Portrait of Shidang Xu 许适当

Principal Investigator profile

Shidang Xu 许适当

Professor

School of Biomedical Sciences and Engineering, South China University of Technology

He investigates molecular mechanisms and structure–property relationships, and develops rational design strategies and AI methods for molecular and materials science.

Email Shidang Xu 许适当

About

About Shidang Xu 许适当

Shidang Xu is a Professor in the School of Biomedical Sciences and Engineering at South China University of Technology. His research asks how limited observations, experiments, and computational resources can yield reliable, testable scientific knowledge that future research can build on, revise, and extend. He investigates molecular mechanisms and structure–property relationships, and develops rational design strategies and AI methods for molecular and materials science. Representative contributions include studies of molecular packing and excited-state behavior, mechanism-guided chemical design, electron-density representations for protein–ligand interaction prediction, and active learning for molecular discovery. He received his Ph.D. from the National University of Singapore in 2020, completed postdoctoral research there, and joined SCUT in 2022. His long-term goal is to develop transferable principles for scientific learning and discovery.

Selected work

Selected research contributions

  1. 2026

    Scientific representations for molecular interactions

    E-CloudBind combines ligand electron-density representations, physically motivated protein-pocket point clouds, and molecular graphs to predict binding affinity. It studies how representations can preserve useful interaction information under structural uncertainty.

    An electron-density point-cloud framework for robust protein-ligand interaction prediction

    Nat. Commun., 17(1), 7424 (2026)

  2. 2021

    Active learning for molecular discovery

    This work combines quantum calculations with Bayesian active learning to select promising photosensitizer candidates. Selected molecules were synthesized and evaluated, connecting computational search with experimental evidence.

    Self-Improving Photosensitizer Discovery System via Bayesian Search with First-Principle Simulations

    In J. Am. Chem. Soc.

  3. 2025

    Mechanistic descriptors for molecular design

    This collaborative study links changes in excited-state charge-transfer dynamics to fluorescence activation. Calculations and spectroscopy are used to evaluate a descriptor of fluorescence responsiveness and guide the design of near-infrared probes.

    Tuning Second Near-Infrared Fluorescence Activation by Regulating the Excited-State Charge Transfer Dynamics Change Ratio

    J. Am. Chem. Soc., 147(20), 17330-17341 (2025)

  4. 2022

    Molecular mechanisms and rational chemical design

    This study advances the understanding of molecular mechanisms by connecting molecular frameworks, packing interactions, molecular motion, and exciton utilization. It demonstrates how mechanistic insight can guide rational chemical design.

    High Exciton Utilization of 1D Molecular Column with High Packing Energy Formed by Folded π-Molecules

    In J. Am. Chem. Soc.

  5. 2026

    Cross-scale learning in medical imaging

    PyraE2E explores cross-scale super-resolution for end-to-end whole-slide image analysis. This collaborative work has been accepted at ECCV 2026.

    PyraE2E: Enhancing End-to-End WSI Analysis via Cross-Scale Super-Resolution

    ECCV, 2026 — Accepted

Full publication list

Teaching & Mentoring

I teach courses in neural networks and deep learning, and in data mining and big data. My mentoring aims to help students become independent researchers who can formulate scientific questions, design methods, and develop meaningful evaluation criteria.

Recognition and Research Support

He was selected for a national young talent programme in 2023. His research has received support from the National Natural Science Foundation of China, the Guangdong Natural Science Foundation’s Distinguished Young Scholars programme, a subproject under the National Key R&D Program of China, and Guangzhou municipal research programmes.

Further reading