Columbia University
Industrial Engineering and Operations Research
New York, New York
Overview
Columbia University was established as King's College in 1754. Today it consists of sixteen schools and faculties and is one of the leading universities in the world. The University draws students from many countries. The high caliber of the students and faculty members makes it an intellectually stimulating place to be. Columbia University is located on Morningside Heights, close to Lincoln Center for the Performing Arts, Greenwich Village, Central Park, and midtown Manhattan.
In 2005-06, enrollment in the Department of Industrial Engineering and Operations Research totaled 379 students and included 171 undergraduates (juniors and seniors), 157 Master of Science degree candidates, and 51 doctoral candidates. The student population has a diverse and international character; 47 percent of those enrolled are women.
The Location and Community
New York City is the intellectual, artistic, cultural, gastronomic, corporate, financial, and media center of the United States and perhaps of the world. The city is renowned for its theaters, museums, libraries, restaurants, opera, and music. Inexpensive student tickets for cultural and sports events are frequently available, and the museums are open to students at very modest cost or are free. The ethnic variety of the city adds to its appeal. The city is bordered by uncongested areas of great beauty that provide varied types of recreation, such as hiking, camping, skiing, and ocean and lake swimming. There are superb beaches on Long Island and in New Jersey, while to the north lie the Catskill, Green, Berkshire, and Adirondack mountains. Close at hand is the beautiful Hudson River valley.
The proximity of many local industries provides strong student-industry contact and excellent job opportunities. Adjunct faculty members from industry provide courses in areas of current professional interest.
Programs of Study and Degree Requirements
The Department of Industrial Engineering and Operations Research offers Master of Science (M.S.) programs in industrial engineering, operations research, and financial engineering. Graduate programs leading to a Doctor of Philosophy (Ph.D.) or Doctor of Engineering Science (Eng.Sc.D.) in industrial engineering or operations research, as well as one leading to the professional degree in industrial engineering, are also available. Combined M.S./M.B.A. programs are offered in conjunction with Columbia's Graduate School of Business.
The Master of Science degree can be completed within one academic year of full-time classwork or longer if the student chooses to study part-time. Registration as a nondegree candidate (special student) is also possible. Required courses for the industrial engineering program include production management, operations research, deterministic models, and probability and statistics. Required courses for the operations research program include probability, statistical inference, deterministic models, simulation, and stochastic models. Individual programs are designed in consultation with a faculty adviser, and a number of concentrations are available. The joint M.S./M.B.A. can be obtained after five terms of full-time study.
The Ph.D. program is geared toward the exceptional student. The first year is used to prepare for the Ph.D. examinations, which requires advanced course work in probability theory and mathematical programming. In addition to advanced electives, each student must take mathematical analysis, statistical inference, and simulation, unless equivalent courses were taken prior to admittance. Thereafter, the focus is on research designed to prepare students for research and teaching careers.
Facilities & Resources
The department's PC computer laboratory contains networked, state-of-the-art machines with supporting software and printers. Networked PCs are available in all teaching and graduate assistant offices. In addition, Columbia University's Academic Information Systems (AcIS) supports the academic computing and data communications needs of the University. The Columbia University library system is among the nation's ten largest academic libraries and maintains an excellent collection in industrial engineering and operations research and related disciplines.
Expenses and Aid
The cost of study is approximately $1,510 per credit. Annual fees were approximately $1225, and the cost of books was approximately $800.
Financial Aid:
Financial support for Ph.D. students is awarded on a competitive basis in the form of assistantships that provide a stipend and a tuition allowance that covers a full 15-point program each semester.
Housing/Living Expenses:
The University provides limited housing for graduate students who are registered either for an approved program of full-time academic study or for doctoral dissertation research. University residence halls include traditional dormitory facilities as well as suites and apartments for single and married students; furnishings and utilities may be included. An estimated minimum of $14,500 should be allowed for board, room, and personal expenses for the academic year. Rooms are also available at International House; these cost from $870 to $1150 per month. University Real Estate properties include apartments owned and managed by the University in the immediate vicinity of the Morningside Heights campus. These are leased yearly, as they become available, to single and married students at rates that reflect the size and location of each apartment as well as whether furnishings or utilities are included. Requests for additional information and application forms should be directed to the Assignments Office, 111 Wallach Hall.
How to Apply / Application
For maximum consideration for admission, doctoral students should submit the following before December 15 for the fall term: an official application, transcripts, recommendations, and a $55 application fee. The deadline for application to the Master of Science in industrial engineering or operations research is January 5 for the fall term if the student wants to be considered for financial aid; otherwise, the deadline is February 15. The deadline for the Master of Science in financial engineering program is January 5 for the summer term. The deadline for the spring term is October 1, but the Master of Science in financial engineering does not have spring term enrollment.
The General Test of the Graduate Record Examinations (GRE) is required for all graduate students; scores must be received prior to the deadline. Prospective students for the joint M.S./M.B.A. program must submit separate applications to the School of Engineering and Applied Science and the Graduate School of Business. For more information about admissions, students should visit http://www.engineering.columbia.edu/admissions/grad/programs.
