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Dr Jiannan YANG
Post-doctoral Fellow
HKU Musketeers Foundation Institute of Data Science 
Key Expertise
Deep Learning in Healthcare; Interpretable Deep Learning; Medical Informatics
About Me

Dr. Jiannan Yang is Post-doctoral Research Fellow at the HKU Musketeers Foundation Institute of Data Science (HKU IDS), working with Prof. Qingpeng Zhang. He received his Ph.D. degree in Data Science from the City University of Hong Kong and his Bachelor’s degree in Geographic Information Science from Nanjing University.

Current Research Project

Currently, his research project focuses on developing a generalist multimodal foundation model for pharmacy practices in Hong Kong.

Effective medication management is fundamental to patient safety and treatment efficiency, especially in regions like Hong Kong, where there is a high prevalence of chronic diseases requiring complex medication protocols. Traditional methods for pharmacy-related tasks, which rely on structured records and basic machine learning, often fall short in real-world scenarios that necessitate the synthesis of multimodal information. These models, which predominantly use data covering Western populations, overlook the ethnic and regional differences, making them less suitable for the Hong Kong demographic. To bridge this gap, this project aims to propose a multimodal large language model (LLM) specifically designed for Hong Kong’s pharmacy practices.

Selected Publications
  • Yang, J., Li, Z., W.K.K., Yu, S., Xu, Z., Chu, Q., Zhang, Q. Deep Learning Identifies Explainable Reasoning Paths of Mechanism of Drug Action for Drug Repurposing from Multilayer Biological Network. Briefings in Bioinformatics. 2022.
  • Yang, J., Xu, Z., Wu, W.K.K., Chu, Q., Zhang, Q. GraphSynergy: Network Inspired Deep Learning Model for Anti–Cancer Drug Combination Prediction. Journal of the American Medical Informatics Association. 2021.
  • Liang, P.*, Yang, J.*, Wang, W.., Yuan G., Han, M., Zhang, Q, Li, Z. Deep Learning Identifies Intelligible Predictors of Poor Prognosis in Chronic Kidney Disease. IEEE Journal of Biomedical and Health Informatics. 2023.
Research Interests
His research is primarily concentrated in the field of medical informatics. Specifically, he focuses on developing novel artificial intelligence methods for innovative drug discovery and disease progression prediction.