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• A Prospect-Theoretic Policy Gradient Framework for Behaviorally Nuanced Reinforcement Learning
• On the Global Optimality of Policy Gradient Methods in General Utility Reinforcement Learning
• Invited talk - ICCOPT 2025
• Online Multi-Agent Control with Adversarial Disturbances
• Optimistic Online Learning in Symmetric Cone Games
• Learning Zero-Sum Linear Quadratic Games with Improved Sample Complexity and Last Iterate Convergence
• Invited talk - Learning Theory and Applications Workshop, NTU
• Invited talk - Finance and RL Talks
• Independent Policy Mirror Descent for Markov Potential Games: Scaling to Large Number of Players
• Invited talk - 4th Symposium on Machine Learning and Dynamical Systems