Recipient of the PIMCO Postdoctoral Fellow in Data Science award
ML and Systems Rising Stars 2025 award, one of 38 awardees among 150+ applications
Theoretical framework bridging robust reinforcement learning and offline reinforcement learning via pessimism accepted to L4DC 2025
Undergraduate mentee's work on a theoretical framework addressing transfer setup in reinforcement learning accepted as an oral presentation at AISTATS 2025 (acceptance rate ~2%)
New fundamental result on game-theoretic equilibria explaining human behaviors in multi-agent scenarios accepted as an oral presentation at ICLR 2025 (acceptance rate 1.8%)
Background
Research interests include machine learning, theoretical foundations of reinforcement learning algorithms, addressing the gap between simulation and real-world performance. Future research will focus on broader domains like multi-agent systems, imitation learning, human feedback, and more. Additional expertise spans optimization, high-dimensional probability, multi-armed bandits, online learning, and stochastic theory.
Miscellany
In the job market for full-time faculty positions and core industrial research positions starting in 2025.