I'm a 3rd-year Ph.D. student in Computer Science at Arizona State University. I work at Yochan Lab (AI Lab), supervised by Dr. Subbarao Kambhampati. My research interests lie at the intersection of machine learning (especially reinforcement learning), robotics, and human-agent interaction. Specifically, I am working on efficiently personalizing agent behavior and modeling human preference by taking multi-modal human inputs (e.g. binary feedback + human attention, or concept-based advice). I am also working on building intelligent agents that learn to solve complex tasks by integrating classical planning with reinforcement learning and leveraging human knowledge in the form of symbolic models.
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Google |
TikTok |
Arizona State University |
The University of Texas at Austin |
Leveraging Approximate Symbolic Models for Reinforcement Learning via Skill Diversity Lin Guan*, Sarath Sreedharan*, Subbarao Kambhampati ICML 2022 [Paper]
Enhanced Exploration in Neural Feature Selection for Deep Click-Through Rate Prediction Models via Ensemble of Gating Layers Lin Guan, Xia Xiao, Ming Chen, Youlong Cheng AAAI-22 Workshop on Practical Deep Learning in the Wild [Paper]
Learning from Ambiguous Demonstrations with Self-Explanation Guided Reinforcement Learning Yantian Zha*, Lin Guan*(equal contribution), Subbarao Kambhampati AAAI-22 Workshop on Reinforcement Learning in Games [Paper]
Symbols as a Lingua Franca for Bridging Human-AI Chasm for Explainable and Advisable AI Systems Subbarao Kambhampati, Sarath Sreedharan, Mudit Verma, Yantian Zha, Lin Guan AAAI 2022, Blue Sky Track [Paper]
Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic Grasping Yantian Zha, Siddhant Bhambri, Lin Guan IROS 2021 [Paper]
Leveraging Human Guidance for Deep Reinforcement Learning Tasks Ruohan Zhang, Faraz Torabi, Lin Guan, Dana H. Ballard, Peter Stone IJCAI 2019, Survey Track [Paper]
Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset Ruohan Zhang, Calen Walshe, Zhuode Liu, Lin Guan, Karl S. Muller, Jake A. Whritner, Luxin Zhang, Mary M Hayhoe, Dana H Ballard AAAI 2020 [Paper]