Wang Dan Debby (王丹)

Assistant Professor
School of Science and Technology,
Hong Kong Metropolitan University,
Room D1117, Jockey Club Campus, Ho Man Tin, Hong Kong.

Email: dwang@hkmu.edu.hk

 



😊 I am seeking highly self-motivated Ph.D. and MPhil students to work on Structural Bioinformatics and AI for Science. Interested applicants may email me their CV.

Biography

Dr. Wang received her Ph.D. degree from the Department of Electronic Engineering at City University of Hong Kong in 2014. Later, she held research positions at the City University of Hong Kong (Postdoctoral Fellow, 2015–2016; Research Fellow, 2019–2020), the Caritas Institute of Higher Education (Research Fellow, 2016–2017), the National University of Singapore (Research Fellow, 2017–2018), and the University of Shanghai for Science and Technology (Assistant Professor, 2020–2022). Currently, she serves as an Assistant Professor in the School of Science and Technology at Hong Kong Metropolitan University.

Dr. Wang's research focuses on structural bioinformatics and AI for Science, with specific expertise in the following areas:

  1. Designing structure-based scoring models for protein-ligand binding affinity prediction (BAP) in computer-aided drug design;
  2. Target-specific BAP and drug-efficacy analysis in non-small cell lung cancer (NSCLC) studies;
  3. Molecular dynamics simulation and analysis in biomedical sciences;
  4. Molecular representation modeling and tool development;
  5. Molecular property prediction using AI and deep learning.

News

🔈Share your contributions to our newly organized Special Issue in Computational and Structural Biotechnology Journal!
🎉Our Special Issue was successfully published in International Journal of Machine Learning and Cybernetics!
🎉Our new journal paper 'Scoring protein-ligand binding structures through learning atomic graphs with inter-molecular adjacency' (accepted by PLOS Computational Biology) is online now!
🎉Our new conference paper 'GeCC: Generalized Contrastive Clustering with Domain Shifts Modeling' (accepted by AAAI) is online now!
🎉Our new conference paper 'Learning of Molecular Graphs in Toxicity Prediction' (accepted by IEEE ICMLC) is online now!
🧑‍🤝‍🧑 A new research assistant has joined our group!
🧑‍🤝‍🧑 Four new undergraduate researchers will join our group very soon!