Class 2019Princeton Preview

Presented by

Prof. Alain KornhauserDepartment Representative

For more info see orfe.princeton.edu

Why ORFE?• Study and work on challenging and

relevant problems.

• Learn and apply mathematical & computational skills to address interesting, useful and timely applications.

– These skills are recognized and rewarded in the marketplace by employers & top graduate schools.

– They will make you a better Leader.

Marketable Skills• Probability: Modeling & understanding of

uncertainty.

• Statistics: Quantifying uncertainty.

• Optimization: Modeling & understanding of the tradeoffs associated with the good fortune of having alternatives (and choosing among them even though they are uncertain)

– These skills are recognized and rewarded in the marketplace by employers & top graduate schools.

– They will make you a better Leader.

Skills are Focused on Improving Societal Challenges

• Operations Research:

– Logistics & Transportation

– Energy Systems

– Telecommunications & eCommerce

– Health Care

• Financial Engineering:

– Risk Management

– Investment Strategies

– Financial Instruments

– Economic Stimulation

• Machine Learning:

– Real-time Decision Systems

– Addressing High Dimensional Problems (aka “Big Data”)

Core Classes

• ORF 245 – Engineering Statistics

• ORF 307 – Optimization

• ORF 309 – Probability & Stochastic Processes

• ORF 335 – Introduction to Financial Engineering

• ORF 405 – Regression & Applied Time Series

• ORF 411 – Operations & Information Engineering

Eight Department Electives• From... MAT 320 - Introduction to Real Analysis, MAT 322/APC 350 - Methods in Partial Differential

Equations, MAT 375 - Introduction to Graph Theory, MAT 377 - Combinatorial Mathematics, MAT 378 - Theory of Games, MAT 385 - Probability Theory, MAT 391/MAE 305 - Mathematics in Engineering I or MAT 427, MAT 392/MAE 306 - Mathematics in Engineering II, MAT 427 - Ordinary Differential Equations, MAT 486 - Random Process, MAT 522 - Introduction to Partial Differential Equations, ORF 311 - Optimization Under Uncertainty, ORF 350 – Analysis of Big Data, ORF 360 – Decision Modeling in Business Analytics, ORF 363 – Computing and Optimization for the Physical and Social Sciences, ORF 375 - Junior Independent Work, ORF 376 - Junior Independent Work, ORF 401 - Electronic Commerce , ORF 406 - Statistical Design of Experiments, ORF 407 – Fundamentals of Queueing, ORF 409 - Introduction to Monte Carlo Simulation, ORF 417 - Dynamic Programming, ORF 418 - Optimal Learning, ORF 435 - Financial Risk Management, ORF 455 – Energy and Commodities Markets, ORF 467 – Transportation, ORF 473/474 - Special Topics in Operations Research and Financial Engineering, CEE 303 - Introduction to Environmental Engineering, CEE 460 - Risk Assessment and Management , CHM 303 – Organic Chemistry I, CHM 304 – Organic Chemistry II, COS 217 - Introduction to Programming Systems, COS 226 - Algorithms and Data Structures, COS 323 - Computing for the Physical and Social Sciences, COS 340 - Reasoning about Computation, COS 402 - Artificial Intelligence, COS 423 - Theory of Algorithms, COS 425 - Database and Information Management Systems, ECO 310 - Microeconomic Theory: A Mathematical Approach, ECO 312 – Econometrics: A Mathematical Approach, ECO 317 - The Economics of Uncertainty, ECO 332 – Economics of Health and Health Care, ECO 341 - Public Finance, ECO 342 - Money and Banking, ECO 361 - Financial Accounting, ECO 362 - Financial Investments, ECO 363 - Corporate Finance and Financial Institutions, ECO 414 - Introduction to Economic Dynamics, ECO 418 - Strategy and Information, ECO 462 - Portfolio Theory and Asset Management, ECO 464 - Corporate Restructuring, ECO 466 - Fixed Income: Models and Applications, ECO 467 - Institutional Finance, EEB 323 – Theoretical Ecology, ELE 485 - Signal Analysis and Communication Systems, ELE 486 - Digital Communication and Networks, MAE 433 - Automatic Control Systems, MOL 345 – Biochemistry, MOL 457 – Computational Aspects of Molecular Biology, NEU 437 – Computational Neuroscience, NEU 330 – Introduction to Connectionist Models

