I am a PhD student at Nanyang Technological University, advised by Prof. Bo An. Currently, I am leading Project Cradle, working with Prof. Zongqing Lu from Beijing Academy of Artificial Intelligence (BAAI). Our team is hiring. Feel free to contact me if you have interest.

My research interests lie in reinforcement learning (RL), generative models, and AI agents. Artificial general intelligence(AGI) has been my dream all along. My goal is to design general intelligent agents outperforming humans across all tasks in cyberspace.

Previously, I worked closely with Prof. Christopher Amato and Dr. Yuchen Xiao as an RA at Northeastern University (NEU). Before NEU, I obtained my master's degree in the College of Information & Computer Sciences at University of Massachusetts (UMass), Amherst. During this period, I worked with Prof. Robert Kozma and I also collaborated with Microsoft AI Development Acceleration Program under the lead of Dr. Soundar Srinivasan and Dr. H M Sajjad Hossain. Before UMass, I obtained my bachelor's degree in the Software College at Beihang University. During this period, I used to work with Prof. Yasha Wang at Peking University.

When I am not doing research, I enjoy watching animations and playing games (especially miHoYo's games). An interesting coincidence is that my current advisor's name is almost the same as Amber's, the first local guide and good partner in Genshin Impact, in Chinese.

Publications

I can also be found on Google Scholar.

(“*” indicates equal contribution. "†" indicates equal advising.)

Conference Papers

  1. Towards General Computer Control: A Multimodal Agent for Red Dead Redemption II as a Case Study
    Weihao Tan, Ziluo Ding, Wentao Zhang, Boyu Li, Bohan Zhou, Junpeng Yue, Haochong Xia, Jiechuan Jiang, Longtao Zheng, Xinrun Xu, Yifei Bi, Pengjie Gu, Xinrun Wang, Börje F. Karlsson, Bo An, Zongqing Lu
    Preprint | [paper] | [website]

  2. True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning
    Weihao Tan, Wentao Zhang, Shanqi Liu, Longtao Zheng, Xinrun Wang, Bo An
    ICLR 2024 | [paper]

  3. Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning
    Yuchen Xiao, Weihao Tan, Christopher Amato
    NeurIPS 2022 | [paper]

  4. On Optimizing Interventions in Shared Autonomy
    Weihao Tan*, David Koleczek*, Siddhant Pradhan*, Nicholas Perello, Vivek Chettiar, Nan Ma, Aaslesha Rajaram, Vishal Rohra, Soundar Srinivasan, H M Sajjad Hossain†, Yash Chandak†
    AAAI 2022 | [paper]

  5. Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks
    Weihao Tan, Devdhar Patel, Robert Kozma
    AAAI 2021 | [paper]

  6. MUSEFood: Multi-sensor-based Food Volume Estimation on Smartphones
    Junyi Gao*, Weihao Tan*, Liantao Ma, Yasha Wang and Wen Tang
    IEEE UIC 2019 | [paper]

Journal Paper

  1. Optimization Methods for Improved Efficiency and Performance of Deep Q-Networks upon Conversion to Neuromorphic Population Platforms
    Weihao Tan, Devdhar Patel, Robert Kozma
    Knowledge-Based Systems(IF: 8.139) | [paper]

Workshop Papers

  1. Asynchronous Multi-Agent Actor-Critic with Macro-Actions
    Yuchen Xiao, Weihao Tan, Christopher Amato
    How to Design Multi-Agent Systems In the Absence of Reliable Communications@AAAI 2022 Spring Symposium | [paper]

  2. Intervention Aware Shared Autonomy
    Weihao Tan*, David Koleczek*, Siddhant Pradhan*, Nicholas Perello, Vivek Chettiar, Nan Ma, Aaslesha Rajaram, Vishal Rohra, Soundar Srinivasan, H M Sajjad Hossain†, Yash Chandak†
    Human-AI Collaboration in Sequential Decision-Making@ICML 2021 | [paper]