Cornell University Registrar

Program Description

Operations Research and Information Engineering (ORIE) is the field of developing, evaluating, and applying tools for analyzing data to make better decisions. The field draws expertise from theoretical and applied mathematics, probability and statistics, data science, computer science, machine learning and artificial intelligence, systems engineering, and others. Example tools include mathematical models that optimize performance or cost, process simulations that identify complex relationships between system elements, and machine learning algorithms that help unlock the secrets hidden in troves of data.

The ORIE M.Eng. is a full-time, in-person professional degree that stresses applications to real-world challenges. Every sector of the economy – from healthcare to energy to finance to government – draws upon the skills of our graduates to improve effectiveness and efficiency. ORIE employers need descriptive analytics that help them understand the status quo, prescriptive analytics to inform current decisions, and predictive analytics to help prepare for the future.

The ORIE M.Eng. program serves two groups of students:  undergraduate majors in operations research who wish to deepen their practical knowledge of the field, and qualified undergraduates from other quantitative fields who want to complement their technical backgrounds with a solid foundation in ORIE. For admission, all entering students must have completed courses in differential, integral, and multivariate calculus, linear algebra, a calculus-based course in probability and statistics, and an intermediate-level computer programming course. Students interested in data analytics or financial engineering must have a second probability/statistics course. Students interested in financial engineering should also have courses in stochastic processes and finance, and must complete a pre-semester “FE Intensive” refresher of probability/statistics skills.

All ORIE M.Eng. students study core course content in optimization, stochastics, and data science and statistical modeling. Then the program offers six concentrations that assist students in designing their academic program from courses within ORIE and other Cornell fields. Concentrations include applied operations research, data analytics, financial engineering, information technology, manufacturing and industrial engineering, and strategic operations.

All concentrations except for financial engineering typically can be completed in two semesters. Depending on the student’s preparation, an additional summer or semester may be needed. Graduating Cornellians may qualify for an “early-admit program” that allows completion in one M.Eng. semester. The financial engineering concentration spans three semesters, allowing for a summer internship and culminating in an immersive third semester in New York City at ORIE’s satellite campus, Cornell Financial Engineering Manhattan (CFEM), where students apply their skills in a hands-on, industry-integrated environment.

The program capstone is a team-based project. ORIE projects entail real projects, working with real organizations (for-profits, non-profits, and governments), using real data. Students experience the application of ORIE tools while gaining valuable professional skills such as project planning, teamwork, and verbal and written communications.

Program Information 

• Program Mode of Delivery: In Person

• Program Location: Ithaca, NY
• Minimum Credits for Degree: 30

Program Requirements

In addition to meeting University and College requirements, all ORIE M.Eng. students must meet core course requirements in optimization, stochastics, and data science and statistical modeling. To aid in professional development, students also complete a career practicum, a project preparation course, a course in engineering economics, and a colloquium.  

The program builds on the core with six concentrations that assist students in designing their academic program. Concentrations include applied operations research, data analytics, financial engineering, information technology, manufacturing and industrial engineering, and strategic operations. Typically, each concentration includes a set of required courses, plus a menu of concentration electives from which students may choose. Drawing on the breadth of Cornell, many students elect to take courses not only from ORIE, but also from Computer Science, Statistical Science, Systems Engineering, Electrical and Computer Engineering, and other fields.

All ORIE M.Eng. students must complete a five-credit capstone project. Financial engineering concentrators complete their project during their third semester while at Cornell Financial Engineering Manhattan, while all other students complete their project in the Spring semester. Common elements in all projects include working on a team of students on an engineering design problem, meeting with a faculty advisor and project partner organization on a regular basis, and presenting the final results to the project partner. ORIE M.Eng. projects have real-world client sponsors and address relevant, practical problems.

Cornell Tech in New York City also offers a Master in Operations Research and Information Engineering. This program is entirely separate from Cornell Ithaca’s M.Eng program. The financial engineering concentration is only offered by the Ithaca program, and the credits earned while in “early-admit” status may not count towards the M.Eng. degree at Cornell Tech.

