Biostatistics

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 andRead more

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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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Tan Bee Huat, Iain

Associate Professor (Joint) Tel (65) 6436 8574 Email iain.tan.b.h@singhealth.com.sg TAN Bee Huat, Iain I am a senior consultant medical oncologist and Director of research at the Division of Medical Oncology at National Cancer Centre Singapore. I am also the platform lead for databases and biobanks at the Singapore Translational Cancer Consortium (STCC) under CRIS,MOH. I take the lead on population health research & innovation at National Cancer Centre Singapore. We are creating the national cancer dataset based as the cancer data commons within Singapore Translational Cancer Consortium (STCC) in collaboration

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SHOU Yiyun

Assistant Professor (Research) Email Yiyun.shou@nus.edu.sg SHOU YiyunAffiliation NUS Saw Swee Hock School of Public Health (Joint) Lloyd’s Register Foundation Institute for the Public Understanding of Risk (Joint) Research Areas Judgment and decision making Risk and uncertainty attitudes Cross-cultural measurement Risk and health communication Academic/Professional Qualifications PhD in Psychology, Australian National University BSc (Hons), Australian National University Career History Senior Research Fellow, Australian National University ARC DECRA Fellow, Australian National University Postdoctoral Research Associate, Australian National University Selected Publications Shou, Y., Smithson, M., Gulliver A., Murray, K., Banfield M., Harris, R., McCallum,

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WU David Bin-Chia

Assistant Professor (Adjunct) Email david.wu@nus.edu.sg WU David Bin-Chia Dr Wu is the Regional Director of Real World Evidence (RWE) & Health Economics (HE) in Market Access (Asia Pacific) at Johnson & Johnson Innovative Medicine. In this role, he is responsible for guiding cross-functional RWE strategy and tactics and HE to support market access, e.g. health technology assessment (HTA) submission and commercialization across product life cycle and all therapeutic areas. Dr. Wu's collaborative efforts extend globally, with partnerships formed with prestigious institutions such as the World Health Organization, the National Institutes of

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MO Yin

Senior Lecturer (Joint) Email mdcmy@nus.edu.sg MO Yin Dr Mo Yin is driven by the ideal of using quality clinical research to influence patient care and propel health policies. She has been active in clinical research, medical education, as well as hospital administration. She has received numerous awards for her achievements in clinical care, research and teaching. Dr Mo Yin’s career goal is to serve her community focusing on translational research to influence regional and global policies. Affiliation NUS Saw Swee Hock School of Public Health (Joint) NUS Yong Loo Lin

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Zaw Myo TUN

Research Fellow (Adjunct) Email zawmyo.tun@ird.global Zaw Myo TUNAffiliation NUS Saw Swee Hock School of Public Health (Adjunct) Senior Manager (Research and Evaluation), IRD Global Singapore (Primary) Research Areas Epidemiology Global Health Tuberculosis Vaccines Teaching Areas Public health and epidemiology Academic/Professional Qualifications PhD (2016-2021), Saw Swee Hock School of Public Health, National University of Singapore MSc Epidemiology (2011-2012), London School of Hygiene & Tropical Medicine MBBS (2003-2008), University of Medicine, Mandalay, Myanmar Career History Postdoctoral Fellow, Saw Swee Hock School of Public Health (2022) Research Associate, Saw Swee Hock School of

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ZHU Junxian

Research Fellow Email junxian@nus.edu.sg ZHU JunxianAffiliation NUS Saw Swee Hock School of Public Health Research Areas Best-Subset Selection GWAS Non-compliance in randomised clinical trials Academic/Professional Qualifications Bachelor (Statistics), Sun Yat-Sen University PhD (Statistics), Sun Yat-Sen University Selected Publications Junxian Zhu, Canhong Wen, Jin Zhu, Xueqin Wang and Heping Zhang. A Polynomial Algorithm for Best-subset Selection Problem. Proceedings of the National Academy of Sciences. 2020, 117 (52), 33117-33123; DOI: 10.1073/pnas.2014241117. Junxian Zhu, Qiao Fan, Wenying Deng, Yimeng Wang and Xiaobo Guo. BTOB: Extending the biased GWAS to bivariate GWAS. Frontiers in

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Caro Jaime

CARO J. Jaime

Honorary Visiting Professor Email jaime.caro@mcgill.ca CARO J. Jaime I trained in medicine and epidemiology at McGill University but early on focused on health technology assessment. Most of my work is on methods development and teaching these new approaches. For Germany’s IQWiG, I proposed the use of efficiency frontiers as they rejected using the QALY. Recently, I have developed the DICE simulation method, a unified approach to modeling that enables rapid, standardized and less error-prone forecasting models. Work on a broader approach than QALYs to value health benefits is ongoing. Leveraging mixed

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