Elizabeth (Liz) Chin

PhD Candidate @ Stanford

I am a PhD candidate in the Department of Biomedical Data Science at Stanford University, advised by Euan Ashley and Trevor Hastie. My research focuses on promoting health equity by addressing disparities in chronic illness and mass incarceration. My work centers around integrating data from disparate sources using a variety of quantitative approaches such as machine learning, simulations, and inference.

I am interested in occupational, socioeconomic, and racial inequities and their relation to public health. My most recent projects include (1) Modeling interventions and analyzing COVID-19 response in California Prisons [NEJM, medRxiv, medRxiv] (2) Projected geographic disparities in healthcare worker absenteeism from COVID-19 school closures [PubMed] (3) Testing for COVID-19 in high-risk environments [CID, Lancet ID].

I am grateful for the support of the Stanford Graduate Fellowship and the National Science Foundation Graduate Fellowship. Before coming to Stanford, I obtained my Bachelor of Science in Applied Mathematics at the University of California Los Angeles, where I was fortunate to conduct computational genomics research under the advisement of Xinshu (Grace) Xiao. As an undergraduate, I was also honored to conduct research with Rachel Martin, Carter Butts, and Pardis Sabeti as part of NSF REU and Harvard Systems Biology Summer Research Programs. I have also worked on machine learning/data science teams at Adobe Systems and Quora.

If you’re interested in my work or share interests, don’t hesitate to reach out. You can contact me at etchin at stanford.edu.

Recent press coverage:

• Vaccine acceptance in California prisons: SF Chronicle
• Testing for Covid-19 in high-risk environments: NPR, SF Chronicle