Sarah Tan Hui Fen (Sarah) Tan
Google Scholar

I'm a PhD student at Cornell Statistics, minoring in Computer Science. I'm currently a visiting student at UCSF. Broadly, I work on interpretability of machine learning methods. I'm also interested in causal inference, healthcare applications, and algorithmic fairness.

I'm advised by Giles Hooker and Martin Wells, and Thorsten Joachims and Rich Caruana are on my committee. Previously, I studied at Berkeley and Columbia, and worked in public policy in NYC, including the health department and public hospitals system. In 2014, I was a Data Science for Social Good fellow. I spent summer 2015 at Xerox Research (now Naver Labs) and summers 2017 and 2018 at Microsoft Research, working with Rich Caruana. I'm on the board of the Women in Machine Learning organization.


I’m based in the SF Bay Area in 2018. You can reach me at ht395 AT cornell DOT edu.

I am on the job market! Here is a short cv. I will be attending NeurIPS in Montreal. Please reach out if you would like to meet.


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