Team

MS&E: Computational methods for distributionally robust stochastic control

MS&E: Distributionally robust reinforcement learning, algorithms for stochastic optimization, extremes

ICME: Distributionally robust stochastic control and regret optimization

MS&E: Optimal transport, mean field models, distributionally robust optimization. (Jointly advised with P. Glynn)

Liu - MS&E: Stochastic control, distributionally robust control, and diffusion models

MS&E: Distributionally robust control, games, learning. (Jointly advised with N. Bambos)

MS&E: Distributionally robust reinforcement learning, reinforcement learning with human feedback

ICME: Risk sensitive stochastic optimization and application to power systems

MS&E: Causal inference, distributional robustness. (Jointly advised with V. Syrgkanis)

MS&E: Optimization in the space of probabilities

MS&E: Reinforcement learning, gradient estimation, stochastic control, distributional robust control. (Jointly advised with P. Glynn)

MS&E: Optimal transport, efficient numerical methods for stochastic control

Math: Optimal transport, hypothesis testing, branching random walks, polymer networks