Scholar
Muhan Lin
Google Scholar ID: dxKq5XQAAAAJ
Purdue University
Citations & Impact
Citations
14
H-index
2
i10-index
0
Publications
5
Co-authors
8
list available
Publications
Resume (English only)
Academic Achievements
- - Paper IGSES accepted for oral presentation at AAAI 2025
- - A paper accepted to EMNLP 2024
- - A paper accepted to the RLBrew workshop (part of RLC 2024)
- - Served as a reviewer for RAL 2025, Neurips ARLET 2025, ICRA 2024, 2025, and IEEE Transactions on Games 2024
Research Experience
- - Working on single/multi-agent reinforcement learning at Purdue University
- - Previously collaborated with Honda Research Institute during the master's program at Carnegie Mellon University
- - Participated in the CMU Robotics Institute Summer Scholars (RISS) program
Education
- - Ph.D. in Computer Science at Purdue University, advised by Prof. Joseph Campbell
- - M.S. in Robotics (MSR) at Carnegie Mellon University, advised by Prof. Katia Sycara, collaborating with Honda Research Institute
- - Bachelor's degree from the Chinese University of Hong Kong, Shenzhen, thesis supervised by Prof. Tin Lun Lam
- - Participated in CMU Robotics Institute Summer Scholars (RISS) program in 2022, working with Prof. Sebastian Scherer
Background
- Research interests include single/multi-agent reinforcement learning (RL), using LLM to train AI agents with humanlike acting and learning habits, improving time and resource efficiency and robustness of RL. Areas of interest encompass human-value aligned RL (such as RLHF, RLAIF), reward specification, multi-agent collaboration analogous to human teamwork, human-in-the-loop interaction and adaptation, etc. Long-term research goal is to develop AI agents which can not only seamlessly interact with each other, but also with human partners.
