Meet the team

Dr. Yiu Chung Daniel Lau is a trained statistician with a BSc in Statistics and a PhD in Public Health from the University of Hong Kong. He joined the team in 2021. His research interests include infectious disease modelling, and he develops models to predict disease burden and risk for respiratory viruses, including influenza and COVID-19. He also develops forecasting models to guide proactive interventions that mitigate transmission and help control these diseases.

He holds a Health and Medical Research Fund (HMRF) grant as PI, and currently serves as the data manager at the Division of Epidemiology and Biostatistics in the School, and is involved in several projects within the team.

Contact: chunglau@hku.hk

Mr. Jiaqi Chen (Jackie) obtained his M.Sc. in Systems Science in 2024 (USST, Shanghai) and B.Eng. in Information Systems and Technology in 2021 (STBU, Shandong). His research interests lie at the intersection of infectious disease modelling and AI for health. He develops multiscale modelling frameworks that connect within-host pathogen dynamics with population-level disease transmission. By integrating mechanistic epidemic models with Bayesian machine learning and other data-driven AI methods, he aims to improve epidemic forecasting, risk assessment, and public health preparedness. He also explores the potential of large language models (LLMs) to advance public health research and decision-making. 

Beyond academia, Jackie leads interdisciplinary teams in developing AI-native products and has secured government-backed funding for these ventures. Outside work, he enjoys swimming, hiking, and other outdoor activities (personal website).

Contact: jiaqichen@connect.hku.hk

Mr. Zhichao Zhou earned his MPH in Epidemiology of Microbial Disease in 2026 (Yale University) and B.Sc. in Applied Mathematics in 2024 (UNNC, Ningbo). His research interests are developing mathematical and computational models to investigate the transmission dynamics and progression of infectious diseases. His current research focuses on understanding the transmission dynamics of infectious diseases, including influenza, hand-foot-and-mouth, and dengue under time-varying interventions. He explores opportunities to establish a close connection between biological processes and their representation in mechanistic mathematical models. His primary aim is to understand how disease patterns emerge and change over time by integrating biological principles with mathematical and computational analysis.

Contact: zhichao.zhou@connect.hku.hk 

Mr. Bowen Li obtained his MSc in Statistical Sciences in 2026 and a B.Sc. in Mathematics and Statistics in 2025 (both from the University of Toronto). His research interests lie in Bayesian statistics and spatiotemporal modeling, with applications in public health and epidemiology. Currently, his work focuses on modeling infectious disease dynamics, including predicting time-varying transmissibility and disease severity, to better understand disease transmission patterns.

Contact: bowenli@hku.hk

Ms. Yumeng Gu obtained his MSc in Statistical Sciences in 2026 and a B.Sc. in Mathematics and Statistics in 2025 (both from the University of Hong Kong). Her research interests are developing statistical and machine learning models for predicting infectious disease burden with applications to public health and epidemiology. Currently, she is working on forecasting infectious disease dynamics for respiratory and vector-borne infectious diseases.

Contact: ymgu@hku.hk