Who to Contact
Admissions Committee
Department of Industrial Engineering and Operations Research
313 Seeley W. Mudd Building
Columbia University
New York, New York 10027
212-854-2941
E-mail: info@ieor.columbia.edu
Faculty and Research
Department of Industrial Engineering and Operations Research
• Daniel Bienstock, Ph.D. Combinatorial optimization and integer programming, parallel computing, applications to telecommunications.
• Edward Coffman, Ph.D. (Electrical Engineering Department). Modeling and performance analysis of computer and communication systems (Internet), analysis of algorithms.
• Awi Federgruen, Ph.D. (Graduate School of Business). Modeling of stochastic systems, physical distribution management, dynamic programming.
• Guillermo Gallego, Ph.D. Inventory control, revenue optimization, supply-chain management, scheduling, semiconductor manufacturing.
• Paul Glasserman, Ph.D. (Graduate School of Business). Stochastic systems, Monte Carlo simulation, mathematical and computational finance.
• Donald Goldfarb, Ph.D. Algorithms for linear, quadratic, and conic programming; network flows; robust optimization; portfolio optimization; large sparse systems.
• Martin Haugh, Ph.D. Financial engineering, computational finance.
• Chris Heyde, Ph.D. (Department of Statistics). Stochastic modeling, applied probability, asymptotic theory, inference for stochastic processes.
• Garud Iyengar, Ph.D. Convex optimization, mathematical and computational finance, information theory, signal processing.
• Soulaymane Kachani, Ph.D. Pricing and revenue management, transportation science, mathematical optimization.
• Ioannis Karatzas, Ph.D. (Department of Mathematics). Stochastic differential equations, finance applications.
• Steven Kou, Ph.D. Mathematical and computational finance, simulation, queuing theory, mathematical statistics.
• Jay Sethuraman, Ph.D. Queueing networks, deterministic and stochastic scheduling, discrete optimization.
• Perwez Shahabuddin, Ph.D. Simulation, stochastic systems, fast simulation techniques, applications to communication systems.
• Karl Sigman, Ph.D. Queuing theory, queuing networks, applied stochastic processes, point processes.
• Clifford Stein, Ph.D. Analysis of algorithms, combinatorial optimization, scheduling, network algorithms, computational biology.
• Ward O. Whitt, Ph.D. Queueing theory, performance analysis, stochastic modeling of telecommunication systems, numerical transform inversion.
• David Yao, Ph.D. Optimization and control of discrete event stochastic systems, queuing networks, manufacturing systems.
Associated Faculty in the Graduate School of Business
• Mark Broadie, Ph.D. Computational finance, security pricing.
• Sidney Browne, Ph.D. Stochastic systems, queuing.
• Fangruo Chen, Ph.D. Supply-chain management, negotiation.
• Linda Green, Ph.D. Stochastic systems, queuing, applications to service and production systems.
• Costis Maglaras, Ph.D. Stochastic modeling, operations management, revenue management.
• Garrett van Ryzin, Ph.D. Stochastic optimization, pricing and revenue management, supply-chain management.
Associated Faculty in the Department of Statistics
• Victor de la Pena, Ph.D. Martingales, stopping times, sequential analysis, U-statistics.
Adjunct Faculty
• Kosrow Dehnad, Ph.D. Forecasting and finance.
• Brian Eck, Ph.D. Quality control and management.
• Leon Gold, Ph.D. Human factors.
• Hanan Luss, Ph.D. Facilities layout and planning.
• George Mihalia, Ph.D. Database design.
• Peter Norden, Ph.D. Organization theory.
• Lucius Riccio, Ph.D. Operations research models in the public sector.
• Paul Shapiro, Ph.D. Industrial information systems.
• Sheldon Weinig, Ph.D. Technology and policy issues in manufacturing enterprises.
• Philip Wolfe, Ph.D. Mathematical programming.
CURRENT AREAS OF RESEARCH
• In industrial engineering, research is conducted in the design and control of manufacturing and service systems, including supply-chain management, inventory control, yield management, scheduling, and logistics. In operations research, new developments in mathematical programming, combinatorial optimization, queuing, reliability, simulation, mathematical and computational finance, and in both deterministic and stochastic network flows are being explored. In financial engineering, research is being carried out in portfolio management; option pricing; computational finance, such as Monte Carlo simulation and numerical methods; and data mining.
• Projects are sponsored and supported by leading private firms and government agencies. In addition, students and faculty members are involved in the work of two NSF-funded research and educational centers: the Center for Applied Probability (CAP) and the Computational and Optimization Research Center (CORC). Both of these centers are principally supported by major grants from the National Science Foundation.
• CAP is a cooperative center involving the School of Engineering and Applied Science, several departments in the Graduate School of Arts and Sciences, and the Graduate School of Business. Its main interests are in four applied areas: mathematical and computational finance, stochastic networks, logistics and distribution, and population dynamics. The center maintains a laboratory of workstations for exclusive use by graduate students. CORC is a center involving the IBM-Watson Research Center, Cornell University, the School of Engineering and Applied Science, the Graduate School of Arts and Sciences, and the Graduate School of Business. Its mission is the development of new theory and tools for the solution of computationally intensive optimization problems. It has its own parallel computer and workstations for graduate students and faculty members.