Some Common Tracks• Information Sciences

– ORF 401 – eCommerce

– ORF 418 – Optimal Learning

– COS 217 – Programming Systems

– COS 226 – Algorithms & Data Structures

– COS 425 – Database Systems

• Engineering Systems

– ORF 409 – Intro to Monte Carlo Simulation

– ORF 467 – Transportation Systems Analysis

– ORF 417 – Dynamic Programming

– MAE 433 – Automatic Control Systems

– ELE 485 – Signal Analysis and Communication Systems

More Common Tracks• Applied Mathmatics

– MAT 375 – Intro to Graph Theory

– MAT 378 – Theory of Games

– MAT 321 – Numerical Methods

– MAE 406 – Partial Differential Equations

• Financial Engineering– ORF 311 – Optimization Under Uncertainty

– ORF 350 – Analysis of Big Data

– ORF 435 – Financial Risk Management

– ECO 362 – Financial Investments

– ECO 465 – Financial Derivatives

More Common Tracks• Machine Learning

– COS 217 – Intro to Graph Theory

– COS 226 – Theory of Games

– ORF 350 – Analysis of Big Data

– ORF 407 – Fundamentals of Queueing Theory

– ORF 418 – Optimal Learning

• Statistics– ORF 311 – Optimization Under Uncertainty

– ORF 350 – Analysis of Big Data

– ORF 409 – Intro to Monte Carlo Simulation

– ORF 418 – Optimal Learning

– ECO 467 – Transportation Systems Analysis

More Common Tracks• Pre-Med/Health Care

– CHM 303 – Organic Chemistry I

– CHM 304 – Organic Chemistry II

– MOL 345 – BioChemistry

– ORF 350 – Analysis of Big Data

– ORF 401 – eCommerce

– ORF 418 – Optimal Learning

Selected Senior Theses• Eileen Lee’14 – Uncovering Systematic Corruption in the ER: An Empirical

Analysis of Motor Vehicle-Related Hospital Bills and their Impacts on Insurance Companies

• Adam Esquer’14 - The Real Moneyball: Modelling Baseball Salary Arbitration

• Lauren Hedinger’11 - The Quadrivalent Human Papillomavirus Vaccine: A Cost-Benefit Analysis of Cervical Cancer Prevention Strategies

• Stephanie Lubiak’11 – Neighborhood Nukes: Great for America? Great for the Environment? Great for Al Qaeda?

• James Tate’12 – The Game Behind the Game: An Analysis of Baseball Player Evaluation Models

• A. Hill Wyrough, Jr.’14 – A National Disaggregate Transportation Demand Model for the Analysis of Autonomous Taxi Systems

• Bharath Alamanda’13 – Customer Targeting in eCommerce: A Feature Selection and Machine Learning Approach

• Raj K. Hathiramani’10 – Dissecting the Collapse of Amaranth Advisors LLC (2006): Natural Gas Stochastic Volatility, Irrational Position-Sizing and

Predatory Trading

Recent Graduates• Graduate Schools: Harvard, Stanford,

Cornell, Georgia Tech, Texas A&M, U. of Kentucky (Med School)

• Banks & Investment Firms: Goldman Sachs, Morgan Stanley, JP Morgan, Deutche, BlackRock,

• Industries: Aspect Medical Systems, Parsons Brinkerhoff, Walt Disney, Abercrombie,

• Management/Economic Consulting: Mercer, Accenture, Monitor, McKinsey, Bates

Recent Graduates

Questions / Discussion

For more info see orfe.princeton.edu