Sarah Tan Hui Fen (Sarah) Tan
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I am a research scientist interested in algorithmic fairness, causal inference, interpretability, and healthcare. Currently, I work at Cambia Health on emerging aspects of machine learning, including responsible AI and large language models. I also hold a Visiting Scientist appointment at Cornell University. I co-founded the Trustworthy ML Initiative and am president of Women in Machine Learning (WiML).

I received my PhD in Statistics from Cornell University, where I was advised by Giles Hooker and Martin Wells, with Thorsten Joachims and Rich Caruana 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. I was also a Data Science for Social Good fellow. I was fortunate to spend summers at Microsoft Research, working with Rich Caruana, Kori Inkpen, and Ece Kamar. Towards the end of my PhD studies, I was a visiting student and bioinformatics programmer at UCSF medical school. I joined Facebook after completing my PhD, and worked in Core Data Science before moving to Responsible AI.


I’m currently based in Seattle. You can reach me at ht395 AT


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  • I played piano and (bad) ukulele in an Indian fusion carnatic band. We have some videos here