Me
Haitao Lin (林海涛)
CS Ph.D. Student @ Westlake University

About

I am a CS Ph.D student at CAIRI@Westlake University. I obtained my B.S. degree in Solid State Physics from Sichuan University. My research interests focus on generative models and their applications in AI4Science, including small molecule and protein generation. Additionally, I have worked on modeling continuous flow fields and extreme events.

I will graduate in June 2026 and am seeking postdoctoral positions in North America to continue research on generative models and AI4Science. If you have postdoctoral openings and are interested in having me join your team, welcome to contact me.

Education

Ph.D.           Sep. 2021 - Present
                     - Westlake University & Zhejiang University, Hangzhou, China
                     - Ph.D. student in Computer Science;
                     - Under the supervision of Stan Z. Li

News

  • Three papers (CBGBench, EVA, SimDDG) are accepted by ICLR 2025, with CBGBench as spotlight presentation.
  • One paper (EDTPP) is finally accepted by IEEE TKDE after 3 years of review process from my first year of Ph.D. T^T
  • One paper (DiffBP) is accepted by Chemical Science.
  • One paper on Lead Optimization is accepted by Journal of the American Chemical Society.
  • Four papers (PPFlow; GeoAB; Prompt-DDG; Re-Dock) are accepted by ICML 2024, with Re-Dock as spotlight presentation.
  • One paper (MAPE-PPI) is accepted by ICLR 2024, as spotlight presentation.
  • Two papers (PSC-CPI; SAO) are accepted by AAAI 2024.
  • One paper (D3FG) is accepted by NeurIPS 2023.

Experiences

  • Jun. 2024 - Present
        - DP Technology, Beijing, China
        - Research Intern, working on Biomolecule Generation;
        - Under the guidance of Zhifeng Gao and Guolin Ke
  • Jul. 2019 - Aug. 2019
        - CBICR, Tsinghua University, Beijing, China
        - Visiting Student, working on Neural Science with ML;
        - Supervisor: Quan Wen
    		•

    Selected Publications

    Drug Design:
  • CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph
    •      Lin, H., Zhao, G., Zhang, O., Huang, Y., Wu, L., Tan, C., Liu, Z., Gao, Z., Li, SZ.
         International Conference on Learning Representations, 2024 (Spotlight, Top 2.0%)
         [Paper]      [Code]
  • DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding
    •      Lin, H., Huang, Y., Zhang, O., Ma, S., Liu, M., Li, X., Wu, L., Ji, S., Hou, T., Li, SZ.
         Chemical Science, Royal Society of Chemistry, 2024
         [Paper]      [Code]
  • Deep Lead Optimization: Leveraging Generative AI for Structural Modification
    •      Zhang, O.*, Lin, H.* , Zhang, H., Zhao, H., Huang, Y., Hsieh, C. Y., Pan, P., Hou, T.
         Journal of the American Chemical Society, 2024
         [Paper]
  • Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration
    •      Lin, H., Huang, Y., Zhang, O., Liu, Y., Wu, L., Li, S., Chen, Z., Li, SZ.
         Neural Information Processing Systems, 2023
         [Paper]      [Code]
    Protein&Peptide Design:
  • GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation
    •      Lin, H., Wu, L., Huang, Y., Liu, Y., Zhang, O., Zhou, Y., Sun, R., Li, SZ.
         International Conference on Machine Learning, 2024
         [Paper]      [Code]
  • Target-Aware Peptide Design with Torsional Flow Matching
    •      Lin, H., Zhang, O., Zhao, H., Jiang, D., Wu, L., Liu, Z., Huang, Y., Li, SZ.
         International Conference on Machine Learning, 2024
         [Paper]      [Code]
    Continuous Flow & Extreme Events:
  • An Empirical Study: Extensive Deep Temporal Point Process
    •      Lin, H., Tan, C., Wu, L., Liu, Z., Zhao, G., Li, SZ.
         IEEE Transaction on Knowledge and Data Engineering, 2024
         [Paper]      [Code]
  • Exploring Generative Neural Temporal Point Process
    •      Lin, H., Wu, L., Zhao, G., Liu, P., Li, SZ.
         Transaction on Machine Learning Research, 2022
         [Paper]      [Code]
  • Conditional Local Convolution for Spatio-temporal Meteorological Forecasting
    •      Lin, H., Gao, Z., Xu, Y., Wu, L., Li, L., Li, SZ.
         AAAI Conference on Artificial Intelligence, 2022
         [Paper]      [Code]

    Selected Honors & Awards

    • National Scholarship, 2016
    • National Scholarship, 2017

    Miscellaneous

    I enjoy cooking, brewing coffee, and spending time with my family and my cats (Edamame the Bicolor Garfield and Pinenut the British Golden Longhair).
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