Xiang Chen's research focuses on spatio-temporal modeling of climate-sensitive infectious diseases, integrating large-scale health, climate, and human mobility data to improve epidemiological forecasting and support public health decision-making.
Biography
Xiang Chen is a Ph.D. candidate in Statistics in the Geospatial Statistics and Health Surveillance (GeoHealth) Group at King Abdullah University of Science and Technology (KAUST), supervised by Prof. Paula Moraga.
He received his B.Eng. and M.S. degrees in Computer Science from Harbin Institute of Technology (HIT), where he worked on automated machine learning and data-driven modeling methods. During his doctoral studies, he has developed advanced statistical and deep learning frameworks for dengue forecasting across Brazil, incorporating climate variability, spatial dependence, and mobility patterns.
His work has been published in journals including BMC Public Health, Tropical Medicine and Health, and Infectious Disease Modelling. His research aims to bridge statistical methodology and real-world health surveillance to support early warning systems and data-driven policy planning.
Research Interests
Xiang Chen's research focuses on the intersection of statistics, machine learning, and public health, with a primary emphasis on the spatio-temporal modeling of infectious diseases. His work leverages geospatial statistics, time series analysis, and human mobility modeling to understand disease spread and improve epidemiological forecasting. Additionally, he explores climate-health interactions within environmental epidemiology. To ensure that his predictive models - including deep learning approaches for public health data - remain transparent and actionable, he actively incorporates Explainable AI (XAI) and interpretable machine learning into his methodology.
Awards and Distinctions
- Dean’s List Award, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division of King Abdullah University of Science and Technology (KAUST), 2025
- Excellent Graduate, Harbin Institute of Technology (HIT), 2022
- Excellent Graduate, Harbin Institute of Technology (HIT), 2020
Education
- Master of Science (M.S.)
- Computer Science and Technology, Harbin Institute of Technology (HIT), China, 2022
- Bachelor of Engineering (B.Eng.)
- Computer Science and Technology, Harbin Institute of Technology (HIT), China, 2020
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