Xindi (Cindy) Hu

Xindi (Cindy) Hu, ScD, MS, is an environmental data scientist and serves as an Assistant Professor in the Department of Environmental and Occupational Health at the George Washington University Milken Institute School of Public Health. Dr. Hu's research aims to understand the relative contribution of chemical exposures in environmental media on population health outcomes and health disparities and generate evidence at a large scale. To achieve this, she employs a multidisciplinary approach encompassing exposure science, geospatial data science, and health informatics. Through collaborations established in academic and applied policy research settings, she develops machine learning techniques for modeling human exposure to drinking water contaminants (PFAS) through a place-based approach. She also leverages healthcare big data, including insurance enrollment, claims data, and EHR, to discern patterns in healthcare utilization and costs at the national scale in a variety of projects, including tracking community-level drug abuse and COVID-19 burden using wastewater-based epidemiology, causally assessing the impact of heatwaves on the vulnerable population, and utilizing machine learning techniques to predict the risk of long COVID.

Prior to joining the George Washington University faculty in 2024, Dr. Hu was a Principal Data Scientist and the Chief Data Scientist of the Health Data Innovation Lab at Mathematica, Inc., a public policy research organization with the mission to improve public well-being. She established and expanded Mathematica’s environmental health research portfolio through program development and fundraising, including leading the development of several award-winning dashboards such as 19andMe and ClimaWATCH.

In addition to her research, Dr. Hu is deeply committed to inspiring the next generation of public health leaders through teaching and mentoring. Throughout her academic journey and professional career, she mentored a diverse group of students and junior data scientists. Several of them have had the opportunity to present their research at academic conferences, publish manuscripts in reputable journals, and pursue doctoral-level training. Her unique background in data science and environmental health has inspired her students and mentees to leverage advancement in artificial intelligence and machine learning for the public good.