Transcript Why ORFE? - Operations Research and Financial Engineering

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
– 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