Required Classes

Course List

Code	Title	Hours
Required Classes
ORIE 5915	MEng Career Practicum	1
ORIE 5110	Engineering Economics and Strategic Decision-Making 1	1
ORIE 5980	ORIE Master of Engineering Project 1	1
ORIE 5981	ORIE Master of Engineering Project 1, 3	4-5
ORIE 5220	Applied Financial Engineering (in NYC) 2	5
Total Hours		12-13

Core Coursework 

Course List

Code	Title	Hours
Core Coursework
Students must take 12 credits of Core coursework. 3 credits must be taken in each Core Area. 8 credits must be from ORIE Department courses.
Core Area: Optimization Modeling		3
Select at least 3 credits of the following:
CS 5223	Numerical Analysis: Linear and Nonlinear Problems	4
ECE 5280	Optimal System Analysis and Design	4
ORIE 5126	Principles of Supply Chain Management	4
ORIE 5300	Optimization I	4
ORIE 5310	Optimization II	4
ORIE 5340	Applications of Optimization: Modeling and Computation	4
ORIE 5370	Optimization Modeling in Finance	3
ORIE 5570	Reinforcement Learning with Operations Research Applications	3
SYSEN 5680	Optimal Control and Decision Theory	3
SYSEN 6800	Computational Optimization	4
Core Area: Stochastic Modeling		3
Select at least 3 credits of the following:
ECE 5110	Random Signals in Communications and Signal Processing	3-4
ORIE 5126	Principles of Supply Chain Management	4
ORIE 5130	Service System Modeling and Design	4
ORIE 5500	Eng Probability and Statistics: Modeling and Data Science II	4
ORIE 5510	Introduction to Engineering Stochastic Processes I	4
ORIE 5570	Reinforcement Learning with Operations Research Applications	3
ORIE 5580	Simulation Modeling and Analysis	4
ORIE 5581	Monte Carlo Simulation	2
ORIE 5582	Monte Carlo Methods in Financial Engineering	2
ORIE 5600	Financial Engineering with Stochastic Calculus I	4
ORIE 5610	Financial Engineering with Stochastic Calculus II	4
ORIE 5630	Operations Research Tools for Financial Engineering	4
ORIE 5650	Quantitative Methods of Financial Risk Management	3
Core Area: Data Science and Statistical Modeling		3
Select at least 3 credits of the following:
CS 5700	Foundations of AI Reasoning and Decision-Making	3
CS 5780	Introduction to Machine Learning	4
CS 5782	Introduction to Deep Learning	4
CS 5789	Introduction to Reinforcement Learning	3
ECE 5200	Foundations Machine Learning	4
ORIE 5550	Applied Time Series Analysis	4
ORIE 5630	Operations Research Tools for Financial Engineering	4
ORIE 5640	Statistics for Financial Engineering	4
ORIE 5741	Learning with Big Messy Data	4
ORIE 5742	Info Theory, Probabilistic Modeling, and Deep Learning with Scientific and Financial Apps	3
STSCI 5030	Linear Models with Matrices	4
STSCI 5090	Theory of Statistics	4
STSCI 5740	Data Mining and Machine Learning	4
SYSEN 6888	Deep Learning	4

Concentration Coursework

Concentration: Applied Operations Research

Course List

Code	Title	Hours
Applied Operations Research
At least 12 credit hours of approved ORIE Department graded coursework. These classes may also count towards your Core requirements.

Concentration: Data Analytics

Course List

Code	Title	Hours
Data Analytics
At least 9 credit hours distributed in at least 3 classes. At least 1 of these classes must come from the Data Science and Statistical Modeling Core Area. At least 1 must come from the Data Analytics Elective List. The remaining class can come from either of those two lists.
Data Analytics Elective List
CS 5320	Introduction to Database Systems	3
CS 5740	Natural Language Processing	3-4
CS 5777	Principles of Large-Scale Machine Learning Systems	4
CS 6241	Numerical Methods for Data Science	3
CS 6386	Data to Decisions: Principles of Efficient Data Science	4
HADM 6050	Revenue Management	3
INFO 5556	Business Intelligence Systems	4
NBA 6200	Marketing Research	3
NBA 6390	Data Driven Marketing	1.5
ORIE 5100	Manufacturing Systems Design: A Consulting Boot Camp	4
ORIE 5160	Topics in Data Science and OR	3
ORIE 5270	Big Data Technologies	2
ORIE 5570	Reinforcement Learning with Operations Research Applications	3
ORIE 5580	Simulation Modeling and Analysis	4
ORIE 5581	Monte Carlo Simulation	2
ORIE 5582	Monte Carlo Methods in Financial Engineering	2
ORIE 5820	Data-Driven Decision Modeling and Analysis	3
STSCI 5045	Python Programming and its Applications in Statistics	4
STSCI 5065	Big Data Management and Analysis	3
STSCI 5160	Categorical Data	3
STSCI 5520	Statistical Computing	4

