Lect: 3.

Prerequisites: Familiarity with object-oriented programming.

Object-oriented programming and database development for building financial data and risk systems; Python and Python's scientific libraries; basic database theory, querying and construction database; basic risk management and design of risk systems.

IEOR E4739 Programming for FE 2: Implementing High Performance Financial Systems. 3 points.

Lect: 2.5.

Prerequisites: (IEOR E4738)

Developing effective software implementations in C programming language; modeling of portfolio optimization; modeling of price impact trading models; review of synchronization of programs using threads; review of synchronization of programs using sockets; implementation of high-performance simulations in finance. 

IEOR E4900 Master's Research or Project. 1-3 points.

Prerequisites: Approval by a faculty member who agrees to supervise the work.

Independent work involving experiments, computer programming, analytical investigation, or engineering design.

Summer 2018: IEOR E4900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4900 001/83097  
Shipra Agrawal 1-3 0/20
IEOR 4900 002/26946  
Daniel Bienstock 1-3 0/20
IEOR 4900 003/17446  
Agostino Capponi 1-3 1/20
IEOR 4900 004/22346  
Emanuel Derman 1-3 0/20
IEOR 4900 005/28597  
Antonius Dieker 1-3 0/20
IEOR 4900 006/92067  
Adam Elmachtoub 1-3 0/20
IEOR 4900 007/79779  
Yuri Faenza 1-3 2/20
IEOR 4900 008/70941  
Donald Goldfarb 1-3 0/20
IEOR 4900 009/11279  
Vineet Goyal 1-3 0/20
IEOR 4900 010/92068  
Ali Hirsa 1-3 1/20
IEOR 4900 011/64692  
Garud Iyengar, Ali Hirsa 1-3 0/20
IEOR 4900 012/62146  
Hardeep Johar 1-3 0/20
IEOR 4900 013/66046  
Soulaymane Kachani 1-3 0/20
IEOR 4900 014/72196  
Daniel Lacker 1-3 0/20
IEOR 4900 015/77497  
Henry Lam 1-3 2/20
IEOR 4900 016/82446  
Dylan Possamai 1-3 1/20
IEOR 4900 017/86496  
Jay Sethuraman 1-3 0/20
IEOR 4900 018/91846  
Karl Sigman 1-3 0/20
IEOR 4900 019/96546  
Clifford Stein 1-3 0/20
IEOR 4900 020/98446  
Van Anh Truong 1-3 0/20
IEOR 4900 021/88529  
Ward Whitt 1-3 0/20
IEOR 4900 022/10780  
David Yao 1-3 0/20
IEOR 4900 023/11746  
David Yao, Xunyu Zhou 1-3 0/20
IEOR 4900 024/13596  
Jenny Mak 1-3 0/20
Fall 2018: IEOR E4900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4900 001/10350  
Shipra Agrawal 1-3 0/20
IEOR 4900 002/66595  
Daniel Bienstock 1-3 0/20
IEOR 4900 003/73413  
Agostino Capponi 1-3 0/20
IEOR 4900 004/28996  
Emanuel Derman 1-3 0/20
IEOR 4900 005/65140  
Antonius Dieker 1-3 0/20
IEOR 4900 006/67504  
Adam Elmachtoub 1-3 2/20
IEOR 4900 007/10732  
Yuri Faenza 1-3 3/20
IEOR 4900 008/21082  
Donald Goldfarb 1-3 0/20
IEOR 4900 009/76985  
Vineet Goyal 1-3 0/20
IEOR 4900 010/65023  
Ali Hirsa 1-3 4/20
IEOR 4900 011/73174  
Garud Iyengar 1-3 0/20
IEOR 4900 012/29750  
Hardeep Johar 1-3 0/20
IEOR 4900 013/68396  
Soulaymane Kachani 1-3 0/20
IEOR 4900 014/12502  
Daniel Lacker 1-3 0/20
IEOR 4900 015/10567  
Henry Lam 1-3 0/20
IEOR 4900 016/72178  
Dylan Possamai 1-3 2/20
IEOR 4900 017/67793  
Jay Sethuraman 1-3 0/20
IEOR 4900 018/18009  
Karl Sigman 1-3 0/20
IEOR 4900 019/25288  
Clifford Stein 1-3 0/20
IEOR 4900 020/19448  
Van Anh Truong 1-3 1/20
IEOR 4900 021/13260  
Ward Whitt 1-3 0/20
IEOR 4900 022/28598  
David Yao 1-3 0/20
IEOR 4900 023/63915  
Xunyu Zhou 1-3 1/20
IEOR 4900 024/68408  
Jenny Mak 1-3 0/20
Spring 2019: IEOR E4900
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4900 001/13050  
Shipra Agrawal 1-3 0/10
IEOR 4900 002/14537  
Daniel Bienstock 1-3 0/10
IEOR 4900 003/60089  
Agostino Capponi 1-3 0/10
IEOR 4900 004/21090  
Emanuel Derman 1-3 0/10
IEOR 4900 005/60990  
Antonius Dieker 1-3 0/10
IEOR 4900 006/64524  
Adam Elmachtoub 1-3 0/10
IEOR 4900 007/76689  
Yuri Faenza 1-3 0/10
IEOR 4900 008/74351  
Donald Goldfarb 1-3 0/10
IEOR 4900 009/60635  
Vineet Goyal 1-3 0/10
IEOR 4900 010/65812  
Ali Hirsa 1-3 0/10
IEOR 4900 011/66316  
Garud Iyengar 1-3 0/10
IEOR 4900 012/72831  
Hardeep Johar 1-3 0/10
IEOR 4900 013/76229  
Soulaymane Kachani 1-3 0/10
IEOR 4900 014/21168  
Daniel Lacker 1-3 0/10
IEOR 4900 015/77588  
Henry Lam 1-3 0/10
IEOR 4900 016/66887  
Dylan Possamai 1-3 0/10
IEOR 4900 017/64756  
Jay Sethuraman 1-3 0/10
IEOR 4900 018/15236  
Karl Sigman 1-3 0/10
IEOR 4900 019/29185  
Clifford Stein 1-3 0/10
IEOR 4900 020/72651  
Van Anh Truong 1-3 0/10
IEOR 4900 021/76662  
Ward Whitt 1-3 0/10
IEOR 4900 022/66408  
Yi Zhang 1-3 0/10
IEOR 4900 023/26335  
David Yao 1-3 0/10
IEOR 4900 024/66874  
Xunyu Zhou 1-3 0/10
IEOR 4900 025/21578  
Jenny Mak 1-3 0/10

