Xiao Wu
Scholar

Xiao Wu

Google Scholar ID: VJeJSyAAAAAJ
Columbia University
Causal InferenceBiostatisticsData ScienceMachine LearningClimate and Health
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Citations & Impact
All-time
Citations
4,670
 
H-index
23
 
i10-index
31
 
Publications
20
 
Co-authors
0
 
Contact
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Publications
20 items
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
  • - Published papers in prestigious journals such as Science, New England Journal of Medicine, Lancet Planetary Health, and Journal of the American Statistical Association
  • - Named to Forbes 30 Under 30 - Healthcare (2022)
  • - Calderone Junior Faculty Award (April 2024)
  • - Stanford Data Science Fellowship (October 2021 - December 2022)
  • - Barry R. and Irene Tilenius Bloom Fellowship (March 2021)
Research Experience
  • - Quantitative Researcher at Meta
  • - Assistant Professor of Biostatistics at Columbia University
  • - Data Science Postdoctoral Fellow at Stanford University (2021-2022), working with Dr. Trevor Hastie in Statistics
  • - Collaborative projects to design clinical trials, meta-analyses, and real-world evidence studies
Education
  • - Ph.D. in Biostatistics, Harvard University (2021), advised by Dr. Francesca Dominici and Dr. Danielle Braun
  • - M.S. in Biostatistics, Harvard T.H. Chan School of Public Health (2017)
  • - LL.B. in Laws, B.S. in Mathematics, Peking University (2015)
Background
  • - Research Interests: Causal Inference, Statistical Learning, Environmental Biostatistics, Data Science, Wearable Health and AI
  • - Professional Field: Biostatistics, Data Science
  • - Biography: Xiao Wu is a Quantitative Scientist at Meta and an Assistant Professor of Biostatistics at Columbia University, as well as a member of Columbia Data Science Institute. His research focuses on developing statistical, machine learning, and causal inference methods to address methodological needs in health research. He aims to provide scientific evidence and policy solutions to mitigate the adverse impacts of environmental factors under rapidly evolving natural and societal conditions.
Miscellany
  • - Personal Interests: Harnessing the power of data science to build a healthier, more sustainable world
Co-authors
0 total
Co-authors: 0 (list not available)