Concentration: Financial Engineering

Course List

Code	Title	Hours
Financial Engineering
At least 12 credits, 6 of which must be taken while in Manhattan at CFEM.
AEM 5230	Behavioral Finance	3
AEM 5280	Valuation of Capital Investment	3
HADM 6285	Derivatives: Forwards, Futures, Swaps, and Options	3
NBA 5060	Financial Statement Analysis	1.5
NBA 5090	Advanced Financial Statement Analysis	1.5
NBA 5220	Equity Investment Research and Analysis	3
NBA 5420	Investment and Portfolio Management	3
NBA 5430	Financial Markets and Institutions	3
NBA 5540	International Finance	3
NBA 5550	Fixed Income Securities and Interest Rate Options	3
NBA 5980	Behavioral Finance	1.5
NBA 6060	Evaluating Capital Investment Projects	1.5
NBA 6560	Valuation Principles	1.5
NBA 6730	Derivatives Securities Part I	1.5
NBA 6740	Derivatives Securities Part II	1.5
ORIE 5240	Bond Mathematics and Mortgage-Backed Securities	2
ORIE 5252	Special Topics in Financial Engineering	2
ORIE 5253	Special Topics in Financial Engineering II	2
ORIE 5254	Special Topics in Financial Engineering III	2
ORIE 5255	Special Topics in Financial Engineering IV	2
ORIE 5256	Special Topics in Financial Engineering V	2
ORIE 5257	Special Topics in Financial Engineering VI	2
ORIE 5258	Python for Finance	1.5
ORIE 5259	Market Microstructure and Algorithmic Trading: Theory and Practice	1.5
ORIE 5260	Special Topics in Quantitative Finance	2
ORIE 5610	Financial Engineering with Stochastic Calculus II	4
ORIE 5650	Quantitative Methods of Financial Risk Management	3

Concentration: Information Technology

Course List

Code	Title	Hours
Information Technology
Complete at least 4 concentration-specific courses, one from each of the following categories: Technology and Infrastructure, Information Economics and Strategy, and Managing Implementation. The remaining course may come from any of those areas, or the Additional IT Electives List. At most 1 class may be used to satisfy both an Elective and a Core requirement.
Technology and Infrastructure Electives List
Select at least one of the following:
CS 5320	Introduction to Database Systems	3
CS 5414	Distributed Computing Principles	4
CS 5430	System Security	4
CS 5456	Introduction to Computer Networks	3
ECE 5660	Computer Networks and Telecommunications	3
ECE 5740	Computer Architecture	4
ORIE 5142	Systems Analysis Behavior and Optimization	3
SYSEN 5400	Theory and Practice of Systems Architecture	3
SYSEN 5420	Network Systems and Games	3
Information, Economics, and Strategy Electives List
Select at least one of the following:
ENMGT 5940	Economics and Finance for Engineering Management	4
INFO 5140	Law, Policy, and Politics of Cybersecurity	3
INFO 5355	Human Computer Interaction Design	3
INFO 6220	Networks II: Market Design	3
SYSEN 5140	Economic and Financial Decisions for Engineers	3
SYSEN 5350	Multidisciplinary Design Optimization	4
Managing IT Implementation Electives List
Select at least one of the following:
CS 5150	Software Engineering	4
CS 5154	Software Testing	3
ECE 5830
ENMGT 5900	Project Management	4
INFO 5125	Project Management	3
ORIE 5140	Model Based Systems Engineering	4
SYSEN 5260	Software Systems Engineering: Design, Develop, and Deliver Software in the Modern Enterprise	3
SYSEN 5300	Systems Engineering and Six Sigma for the Design and Operation of Reliable Systems	3-4
SYSEN 5930	Project Management and Leadership for Complex Systems	4
Additional IT Electives List
CS 5410	Operating Systems	3
CS 5700	Foundations of AI Reasoning and Decision-Making	3
CS 5780	Introduction to Machine Learning	4
ORIE 5126	Principles of Supply Chain Management	4
ORIE 5130	Service System Modeling and Design	4
ORIE 5820	Data-Driven Decision Modeling and Analysis	3