IEOR E4998 Managing Technological Innovation and Entrepreneurship. 3 points.

Lect: 3.

This is 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. 

Fall 2018: IEOR E4998
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4998 001/68289 F 10:10am - 12:40pm
633 Seeley W. Mudd Building
Gerard Neumann 3 31/60
Spring 2019: IEOR E4998
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4998 001/16070 F 10:10am - 12:40pm
Room TBA
Gerard Neumann 3 22/80

IEOR E4999 Fieldwork. 0.5-2 points.

Prerequisites: Obtained internship and approval from faculty advisor.

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

Summer 2018: IEOR E4999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4999 001/92197  
Emanuel Derman, Lizbeth Morales 0.5-2 220/400
Fall 2018: IEOR E4999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4999 001/20164  
Ali Hirsa, Lizbeth Morales, Kristen Maynor 0.5-2 100/120
Spring 2019: IEOR E4999
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 4999 001/75627  
Emanuel Derman, Kristen Maynor 0.5-2 0/200

IEOR E6602 Nonlinear Programming. 3 points.

Lect: 3.

Prerequisites: PhD-level Linear Programming.

Convex sets and functions, convex duality and optimality conditions. Computational methods: steepest descent, Newton and quasi-newton methods for unconstrained problems, active set, penalty set, interior point, augmented Lagrangian and sequential quadratic programming methods for constrained problems. Introduction to non-differentiable optimization and bundle methods.

IEOR E6613 Optimization, I. 4.5 points.

Prerequisites: Refer to course syllabus.

Theory and geometry of linear programming. The simplex method. Duality theory, sensitivity analysis, column generation and decomposition. Interior point methods. Introduction to nonlinear optimization: convexity, optimality conditions, steepest descent and Newton's method, active set and barrier methods.

Fall 2018: IEOR E6613
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 6613 001/14946 M W 11:40am - 12:55pm
834 Seeley W. Mudd Building
Vineet Goyal 4.5 31/40
IEOR 6613 R01/75006 F 12:00pm - 1:00pm
Room TBA
4.5 0/0

IEOR E6614 Optimization, II. 4.5 points.

Lect: 3.

Prerequisites: Refer to course syllabus.

An introduction to combinatorial optimization, network flows and discrete algorithms. Shortest path problems, maximum flow problems. Matching problems, bipartite and cardinality nonbipartite. Introduction to discrete algorithms and complexity theory: NP-completeness and approximation algorithms.

