Wanyun Zhou

Wanyun Zhou

About Me

I am Wanyun Zhou, a Ph.D. student in Data Science and Analytics at The Hong Kong University of Science and Technology (Guangzhou).

My research interests are primarily in:

  • AI for Science: Applying advanced AI techniques to complex scientific domains, including physics (modeling and solving partial differential equations for multiple steady-state and unsteady physical systems), biology (peptide property prediction, drug-target interaction prediction, protein pre-training), and quantum chemistry.
  • Quantitative Finance: Focusing on social media and news-driven market analysis, financial time series analysis, and graph neural networks for stock market prediction and analysis.
  • Expertise in advanced AI techniques such as Large Language Models, Reinforcement Learning, and Generative Models.

I am passionate about adapting cutting-edge AI techniques to solve complex challenges in financial markets and scientific discovery.

🎓 Education

  • 09/2023 – Now: Ph.D. in Data Science and Analytics
    • The Hong Kong University of Science and Technology (Guangzhou), China
  • 09/2019 – 06/2023: Bachelor of Science in Mathematics and Applied Mathematics (GPA: 91.1/100, Top 3%)
    • Shandong University, China

📰 News

  • 2025-11 Our paper “DeltaLag: Learning Dynamic Lead-Lag Patterns in Financial Markets.” was accepted and presented as an Oral Presentation at the 6th ACM International Conference on AI in Finance (ICAIF 2025).
  • 2025-11 Our paper “Automated Machine Learning for Physics-Informed Convolutional Neural Networks” is accepted by Nature Communications Physics.
  • 2025-11 Our paper “Unleashing Expert Opinion from Social Media for Stock Prediction” is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • 2025-11 Our paper “DTBind: A Mechanism-driven Deep Learning Framework for Accurate Prediction of Drug–target Molecular Recognition” is accepted by the Science partner journal Research.

📚 Selected Publications