Operations Research and Information Engineering
Ph.D. (Operations Research)
Doctoral students majoring in operations research concentrate in one of three areas:
Applied probability and statistics stresses the techniques and associated underlying theory of probability and statistics, particularly as applied to problems in science, finance, and engineering. The techniques emphasized are those associated with applied stochastic processes (for example, mathematical finance, queuing theory, traffic theory, and inventory theory) and statistics (including statistical decision theory, reliability theory, analysis of life data, and the statistical aspects of the design, analysis, and interpretation of experiments and of ranking and selection theory).
Manufacturing systems engineering is concerned with the analysis and design of complex manufacturing and distribution systems. Problems studied include the establishment of inventory-control policies in multistage production and distribution systems; design of manufacturing plants with optimal amounts of equipment and optimal materials-handling systems; planning and scheduling of production in large-scale, multi-item, multilocation systems; and economic analysis of engineering processes. Students use modern analytic and computer techniques in the design and analysis of such systems. Students are expected to understand the manufacturing processes associated with some type of industry. Research, which may involve development of new mathematical methodology, is often conducted directly with a cooperating company, for example, in automotive or semiconductor manufacturing.
Mathematical programming concentrates on optimization, including linear, nonlinear, integer, and combinatorial programming; network flows; problems of scheduling and sequencing; and discrete and computational geometry. Research ranges from the development and applications of computational algorithms (exact and approximate) to the associated studies of duality theory, convex and variational analysis, polyhedra, combinatorics, and graph theory.
Doctoral students also select two minor subjects for the Ph.D. degree, one of which must be outside the field. A minor may be in operations research or in a subject offered in another field, such as computer science, econometrics and economic statistics, environmental systems engineering, managerial economics, mathematics, or planning theory and systems analysis.
In addition to the examinations required by the Graduate School, the field requires a qualifying examination for Ph.D. degree candidates, normally taken in the third term of graduate study at Cornell.
For more information on the Ph.D. program, see: http://www.orie.cornell.edu/academics/doctor/index.cfm
M.Eng. (Operations Research and Information Engineering)
As a two- or three-semester professional degree program, the ORIE M.Eng. has become highly valued in the marketplace and continues to be an attractive option for well-prepared undergraduates in Operations Research, Industrial Engineering, Mathematics, Finance, and many other quantitative disciplines.
The main objectives of every MEng program at Cornell are to advance the breadth and depth of our students’ technical knowledge and to provide students with opportunities to synthesize and apply this knowledge in a real-world environment. In ORIE, the technical tools of primary importance are mathematical modeling and the application of quantitative techniques instilled within the fields of optimization, probability, stochastic processes, statistics, and simulation. The areas of application for these tools are virtually limitless, but ORIE students generally apply their knowledge to the design, operation, and improvement of business systems.
The capstone component of the ORIE M.Eng. program is the team-based engineering design project, which all students complete with the guidance of a Cornell faculty advisor. The MEng project is fundamentally and purposefully different from traditional coursework and the process of completing an individual Masters’ thesis. It is intended to prepare students for the professional arena by engaging them in client-sponsored project work with real data, deadlines, and deliverables. Regardless of their respective concentrations, students are expected to play major roles in all aspects of their projects, including formulating and analyzing the problem, managing the client relationship, monitoring the project timeline and milestones, and delivering the final results.
Six concentrations and one minor are currently associated with the MEng degree program in ORIE. Each is designed to meet certain educational objectives:
• Applied Operations Research Concentration (AOR)
• Data Analytics Concentration (DA)
• Financial Engineering Concentration (FE)
• Information Technology Concentration (IT)
• Manufacturing and Industrial Engineering Concentration (MIE)
• Strategic Operations Concentration (SO)
• Systems Engineering Minor
All of these concentrations and minors share a common set of base requirements, including a minimum number of course credit hours, core and distribution courses, and participation in an approved engineering design project. The specific courses that are required in order for a student to complete a particular concentration or minor may vary depending on his or her background.
Regardless of concentration, the ORIE M.Eng. program is designed to begin in the fall semester. For a variety of reasons, including the sequencing of offered courses and the timeline for project activities, completing the ORIE M.Eng. program in the traditional fall-spring or fall-spring-fall semester sequence is strongly encouraged. Although students are occasionally admitted to the ORIE M.Eng. program in the spring semester, spring admission is typically limited to applicants who are already at Cornell and have been able to participate in project start-up activities that take place during the fall semester.
For more information on the M.Eng. program, see: http://www.orie.cornell.edu/academics/master/index.cfm
Subject and Degrees
Concentrations by Subject
- applied probability and statistics
- manufacturing systems engineering
- mathematical programming
Operations Research and Information Engineering
- applied operations research
- data analytics
- financial engineering
- information technology
- manufacturing and industrial engineering
- strategic operations