Spring 2019: IEOR E6614
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 6614 001/73766 M W 4:10pm - 5:25pm
Room TBA
Yuri Faenza 4.5 0/40
IEOR 6614 R01/13147  
4.5 0/0

IEOR E6703 Advanced Financial Engineering. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

Prerequisites: Probability theory and advanced stochastic models at the SIEO GR6501 level.

Review of basic mathematics, including renewal theory and stochastic calculus. Martingale approach to Black-Scholes formula. Optimal stopping and American options. Pricing of continuous and discrete exotic options. Term structure models and pricing of bond options. Jump diffusion models. Applications, including pricing of real and electricity options and hedging of real options.

IEOR E6711 Stochastic models, I. 4.5 points.

Prerequisites: (STAT GU4001) or Refer to course syllabus.

This is the first course in a two-course sequence introducing students to the theory of stochastic processes. The fall term starts with a review of probability theory and then treats Poisson processes, renewal processes, discrete-time Markov chains and continuous-time Markov chains. The spring term emphasizes martingales and Brownian motion. Although the course does not assume knowledge of measure theory or measure-theoretic probability, the focus is on the mathematics. Proofs are emphasized. This course sequence is intended for our first-year doctoral students. Indeed, one of the two qualifying exams at the end of the first year covers the material taught in this course sequence. The course is intended to provide students background, so that they will be able to effectively conduct research.

Fall 2018: IEOR E6711
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 6711 001/11085 T Th 11:40am - 12:55pm
834 Seeley W. Mudd Building
Karl Sigman 4.5 33/40
IEOR 6711 R01/19239 F 3:00pm - 4:00pm
Room TBA
4.5 0/0

IEOR E6712 Stochastic models, II. 4.5 points.

Prerequisites: (IEOR E6711) or Refer to course syllabus.

Continuation of IEOR E6711 covering further topics in stochastic modeling in the context of queueing, reliability, manufacturing, insurance risk, financial engineering and other engineering applications. Topics from among generalized semi-Markov processes; processes with a non-discrete state space; point processes; stochastic comparisons; martingales; introduction to stochastic calculus.

Spring 2019: IEOR E6712
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 6712 001/13295 T Th 10:10am - 11:25am
303 Seeley W. Mudd Building
Antonius Dieker 4.5 0/40
IEOR 6712 R01/77745  
4.5 0/0

IEOR E8100 Advanced Topics In IEOR. 1-3 points.

Prerequisites: Faculty adviser's permission.

Selected topics of current research interest. May be taken more than once for credit. 

Fall 2018: IEOR E8100
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 8100 001/23047 M W 2:40pm - 3:55pm
644 Seeley W. Mudd Building
Ward Whitt 1-3 8/40
IEOR 8100 002/29408 M 10:10am - 12:40pm
825 Seeley W. Mudd Building
Clifford Stein 1-3 15/40
Spring 2019: IEOR E8100
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 8100 001/18047 W 1:10pm - 3:40pm
Room TBA
Xunyu Zhou 1-3 0/40
IEOR 8100 002/64819 M W 11:40am - 12:55pm
Room TBA
Daniel Bienstock 1-3 0/40
IEOR 8100 003/63887 M W 10:10am - 11:25am
Room TBA
Henry Lam 1-3 0/40
IEOR 8100 004/67629 T Th 11:40am - 12:55pm
Room TBA
Agostino Capponi 1-3 0/40
IEOR 8100 005/70493 M W 1:10pm - 2:25pm
Room TBA
Shipra Agrawal 1-3 0/40

IEOR E9101 Research. 1-6 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. This course may be repeated for credit.

