Class 2019 Princeton Preview Presented by Prof. Alain Kornhauser Department 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 Engineering Systems 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 Financial Engineering 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 Statistics 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 409 – Intro to Monte Carlo Simulation 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