Concentration: Manufacturing and Industrial Engineering

Course List

Code	Title	Hours
Mandatory Coursework
ORIE 5920	Enterprise Engineering Colloquium	1
ORIE 5100	Manufacturing Systems Design: A Consulting Boot Camp	4
Select one of the following:
NBA 5020	Managerial Accounting and Reporting I: Fundamentals of Cost Analysis
NBA 5530	Accounting and Financial Decision Making
Electives
Select at least 9 credits of the following:
ORIE 5126	Principles of Supply Chain Management	4
ORIE 5130	Service System Modeling and Design	4
ORIE 5140	Model Based Systems Engineering	4
ORIE 5340	Applications of Optimization: Modeling and Computation	4
ENMGT 5900	Project Management	4
MAE 5210	Dimensional Tolerancing in Mechanical Design	1
MAE 5240	Materials Processing and Manufacturing	3
MAE 5250	Computer-Aided Manufacture	1
MAE 5260	Design for Manufacture and Assembly	1
MAE 5270	Design Failure Modes and Effects Analysis (DFMEA)	1
NBA 6100	Applied Operations Strategy	1.5
SYSEN 5300	Systems Engineering and Six Sigma for the Design and Operation of Reliable Systems	3-4
At most one of the following:
ECE 5830
SYSEN 5930	Project Management and Leadership for Complex Systems
At most one of the following:
ENMGT 5940	Economics and Finance for Engineering Management
SYSEN 5140	Economic and Financial Decisions for Engineers

Concentration: Strategic Operations

Course List

Code	Title	Hours
Mandatory Coursework
ORIE 5100	Manufacturing Systems Design: A Consulting Boot Camp	4
ORIE 5126	Principles of Supply Chain Management	4
ORIE 5130	Service System Modeling and Design	4
NBA 6515	Experience in Strategic Operations	3
Elective Coursework
Select at least three credits of the following:
NBA 5020	Managerial Accounting and Reporting I: Fundamentals of Cost Analysis	1.5
NBA 5330	Management Cases	1.5
NBA 5530	Accounting and Financial Decision Making	3
NBA 5580	Corporate Financial Policy	1.5
NBA 6070	Designing and Building AI Solutions	1.5
NBA 6100	Applied Operations Strategy	1.5
NBA 6560	Valuation Principles	1.5
NCC 5080	Managing Operations	2.5
NCC 5580	Managing Operations	1.5-3
ORIE 5100	Manufacturing Systems Design: A Consulting Boot Camp	4
ORIE 5130	Service System Modeling and Design	4

¹

Operations Engineering Concentrations only (Applied Operations Research, Data Analytics, Information Technology, Manufacturing and Industrial Engineering, and Strategic Operations)

²

Financial Engineering Concentration only.

³

Students unable to take ORIE 5980 in the Fall must take ORIE 5981 for 5 credits; all other students must take it for 4 credits.

University Graduation Requirements

Requirements for All Students

In order to receive a Cornell degree, a student must satisfy academic and non-academic requirements.

Academic Requirements

A student’s college determines degree requirements such as residency, number of credits, distribution of credits, and grade averages. It is the student’s responsibility to be aware of the specific major, degree, distribution, college, and graduation requirements for completing their chosen program of study. See the individual requirements listed by each college or school or contact the college registrar’s office for more information.

Non-academic Requirements

Conduct Matters. Students must satisfy any outstanding sanctions, penalties or remedies imposed or agreed to under the Student Code of Conduct (Code) or Policy 6.4. Where a formal complaint under the Code or Policy 6.4 is pending, the University will withhold awarding a degree otherwise earned until the adjudication process set forth in those procedures is complete, including the satisfaction of any sanctions, penalties or remedies imposed.

