Biostatistics

HUANG Jingyan

Research Fellow Email  jy.huang@nus.edu.sg HUANG Jingyan Jingyan is interested in infectious disease modelling with Bayesian modelling and Renewal Processes. Her PhD research focused on change-point detection, sequential testing and high-dimensional time-series analysis. Affiliation NUS Saw Swee Hock School of Public Health Research Areas Infectious disease modelling Bayesian modelling Renewal processes Change-point detection Sequential testing Academic/Professional Qualifications BSc in Statistics, Hong Kong Baptist University PhD in Statistics, National University of Singapore Career History Research Fellow, National University of Singapore. 2023 - Present Selected Publications Hu, S., Huang, J., Chen, H., Chan, H.Read more

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DU, Hao

Research Fellow Email ephdh@nus.edu.sg DU, Hao Dr. Du Hao currently serves as a research fellow at NUS Saw Swee Hock School of Public Health. His research interests primarily revolve around model development and clinical validation for machine learning and deep learning in medical data. Additionally, Dr. Du Hao is an entrepreneur who specializes in MedTech startups, with a focus on applying artificial intelligence models in medical devices and clinical applications. Affiliation NUS Saw Swee Hock School of Public Health Research Areas Design, conduct and analysis of clinical validation and trials

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CHUNG The Hao

Visiting Senior Research Fellow Email haoct@nus.edu.sg CHUNG The Hao Dr. Hao is a trained microbiologist fascinated at how microbes evolve and interact with human. His research seeks to combine high-resolution genomic data and clinical studies to answer relevant public health questions on infectious diseases epidemiology and evolution, and to translate understandings on bacterial evolution and ecology into better approaches in healthcare. Affiliation NUS Saw Swee Hock School of Public Health Oxford University Clinical Research Unit, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford Research

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PHUNG, Khanh Lam

Senior Research Fellow Email lampk@nus.edu.sg PHUNG, Khanh Lam I am a general medical doctor by training but then obtained a Ph.D. with a quantitative focus on developing clinical prediction models in dengue and have spent most of my research career working as a biostatistician. With colleagues at the Oxford University Clinical Research Unit in Vietnam, I conducted various collaborative works on dengue infection, ranging from observational studies to randomized clinical trials, to improve our understanding of the pathophysiology of dengue and the efficacy of different potential therapeutic options for dengue

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ROY Mousumi

Research fellow Email mou.roy@nus.edu.sg ROY Mousumi My research falls within the intersection of infectious disease modeling, human mobility, and Bayesian statistics. I am working with complex pattern of disease transmission by analyzing various factors involving the transmission. Affiliation NUS Saw Swee Hock School of Public Health Research Areas Infectious disease modelling Human mobility pattern Network science Academic/Professional Qualifications M.Sc. (Applied Mathematics), University of Calcutta, 2014 Ph.D. (Applied Mathematics), University of Calcutta, 2022 Selected Publications M Roy, S Mandal, C Hens, A Prasad, NV Kuznetsov, M Dev Shrimali. Model-free prediction of

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JIN Shihui

Research Fellow Email jinshihui@nus.edu.sg JIN Shihui Shihui is interested in infectious disease modelling with mathematical and statistical methods. Her PhD research focused on modelling the transmission dynamics and forecasting outbreaks of SARS-CoV-2. Affiliation NUS Saw Swee Hock School of Public Health Research Areas Infectious disease modelling Wastewater epidemiology Vaccine confidence Academic/Professional Qualifications PhD in Statistics, National University of Singapore, Singapore in Mathematics, Nanjing University, China Career History Research Fellow, National University of Singapore. 2023–Present Selected Publications Jin, S., Dickens, B. L., Quek, A. M., Hartman, M., Tambyah, P. A., Seet,

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ENDO Akira

Assistant Professor Email aendo@nus.edu.sg ENDO Akira Dr Akira Endo is an Assistant Professor at the NUS Saw Swee Hock School of Public Health. His research focuses on mathematical modelling of infectious disease dynamics in the population. Compared with other types of diseases, infectious diseases are unique in that protecting an individual from a disease also means protecting other people by reducing their risk of exposure to the pathogen. This “interdependency” makes the control of infectious disease outbreaks an important social agenda. His current research interests include disease spread within and

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Chandra Prakash YADAV

Research Fellow Email chandrap@nus.edu.sg Chandra Prakash YADAV I am a statistician experienced in collaborative work alongside clinicians and health economists. My expertise spans Bayesian methods, handling censored/incomplete data, managing competing risks, and analyzing longitudinal data. My research centers on harnessing comprehensive electronic health records, large-scale observational studies, and clinical trials. Through these avenues, I investigate real-world healthcare service utilization, evaluate the economic impact of chronic conditions, and build advanced machine learning models for predicting clinical risks and treatment outcomes. My passion lies in comparative and cost-effectiveness research, where I assess

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HUANG Ling

Research Fellow Email huang.l@nus.edu.sg HUANG Ling Huang Ling is now a research fellow in NUS Saw Swee Hock School of Public Health interested. She is interested in trust and explainable AI with the application of deep learning and evidence theory for imperfect (uncertain and imprecise) medical data analysis. Affiliation NUS Saw Swee Hock School of Public Health Research Areas Trusted and explainable Biomedical AI, Uncertainty modelling, evidential reasoning, information fusion, machine learning, deep learning Academic/Professional Qualifications Ph.D , Université de Technologie de Compiègne, France, 2019-2023 M.Sc. Zhejiang Universite of Technology,

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MISHRA Swapnil

Assistant Professor Email s.mishra@nus.edu.sg MISHRA Swapnil Dr. Swapnil Mishra is primarily working at the intersection of global health, machine learning and Bayesian modelling. His research focuses on applying and developing statistical machine learning techniques for the broader and messier world of science and public policy, especially global health. He develops flexible and scalable models for understanding various spatiotemporal data, for example, epidemics (COVID-19, Malaria, HIV) and crime. He co-founded “Machine Learning & Global Health Network” with researchers from Imperial College London, University of Oxford, Technical University of Kaiserslautern, and the

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