Students
Current PhD Students
Nicholas CorradoResearch Interests: data efficiency; action representation learning; data augmentation in reinforcement learning.
Representative Work: On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling [Arxiv Pre-print]
Brahma Pavse
Research Interests: offline policy evaluation; representation learning; RL for queueing problems.
Representative Work: State-Action Similarity-Based Representations for Off-Policy Evaluation [NeurIPS '23].
Subhojyoti Mukerjee (co-advised w/ Rob Nowak)
Research Interests: optimal data collection for policy evaluation and learning; reinforcement learning theory.
Representative Work: ReVar: Strengthening Policy Evaluation Via Reduced Variance Sampling [UAI '23].
Adam Labiosa
Research Interests: RL + robotics; multi-agent reinforcement learning; sim2real
Representative Publication: Reinforcement Learning within the Classical Robotics Stack: A Case Study in Robot Soccer [ICRA '25']
Yunfu Deng
Research Interests: RL + robotics; sim2real.
Abhinav Harish
Research Interests: RL + robotics; multi-agent reinforcement learning.
Representative Work: Reinforcement Learning via Auxiliary Task Distillation [ECCV '24].
Will Cong
Research Interests: model-based RL; partial observability; RL + robotics
Current MS Students
- Anshuman Senapti
- Joseph Zhong
Current Undergraduate Students
- Ben Hong
- Chen Li
- Lucas Poon
Alumni
- Yuxiao Qu, B.S. in CS (next PhD @ Carnegie Mellon)
- Adhit Sankaran, B.S. in CS (next MS @ Cornell)
- Arun Ravi, MS in CS (next Google)
- Yoon Chae Na, MS in CS
- Shreyansh Sharma, MS in CS (next Amazon)
- Duohan Zhang, MS in Stats (next PhD @ Penn State)
- John Balis, MS in CS