Princeton’s B.S.E. in Operations Research and Financial Engineering (ORFE) integrates analytical thinking with quantitative modeling to prepare students for careers in tech, finance, policy, and research. These suggested project topics offer opportunities to innovate across theory and practice.
Stochastic Optimization for Renewable Energy Grid Planning
Predictive Modeling of Stock Prices Using Machine Learning
Dynamic Portfolio Optimization Using Reinforcement Learning
Simulating Systemic Risk in Interbank Lending Networks
Queueing Theory Models in Urban Public Transportation Systems
Risk Analysis of Crypto Assets Using Value-at-Risk (VaR)
Supply Chain Disruption Modeling Using Game Theory
Monte Carlo Simulations for Derivatives Pricing
Algorithmic Trading Strategy Based on Market Microstructure
Real-Time Fraud Detection in Financial Transactions
Optimization of Emergency Services Deployment Using GIS
Machine Learning for Credit Scoring and Loan Default Prediction
Markov Chain Models for Customer Behavior Forecasting
Deep Learning for Predictive Maintenance in Industrial Systems
Operations Research in Vaccine Distribution Logistics
Simulated Annealing for Airline Crew Scheduling
Big Data Optimization in E-Commerce Inventory Management
Option Pricing Models with Stochastic Volatility
Risk-Adjusted Performance Analysis of ESG Portfolios
Optimal Bidding Strategies in Electricity Markets
Collexa supports ORFE students in simulation modeling, data analytics, portfolio strategy development, and algorithmic implementation across engineering and finance.
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