Financial Obligations. Outstanding financial obligations will not impact the awarding of a degree otherwise earned or a student’s ability to access their official transcript. However, the University may withhold issuing a diploma until any outstanding financial obligations owing to the University are satisfied.

Graduation Requirements for Master of Engineering Degree (M.Eng.) Programs

Requirements

The following are general requirements for graduation that apply to all Master of Engineering degrees offered on the Ithaca campus. The individual program pages provide additional information about discipline-specific requirements.

Credits and Residency Units

• Satisfactory completion of 30 technical credits, of which:
  • At least 21 credits must be earned at Cornell. (Some M.Eng. programs allow up to 9 transfer credits of letter-graded coursework completed outside of Cornell to be applied to the M.Eng. degree.)
  • At least 12 credit hours must be in coursework from the home M.Eng. program (as determined by the program).
  • A maximum of two credit hours graded on an S/U basis may be included.
• The credit hours of any course in which a student receives a grade below C- will not count toward the Master of Engineering degree.
• Students must maintain a course load of at least 12 credit-bearing hours¹ each semester.
• Students may not enroll in more than 20 credit-bearing hours per semester.
• Students must complete two full-time residency units¹ (semesters) as registered M.Eng. students. Winter and summer sessions do not count as residency units.

¹

Course load and residency unit exceptions apply for Distance Learning program students, employee degree program students, and Industrial Partnership Program students. The residency unit requirement is one full-time registered semester for Early Admit M.Eng. students and certain Cornell MPS/MS/PhD student transfers.

Courses

• Only program-approved courses at the 5000 level and above may count toward the M.Eng. degree.
• Courses covering subject matter previously taken at Cornell may not be repeated for credit.
• Satisfactory completion of an engineering design project bearing 3 or more credit hours and including a formal written report.

Other Requirements

• A grade-point average of 2.50 or above is required across all Cornell courses which count for credit towards the M.Eng. degree.
• Students must complete all degree requirements within four calendar years of their first enrollment in the M.Eng. program (six years for distance learning students), inclusive of any leaves of absence.
• Students must complete the M.Eng. Exit Survey prior to graduation.

Learning Outcomes

• Mastery and Application of Core Disciplinary Knowledge
• Problem Formulation and Organization and Planning of the Solution Process
• Collaborative Problem Solving and Issue Resolution
• Communication of Knowledge, Ideas, and Decision Justification
• Self-Directed Learning and Professional Development

Admissions

Application Requirements and Deadlines

Application Deadlines

Fall, December 1 (of preceding year); Spring, October 1 (for active Cornell Undergraduates only)

Requirements Summary

• Prerequisites dependent on concentration
  • All applicants
    • A standard engineering calculus sequence, including linear algebra (with eigenvalues and eigenvectors) and vector calculus.
    • An introductory engineering probability and statistics course.
    • An introductory computer programming course as well as an intermediate-level computer programming course in a general programming language such as C, C++, Java, or Python. Courses that entail programming applications, but where programming is not the primary focus are not acceptable substitutes. Courses in statistical modeling languages, such as SAS, are not acceptable substitutes.
  • Additional Prerequisites for the Data Analytics concentration
    • A two-semester sequence of calculus-based probability and statistics theory. Courses in which probability and statistical methods are used, but where theory is not the primary focus are not acceptable substitutes, nor are professional exam credentials (e.g., CFA, FRM).
  • Additional Prerequisites for the Financial Engineering concentration
    • A two-semester sequence of calculus-based probability and statistics theory. Courses in which probability and statistical methods are used, but where theory is not the primary focus are not acceptable substitutes, nor are professional exam credentials (e.g., CFA, FRM).
    • An introductory finance course, covering topics such as financial instruments, risk-return tradeoffs, and capital budgeting. Courses in economics and accounting are not acceptable substitutes.
    • Strongly Recommended: A course in differential equations.
    • Strongly Recommended: Proficiency with Python (preferred) or R.
• All Graduate School Requirements, including the English Language Proficiency Requirement
• Minimum two letters of recommendation, three preferred.
• Academic Statement of Purpose
• Personal Statement
• Resume or CV
• GRE (preferred) or GMAT scores
• Video Interview (asynchronous, sent shortly after the application deadline)

Admissions Contact Information

Name: Onnolee Wierson
Email: orie-meng@cornell.edu