@Columbia University

Stochastic Models

• Foundations of Stochastic Processes

• Analysis and Probability - I & II

• Stochastic Modeling - I & II [ Markov Chains, Martingales, Brownian Motion and Stoc. calc. ]

Optimization

• Convex Optimization

• Dynamic Programming

• Optimization - I & II [ Linear, Non-Linear and Network Optimization ]

Statistics/Learning

• Large Scale Machine Learning

• Computational Bayesian Methods (Audit)

• Sparse Signal Modeling

• Computational Statistics

Others

• Advanced Financial Engineering (Audit)

• Game Theory

• Short Couse on Mechanism Design (@Kellogs, Northwestern)

• Production Management

As Teaching Assistant

• Game Theory, O.R. in Public Policy

• Stochastic Models / Deterministic Optimization

• Scheduling: Theory and Algorithms