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Ling Pan

潘玲
Assistant Professor
Department of Electronic and Computer Engineering
Department of Computer Science and Engineering (by courtesy)
Hong Kong University of Science and Technology
Email: lingpan [@] ust [DOT] hk


I am a Tenure-Track Assistant Professor in the Department of Electronic and Computer Engineering and the Department of Computer Science and Engineering (by courtesy) at the Hong Kong University of Science and Technology (HKUST). My research interests mainly include theoretical understanding, algorithmic improvements and practical application of generative flow networks (GFlowNets), reinforcement learning and multi-agent systems.

I focus on developing robust, efficient, and practical intelligent decision-making algorithms. I am also interested in the application of reinforcement learning and GFlowNets in practical problems like computational sustainability and drug discovery.

Prior to that, I was a postdoctoral fellow at Mila supervised by Prof. Yoshua Bengio. I received my Ph.D. from the Institute for Interdisciplinary Information Sciences (IIIS) (headed by Prof. Andrew Yao), Tsinghua University in 2022, advised by Prof. Longbo Huang. I received my B.E. from the School of Computer Science and Engineering, Sun Yat-Sen (Zhongshan) University, Guangzhou, China in 2017. During my Ph.D., I was fortunate to visit Stanford University advised by Prof. Tengyu Ma, University of Oxford advised by Prof. Shimon Whiteson, and I was a research intern in the Machine Learning Group at Microsoft Research Asia advised by Dr. Wei Chen. I was also a recepient of Microsoft Research Ph.D. Fellowship (Asia).

Please drop me an email if you are interested in collaborating with me.

Prospective Students: I am actively looking for self-motivated students (including undergraduate/graduate students and research assistants) who are interested in the areas of artificial intelligence, machine learning, deep reinforcement learning, generative flow networks, and multi-agent systems. I have several PhD/MPhil/RA openings starting in Fall 2024 at HKUST. Please drop me an email with your CV (including rankings/publications) if you are interested.

Selected Awards

  • Outstanding Doctoral Thesis, by Tsinghua University, 2022
    Thesis: Towards Robust, Efficient, and Practical Deep Reinforcement Learning Algorithms
    The only selected computer science doctoral thesis in IIIS, Tsinghua University
  • Outstanding Graduate (top 3%), by Tsinghua University, 2022
    Also Beijing outstanding graduate and IIIS, Tsinghua University outstanding graduate, 2022
  • China National Scholarship (top 2%), by Ministry of Education of China, 2021
  • Microsoft Research Ph.D. Fellowship (Asia), 2020
    12 outstanding Ph.D. students in computer science in the Asia-Pacific region
  • China National Scholarship (top 2%), by Ministry of Education of China, 2016
  • China National Scholarship (top 2%), by Ministry of Education of China, 2015
  • China National Scholarship (top 2%), by Ministry of Education of China, 2014

Professional Activities

  • Organizer:
  • SPC member:
    • International Joint Conference on Artificial Intelligence (IJCAI), 2021
  • PC member/Reviewer:
    • International Conference on Learning Representations (ICLR), 2022-2023
    • Conference on Neural Information Processing Systems (NeurIPS), 2021-2023
    • International Conference on Machine Learning (ICML), 2021-2023
    • AAAI Conference on Artificial Intelligence (AAAI), 2021
    • International Joint Conference on Artificial Intelligence (IJCAI), 2024
    • Transactions of Machine Learning Research (TMLR)
    • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
    • Foundation Models for Decision Making, NeurIPS 2023 Workshop

Selected Talks

Teaching

  • Spring 2024: ELEC6950 Departmental Seminar