Biography

I am a Research Associate at the Research Foundation of City University of New York (RFCUNY), working with Prof. Lei Xie.

I earned my Ph.D. in Computer Science from the Graduate Center, CUNY, under the supervision of Prof. Lei Xie. Prior to that, I obtained my B.S. in Physics from the University of Science and Technology of China (USTC), where I conducted research under the guidance of Prof. Zhenyu Li and Prof. Wenhua Zhang. I also worked on computational materials science at the University of Maryland, College Park (UMD).

In addition to my academic research, I gained industry experience as a Machine Learning Engineer Intern at Pinterest and as a Drug Discovery Research Scientist Intern at ByteDance, where I was supervised by Prof. Lei Li and Prof. Hao Zhou.

My field of expertise is computational biology, with a particular specialization in AI-driven drug discovery and therapeutic design. I’m open to collaborations on interesting projects.

News

Selected Publications

* indicates equal contribution; † indicates corresponding author.

Sequence-based Drug-Target Binding Site Pre-training Enables Cryptic Pocket Detection and Improves Binding Affinity and Kinetics Prediction
Shuo Zhang†, Li Xie, Daniel Tiourine, Lei Xie†

Journal of Cheminformatics, 2026 (Impact Factor: 7.9).

Multimodal Out-of-Distribution Individual Uncertainty Quantification Enhances Binding Affinity Prediction for Polypharmacology
Amitesh Badkul, Li Xie, Shuo Zhang, Lei Xie

Nature Machine Intelligence, 2025 (Impact Factor: 29.8).

                

MolGene-E: Inverse Molecular Design to Modulate Single Cell Transcriptomics
Rahul Ohlan, Raswanth Murugan, Li Xie, Mohammadsadeq Mottaqi, Shuo Zhang†, Lei Xie†

International Conference on Machine Learning (ICML) AI4Science Workshop, 2024.

Protein Language Model-Powered 3D Ligand Binding Site Prediction from Protein Sequence
Shuo Zhang, Lei Xie

Neural Information Processing Systems (NeurIPS) AI for Science Workshop, 2023.

A Universal Framework for Accurate and Efficient Geometric Deep Learning of Molecular Systems
Shuo Zhang, Yang Liu, Lei Xie

Scientific Reports, 2023.

    

End-to-End Sequence-Structure-Function Meta-Learning Predicts Genome-Wide Chemical-Protein Interactions for Dark Proteins
Tian Cai, Li Xie, Shuo Zhang, Muge Chen, Di He, Amitesh Badkul, Yang Liu, Hari Krishna Namballa, Michael Dorogan, Wayne W. Harding, Cameron Mura, Philip E. Bourne, Lei Xie

PLOS Computational Biology, 2023.

Physics-aware Graph Neural Network for Accurate RNA 3D Structure Prediction
Shuo Zhang, Yang Liu, Lei Xie

Neural Information Processing Systems (NeurIPS) Machine Learning for Structural Biology (MLSB) Workshop, 2022.

Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures
Shuo Zhang, Yang Liu, Lei Xie

Neural Information Processing Systems (NeurIPS) Machine Learning for Structural Biology (MLSB) Workshop, 2020.

    

Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation
Shuo Zhang, Lei Xie

International Joint Conference on Artificial Intelligence (IJCAI), 2020.

Acceptance rate: 592/4717=12.6%.

Heterogeneous Multi-Layered Network Model for Omics Data Integration and Analysis
Bohyun Lee, Shuo Zhang, Aleksandar Poleksic, Lei Xie

Frontiers in Genetics, 2020.

Theoretical Study of Adsorption and Dehydrogenation of C2H4 on Cu(410)
Yangyunli Sun*, Shuo Zhang*, Wenhua Zhang, Zhenyu Li

Chinese Journal of Chemical Physics, 2018.

Research Word Cloud

Services

• Conference Reviewer:
  • Neural Information Processing Systems (NeurIPS) (2021 - 2026)
  • International Conference on Machine Learning (ICML) (2021 - 2025)
  • International Conference on Learning Representations (ICLR) (2022 - 2027)
  • International Conference on Computer Vision (ICCV) (2025)
  • Machine Learning in Structural Biology (MLSB) Workshop (2023, 2025)
  • International Conference on Machine Learning & Applications (CMLA) (2020)
• Journal Reviewer:
  • Nature Communications
  • Journal of Cheminformatics
  • IEEE Journal of Biomedical and Health Informatics
  • Journal of Chemical Information and Modeling
  • Bioinformatics
  • BMC Bioinformatics
  • PLOS Computational Biology
  • IEEE/ACM Transactions on Computational Biology and Bioinformatics
  • Computer Vision and Image Understanding
  • International Journal of Advanced Computer Science and Applications

Others

• Patent:
  • Method and Apparatus for Designing Ligand Molecules. Yuwei Yang, Jiarui Lu, Shuo Zhang, Hao Zhou. US Patent App. 18/839,008, 2025.
• Presentation:
  • How Much Can We Learn from Official Property Data Alone in the OpenADMET ExpansionRx Blind Challenge? OpenADMET Conference 2026, Jun. 2026.
  • Cell-Type Specific Molecular Design for Next-Generation Polypharmacology. Appel Poster Event and Symposium, May 2025.
  • Keynote: Accurate High-throughput Cryptic Binding Site Prediction Using Protein Language Model. International Conference on Intelligent Systems for Molecular Biology (ISMB), Jul. 2024.
  • Scalable and Accurate Target-Based Compound Screening Using Large Language Model. Appel Poster Event and Symposium, May 2024.
  • Protein Large Language Model-Powered 3D Ligand Binding Site Prediction from Protein Sequence. LLMs4Bio Workshop at AAAI Conference on Artificial Intelligence (AAAI), Feb. 2024.
  • Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation. International Joint Conference on Artificial Intelligence (IJCAI), Jan. 2020
  • Enhancing Attention-based Graph Neural Networks via Cardinality Preservation. Deep Learning on Graphs Workshop at AAAI Conference on Artificial Intelligence (AAAI), Dec. 2019.