Summer 2018: IEOR E9101
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 9101 001/77498  
Shipra Agrawal 1-6 0/20
IEOR 9101 002/78596  
Daniel Bienstock 1-6 0/20
IEOR 9101 003/82547  
Agostino Capponi 1-6 0/20
IEOR 9101 004/85896  
Emanuel Derman 1-6 0/20
IEOR 9101 005/87146  
Antonius Dieker 1-6 0/20
IEOR 9101 006/88347  
Adam Elmachtoub 1-6 0/20
IEOR 9101 007/91396  
Yuri Faenza 1-6 0/20
IEOR 9101 008/95846  
Donald Goldfarb 1-6 0/20
IEOR 9101 009/97447  
Vineet Goyal 1-6 0/20
IEOR 9101 010/98447  
Ali Hirsa 1-6 0/20
IEOR 9101 011/80029  
Ali Hirsa 1-6 0/20
IEOR 9101 012/85281  
Hardeep Johar 1-6 0/20
IEOR 9101 013/11646  
Soulaymane Kachani 1-6 0/20
IEOR 9101 014/17846  
Daniel Lacker 1-6 0/20
IEOR 9101 015/20896  
Henry Lam 1-6 0/20
IEOR 9101 016/21946  
Dylan Possamai 1-6 0/20
IEOR 9101 017/23398  
Jay Sethuraman 1-6 0/20
IEOR 9101 018/27246  
Karl Sigman 1-6 0/20
IEOR 9101 019/28246  
Clifford Stein 1-6 0/20
IEOR 9101 020/29529  
Van Anh Truong 1-6 0/20
IEOR 9101 021/25942  
Ward Whitt 1-6 0/20
IEOR 9101 022/88941  
David Yao 1-6 0/20
IEOR 9101 023/64279  
Xunyu Zhou 1-6 0/20
IEOR 9101 024/80779  
Jenny Mak 1-6 0/20
Fall 2018: IEOR E9101
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 9101 001/70726  
Shipra Agrawal 1-6 0/20
IEOR 9101 002/68963  
Daniel Bienstock 1-6 1/20
IEOR 9101 003/64865  
Agostino Capponi 1-6 1/20
IEOR 9101 004/12394  
Emanuel Derman 1-6 0/20
IEOR 9101 005/23237  
Antonius Dieker 1-6 0/20
IEOR 9101 006/70525  
Adam Elmachtoub 1-6 4/20
IEOR 9101 007/75700  
Yuri Faenza 1-6 0/20
IEOR 9101 008/75696  
Donald Goldfarb 1-6 2/20
IEOR 9101 009/16041  
Vineet Goyal 1-6 1/20
IEOR 9101 010/29298  
Ali Hirsa 1-6 0/20
IEOR 9101 011/12391  
Garud Iyengar 1-6 1/20
IEOR 9101 012/72657  
Hardeep Johar 1-6 0/20
IEOR 9101 013/66299  
Soulaymane Kachani 1-6 0/20
IEOR 9101 014/29500  
Daniel Lacker 1-6 1/20
IEOR 9101 015/21787  
Henry Lam 1-6 3/20
IEOR 9101 016/76256  
Dylan Possamai 1-6 0/20
IEOR 9101 017/18436  
Jay Sethuraman 1-6 0/20
IEOR 9101 018/71179  
Karl Sigman 1-6 0/20
IEOR 9101 019/22772  
Clifford Stein 1-6 3/20
IEOR 9101 020/75207  
Van Anh Truong 1-6 1/20
IEOR 9101 021/15692  
Ward Whitt 1-6 0/20
IEOR 9101 022/23120  
David Yao 1-6 1/20
IEOR 9101 023/68560  
Xunyu Zhou 1-6 0/20
IEOR 9101 024/63069  
Jenny Mak 1-6 0/20
Spring 2019: IEOR E9101
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEOR 9101 001/66740  
Shipra Agrawal 1-6 0/10
IEOR 9101 002/13224  
Daniel Bienstock 1-6 0/10
IEOR 9101 003/61010  
Agostino Capponi 1-6 0/10
IEOR 9101 004/73935  
Emanuel Derman 1-6 0/10
IEOR 9101 005/20428  
Antonius Dieker 1-6 0/10
IEOR 9101 006/68351  
Adam Elmachtoub 1-6 0/10
IEOR 9101 007/73554  
Yuri Faenza 1-6 0/10
IEOR 9101 008/24616  
Donald Goldfarb 1-6 0/10
IEOR 9101 009/16151  
Vineet Goyal 1-6 0/10
IEOR 9101 010/25826  
Ali Hirsa 1-6 0/10
IEOR 9101 011/22802  
Garud Iyengar 1-6 0/10
IEOR 9101 012/28489  
Hardeep Johar 1-6 0/10
IEOR 9101 013/22762  
Soulaymane Kachani 1-6 0/10
IEOR 9101 014/73679  
Daniel Lacker 1-6 0/10
IEOR 9101 015/72149  
Henry Lam 1-6 0/10
IEOR 9101 016/22110  
Dylan Possamai 1-6 0/10
IEOR 9101 017/64635  
Jay Sethuraman 1-6 0/10
IEOR 9101 018/65692  
Karl Sigman 1-6 0/10
IEOR 9101 019/18935  
Clifford Stein 1-6 0/10
IEOR 9101 020/68473  
Van Anh Truong 1-6 0/10
IEOR 9101 021/64494  
Ward Whitt 1-6 0/10
IEOR 9101 022/13111  
Yi Zhang 1-6 0/10
IEOR 9101 023/60070  
David Yao 1-6 0/10
IEOR 9101 024/75063  
Xunyu Zhou 1-6 0/10
IEOR 9101 025/61284  
Jenny Mak 1-6 0/10

CSOR E4010 Graph Theory: A Combinatorial View. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

Prerequisites: Linear Algebra, or instructor's permission.

