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Xiao Wu

Quantitative Researcher

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. A key milestone of his work is to provide scientific evidence and policy solutions to mitigate the adverse impacts of environmental factors under rapidly evolving natural and societal conditions. He is also interested in health technologies and AI applications with innovative wearable devices. Contact me if you want to harness the power of data science to build a healthier, more sustainable world!

He completed his Ph.D. in Biostatistics at Harvard University, where he was advised by Dr. Francesca Dominici and Dr. Danielle Braun. His dissertation focuses on developing causal inference methods to handle error-prone, continuous, and time-series exposures. He was a Data Science Postdoctoral Fellow at Stanford University, where he worked with Dr. Trevor Hastie in Statistics during 2021-2022. He is also working on collaborative projects to design clinical trials, meta-analyses, and real-world evidence studies.

He has been named to Forbes 30 Under 30 list. His research has been published in prestigious scientific venues such as Science, New England Journal of Medicine, Lancet Planetary Health, and Journal of the American Statistical Association, and it has attracted the attention of international journalism, including at the New York Times, the Guardian, National Geographic, USA Today, Scientific American, and Financial Times.

Interests

• Causal Inference
• Statistical Learning
• Environmental Biostatistics
• Data Science
• Wearable Health and AI

Education

• Ph.D. in Biostatistics, 2021

  Harvard University

• M.S. in Biostatistics, 2017

  Harvard T.H. Chan School of Public Health

• LL.B. in Laws, B.S. in Mathematics, 2015

  Peking University

Awards

Calderone Junior Faculty Award

Columbia University Mailman School of Public Health Apr 2024

2022 Forbes 30 Under 30 - Healthcare

Forbes Dec 2021

Stanford Data Science Fellowship

Stanford University Oct 2021 – Dec 2022

Barry R. and Irene Tilenius Bloom Fellowship

Harvard T.H. Chan School of Public Health Mar 2021Featured PublicationsXiaodi Zhang, Haiqing Liu, Xiao Wu, Longgang Jia, …, Ted M. Dawson, Shizhong Han, Xiaobo Mao (2025). Lewy body dementia promotion by air pollutants. Science.

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Xiao Wu, Kate R Weinberger, Gregory A Wellenius, Francesca Dominici, Danielle Braun (2024). Assessing the causal effects of a stochastic intervention in time series data: Are heat alerts effective in preventing deaths and hospitalizations?. Biostatistics.

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Xiao Wu, Fabrizia Mealli, Marianthi-Anna Kioumourtzoglou, Francesca Dominici, Danielle Braun (2024). Matching on generalized propensity scores with continuous exposures. Journal of the American Statistical Association.

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Xiao Wu, Erik Sverdrup, Michael D. Mastrandrea, Michael W. Wara, Stefan Wager (2023). Low-intensity fires mitigate the risk of high-intensity wildfires in California’s forests. Science Advances.

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Kevin P Josey, Scott W Delaney, Xiao Wu, Rachel C Nethery, Priyanka DeSouza, Danielle Braun, Francesca Dominici (2023). Air pollution and mortality at the intersection of race and social class. New England Journal of Medicine.

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Xiao Wu, Rachel C Nethery, M Benjamin Sabath, Danielle Braun, Francesca Dominici (2020). Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis. Science Advances.

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Liuhua Shi, Xiao Wu, Mahdieh Danesh Yazdi, Danielle Braun, Yara Abu Awad, Yaguang Wei, Pengfei Liu, Qian Di, Yun Wang, Joel Schwartz, Francesca Dominici, Marianthi-Anna Kioumourtzoglou, Antonella Zanobetti (2020). Long-term effects of PM2·5 on neurological disorders in the American Medicare population: a longitudinal cohort study. The Lancet Planetary Health.

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Xiao Wu, Danielle Braun, Joel Schwartz, Marianthi-Anna Kioumourtzoglou, Francesca Dominici (2020). Evaluating the impact of long-term exposure to fine particulate matter on mortality among the elderly. Science Advances.

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Xiao Wu, Yi Xu, Bradley P Carlin (2020). Optimizing interim analysis timing for Bayesian adaptive commensurate designs. Statistics in Medicine.

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Xiao Wu, Danielle Braun, Marianthi-Anna Kioumourtzoglou, Christine Choirat, Qian Di, Francesca Dominici (2019). Causal inference in the context of an error prone exposure: air pollution and mortality. The Annals of Applied Statistics.

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Joong-Ho Won, Xiao Wu, Sang Han Lee, Ying Lu (2017). Cross-sectional design with a short-term follow-up for prognostic imaging biomarkers. Computational Statistics & Data Analysis.

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Recent & Upcoming Talks

Exposure to air pollution and COVID-19 mortality in the United States

Aug 24, 2020 — Aug 27, 2020 Virtual

Impacts of Long-term Exposure to Fine Particulate Matter on Mortality Among the Elderly

Aug 24, 2020 — Aug 27, 2020 Virtual

Optimizing Interim Analysis Timing for Bayesian Adaptive Commensurate Designs

Sep 25, 2019 Washington Marriott Wardman Park

Matching on Generalized Propensity Scores with Continuous Treatments

Jul 31, 2019 Colorado Convention Center

Discussion on Causal Inference Challenges in Air Pollution Research

May 23, 2019 McGill UniversityExperience

Quantitative Scientist

Meta

Jul 2025 – Present New York, NY

Research Scientist Intern

Facebook

Jun 2020 – Aug 2020 Menlo Park, CA

Data Scientist Intern

Google

May 2019 – Aug 2019 Sunnyvale, CA

Biostatistician Intern

Sanofi Genzyme

Jun 2017 – Aug 2017 Cambridge, MAContactName Email Message Send

• 722 W 168th St, New York, NY 10032

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