S. Min, D. J. Russo. An Information-Theoretic Analysis of Nonstationary Bandit Learning. Submitted to Operations Research.

S. Min, C. Maglaras, C. C. Moallemi. Cross-sectional Variation of Intraday Liquidity, Cross-Impact, and their Effect on Portfolio Execution. Operations Research 70(2):830–846. March 2022

S. Min, C. Maglaras, C. C. Moallemi. Thompson Sampling with Information Relaxation Penalties. Accepted at Management Science.

Y. Kanoria, S. Min, P. Qian. The Competition for Partners in Matching Markets. Accepted at Management Science.

S. Min, C. Maglaras, C. C. Moallemi. Risk-sensitive Optimal Execution via a Conditional Value-at-Risk Objective. Major revision at Management Science. Initial version: Nov 2020. 2021 INFORMS Section on Finance Best Student Paper Competition Finalist.

S. Min, C. C. Moallemi, D. J. Russo. Policy Gradient Optimization of Thompson Sampling Policies. Submitted to INFORMS Journal on Computing. Initial version: June 2020.

J. Kim, S. Min. Risk-sensitive Policy Optimization via Predictive CVaR Policy Gradient. Submitted to ICML 2024 (review ratings: 6/6/7/7)