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.

Contact

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

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Miscellaneous

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