Resume
Academic Achievements
- Published extensively in top-tier venues including ICML, NeurIPS, ICLR, SIOPT, and MOR
- Notable works include: 'Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents' (ICML 2024)
- 'Provably Mitigating Overoptimization in RLHF' (NeurIPS 2024)
- 'Maximize to Explore: A Single Objective Fusing Estimation, Planning, and Exploration' (NeurIPS 2023, spotlight)
- 'Embed to Control Partially Observed Systems' (ICLR 2023)
- 'Reinforcement Learning from Partial Observation' (ICML 2022)
- 'Is Pessimism Provably Efficient for Offline RL?' (ICML 2021, later published in Mathematics of Operations Research 2024)
- Multiple papers received Oral or Spotlight presentations
Background
- Associate Professor in the Departments of Industrial Engineering & Management Sciences and Computer Science at Northwestern University
- Affiliated with the Centers for Deep Learning and Optimization & Statistical Learning
- Long-term research goal is to develop a new generation of data-driven decision-making methods, theory, and systems that tailor AI toward addressing societal challenges
- Research focuses on: improving computational and statistical efficiency of autonomous learning agents; designing and optimizing societal-scale multi-agent systems involving human/robot cooperation and/or competition
- Research interests span machine learning, optimization, statistics, game theory, and information theory