Guoqing Liu (刘国庆)
Senior Researcher
Microsoft Research AI for Science

Google Scholar | Github

guoqingliu (at) microsoft.com
21 Station Road, Cambridge, CB1 2FB, United Kingdom
Biography
Guoqing Liu is a Senior Researcher at Microsoft Research AI for Science based in Cambridge, UK. His research interests include reinforcement learning (RL), large language models (LLMs), and AI for Scientific Discovery. Currently, he works on developing LLMs and RL agents to advance chemistry and drug discovery (e.g., PDVN, RetroChimera, NatureLM, and MuProtein). During his PhD studies and his first year as a researcher at Microsoft Research Asia, he gained extensive experiences in deep RL research and its applications in video games (e.g., Project Suphx: The World's Best Mahjong AI, and Project Mariana: Automated Game Testing with Xbox Studios). Before joining Microsoft Research, he completed his Ph.D. from the University of Science and Technology of China (USTC) through a joint program with Microsoft Research Asia (2016-2021), under the supervision of Tie-Yan Liu and Nenghai Yu.

Publications
("*": equal contribution; "†": correspondence)

LLMs, Reinforcement Learning, AI for Science (2022-2025)

  1. What's next?
  2. Accelerating protein engineering with fitness landscape modelling and reinforcement learning [Paper][News]
    Haoran Sun*, Liang He*, Pan Deng*, Guoqing Liu*, Zhiyu Zhao, Yuliang Jiang, Chuan Cao, Fusong Ju, Lijun Wu, Haiguang Liu, Tao Qin, Tie-Yan Liu
    Nature Machine Intelligence (Nature Machine Intelligence 2025)
  3. Chemist-aligned retrosynthesis by ensembling diverse inductive bias models [Paper][News]
    Krzysztof Maziarz*, Guoqing Liu*, Hubert Misztela, Austin Tripp, Junren Li, Aleksei Kornev, Piotr Gaiński, Holger Hoefling, Mike Fortunato, Rishi Gupta, Marwin Segler. arXiv 2025.
  4. NatureLM: Deciphering the Language of Nature for Scientific Discovery [Paper]
    Yingce Xia*, Peiran Jin*, Shufang Xie*, Liang He*, Chuan Cao*, Renqian Luo*, Guoqing Liu*, Yue Wang*, Zequn Liu*, Yuan-Jyue Chen*, Zekun Guo*, etc. NatureLM Team, arXiv 2025.
  5. HybriDNA: A Hybrid Transformer-Mamba2 Long-Range DNA Language Model [Paper]
    Mingqian Ma*, Guoqing Liu*, Chuan Cao*, Pan Deng*, Tri Dao, Albert Gu, Peiran Jin, Zhao Yang, Yingce Xia, Renqian Luo, Pipi Hu, Zun Wang, Yuan-Jyue Chen, Haiguang Liu, Tao Qin
    ICLR 2025 Workshop on Machine Learning for Genomics Explorations (ICLR 2025 MLGenX Workshop)
  6. 3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery [Paper]
    Xiuyuan Hu, Guoqing Liu†, Can Chen, Yang Zhao, Hao Zhang, Xue Liu
    Thirteenth International Conference on Learning Representations (ICLR 2025)
  7. Token-level Direct Preference Optimization [Paper]
    Yongcheng Zeng, Guoqing Liu, Weiyu Ma, Ning Yang, Haifeng Zhang, Jun Wang
    Forty-first International Conference on Machine Learning (ICML 2024)
  8. Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers [Paper]
    Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yujiu Yang
    Twelfth International Conference on Learning Representations (ICLR 2024)
  9. Re-evaluating Retrosynthesis Algorithms with Syntheseus [Paper]
    Krzysztof Maziarz, Austin Tripp, Guoqing Liu, Megan Stanley, Shufang Xie, Piotr Gaiński, Philipp Seidl, Marwin Segler
    Faraday Discussions (Faraday Discussions 2024)
  10. De novo Drug Design using Reinforcement Learning with Multiple GPT Agents [Paper]
    Xiuyuan Hu, Guoqing Liu†, Yang Zhao, Hao Zhang
    Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)
  11. QuinNet: Efficiently Incorporating Quintuple Interactions into Geometric Deep Learning Force Fields [Paper]
    Zun Wang, Guoqing Liu, Yichi Zhou, Tong Wang, Bin Shao
    Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)
  12. Retrosynthetic Planning with Dual Value Networks [Paper]
    Guoqing Liu*, Di Xue*, Shufang Xie, Yingce Xia, Austin Tripp, Krzysztof Maziarz, Marwin Segler, Tao Qin, Zongzhang Zhang, Tie-Yan Liu
    Fortieth International Conference on Machine Learning (ICML 2023)

(Deep) Reinforcement Learning, Game Intelligence (2016-2022)

  1. Reinforcement Learning from Bagged Reward [Paper]
    Yuting Tang, Xin-Qiang Cai, Yao-Xiang Ding, Qiyu Wu, Guoqing Liu, Masashi Sugiyama
    Transactions on Machine Learning Research (TMLR 2024)
  2. You May Not Need Ratio Clipping in PPO [Paper]
    Mingfei Sun, Vitaly Kurin, Guoqing Liu, Sam Devlin, Tao Qin, Katja Hofmann, Shimon Whiteson. arXiv 2022.
  3. Inspector: Pixel-based Automated Game Testing via Exploration, Detection, and Investigation [Paper]
    Guoqing Liu, Mengzhang Cai, Li Zhao, Tao Qin, Adrian Brown, Jimmy Bischoff and Tie-Yan Liu
    IEEE Conference on Games 2022 (COG 2022, Oral)
  4. Independence-aware Advantage Estimation [Paper]
    Pushi Zhang, Li Zhao, Guoqing Liu, Jiang Bian, Minlie Huang, Tao Qin, Tie-Yan Liu
    30th International Joint Conference on Artificial Intelligence (IJCAI 2021)
  5. Demonstration Actor Critic [Paper]
    Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie- Yan Liu
    Neurocomputing, Volume 434, 28 April 2021, Pages 194-202 (Neurocomputing 2021)
  6. Return-based Contrastive Representation Learning for Reinforcement Learning [Paper]
    Guoqing Liu*, Chuheng Zhang*, Li Zhao, Tao Qin, Jinhua Zhu, Jian Li, Nenghai Yu, Tie-Yan Liu
    Ninth International Conference on Learning Representations (ICLR 2021)
  7. Suphx: Mastering Mahjong with Deep Reinforcement Learning [Paper][News]
    Junjie Li, Sotetsu Koyamada, Qiwei Ye, Guoqing Liu, Chao Wang, Ruihan Yang, Li Zhao, Tao Qin, Tie-Yan Liu, Hsiao-Wuen Hon. arXiv 2020.
  8. Trust Region Evolution Strategies [Paper]
    Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
    Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019)
Education
Professional Activities
Honors and Awards