Graph Theory is an important part of the theoretical basis of operations research. A good understanding of the basic fundamentals of graph theory is necessary in order to apply the theory successfully in the future. This is an introductory course in graph theory with emphasis on its combinatorial aspects. It covers basic definitions, and some fundamental concepts in graph theory and its applications. Topics include trees and forests graph coloring, connectivity, matching theory and others. This course will provide a solid foundation for students in the IEOR department, on which further courses may build.

CSOR W4231 Analysis of Algorithms I. 3 points.

Lect: 3.

Prerequisites: (COMS W3134 or COMS W3136COMS 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.

Summer 2018: CSOR W4231
Course Number Section/Call Number Times/Location Instructor Points Enrollment
CSOR 4231 V02/25780 T Th 1:00pm - 4:10pm
524 Seeley W. Mudd Building
Eleni Drinea 3 9
Fall 2018: CSOR W4231
Course Number Section/Call Number Times/Location Instructor Points Enrollment
CSOR 4231 001/15660 T Th 10:10am - 11:25am
451 Computer Science Bldg
Mihalis Yannakakis 3 105/110
CSOR 4231 002/24316 T Th 11:40am - 12:55pm
451 Computer Science Bldg
Mihalis Yannakakis 3 104/110
CSOR 4231 H02/11530  
Mihalis Yannakakis 3 46/50
CSOR 4231 V02/66918 T Th 11:40am - 12:55pm
451 Computer Science Bldg
Mihalis Yannakakis 3 10
Spring 2019: CSOR W4231
Course Number Section/Call Number Times/Location Instructor Points Enrollment
CSOR 4231 002/70835 T Th 1:10pm - 2:25pm
Room TBA
Eleni Drinea 3 1/120
CSOR 4231 003/18737 M W 10:10am - 11:25am
Room TBA
Christos Papadimitriou 3 0/110

COSA E9800 Data Science Doctoral Seminar. 1 point.

Not offered during 2018-19 academic year.

The Data Science Doctoral Seminar is a 1-credit course that meets weekly. The purpose is to expose the doctoral students to a breadth of ideas in data science across disciplinary domains. The syllabus combines guest lectures from academic data scientists in the greater NYC area and faculty at Columbia, along with a selection of related readings chosen by the guest lecturers. As part of this seminar, students will be expected to engage in active open discussion about the topics and readings covered in class, as well as discuss how such topics apply to their own respective research areas.

IEME E4200 Human Centered Design. 1 point.

Lect: 4.5.Not offered during 2018-19 academic year.

Prerequisites: By application and instructor approval.

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 2019: IEME E4200
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEME 4200 001/73782 F 9:00am - 2:30pm
Room TBA
Harry West, Turi McKinley 1 0/45

IEME E4310 The Manufacturing Enterprise. 3 points.

Lect: 3.

The strategies and technologies of global manufacturing and service enterprises. Connections between the needs of a global enterprise, the technology and methodology needed for manufacturing and product development, and strategic planning as currently practiced in industry.  

Fall 2018: IEME E4310
Course Number Section/Call Number Times/Location Instructor Points Enrollment
IEME 4310 001/70776 W 10:10am - 12:40pm
545 Seeley W. Mudd Building
Sheldon Weinig 3 19/60
IEME 4310 V01/76211 W 10:10am - 12:40pm
545 Seeley W. Mudd Building
Sheldon Weinig 3 4

MEIE E4810 Introduction to Human Spaceflight. 0 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 2019: MEIE E4810
Course Number Section/Call Number Times/Location Instructor Points Enrollment
MEIE 4810 001/61573 W 4:10pm - 6:40pm
Room TBA
Michael Massimino 0 0/40

MSIE W6408 Inventory Theory. 3 points.

Lect: 3.Not offered during 2018-19 academic year.

Prerequisites: Probability theory, dynamic programming.

Construction and analysis of mathematical models used in the design and analysis of inventory systems. Deterministic and stochastic demands and lead times. Optimality of (s, S) policies. Multiproduct and multiechelon systems. Computational methods.