I am a T32 Postdoctoral Research Fellow on Substance Use Disorders at the Center for Population Health Sciences and Department of Psychiatry and Behavioral Sciences at Stanford University. I am also a Visiting Scholar at the Harvard FXB Center for Health and Human Rights. I received my doctorate from Harvard TH Chan School of Public Health in Quantitative Methods from the Department of Social and Behavioral Sciences, and I was a 2016 fellow at University of Chicago’s Data Science for Social Good summer fellowship.

My previous work involved using individual-level multimodal data (e.g., smartphone-based digital phenotyping data from various sensors), microlevel administrative data (e.g., death certificates), and third-party data (e.g., human mobility across mobile phone carriers) with spatial modeling, Bayesian methods, and data science to measure, model, and understand health disparities.

I currently have three streams of research. At Stanford, I’m working with Keith Humphreys and the Shah Lab to use machine learning and causal inference on large electronic medical records to understand racial/ethnic disparities in fatal drug overdoses and treatment of substance use disorder. With Harvard FXB, I am examining the effects of wildfires, climate change, and public safety power shutoffs on medically-vulnerable populations. Lastly, with the COVID-19 Mobility Data Network, I am helping technology companies and infectious disease researchers use third-party phone-based location data to understand and measure the impact of non-pharmaceutical interventions on the epidemic spread of COVID-19.

A recent copy of my CV is available here, my Stanford Profile is here, and my ORCiD iD is here.

Publications

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Conference Materials

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Teaching

Social

*Not peer-reviewed.
^†Authors contributed equally.
^‡Best student poster award.