Sarah Tan Hui Fen (Sarah) Tan
Google Scholar

I am a researcher interested in algorithmic fairness, causal inference, interpretability, and healthcare. Currently, I am a Director in Responsible AI at Salesforce. 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


  • 5/24: I did a fireside chat in the University of Colorado Denver’s PUAD 6600 “AI for Public Sector Innovation” class.
  • 3/24: I gave a guest lecture on Ethics in Computer Vision at Stanford University’s CS131 “Computer Vision: Foundations and Applications” class.
  • 9/23: I was a panelist at Columbia Business School’s Challenges in Operationalizing Responsible AI workshop.
  • 7/23: I will be co-organizing a workshop at NeurIPS 2023 on Regulatable ML. Submit your paper!
  • 1/23: I have been elected president of the Women in Machine Learning organization (WiML).
  • 1/23: I will be the Tutorial Chair for FAccT 2023.
  • 9/21: I will be the Diversity & Inclusion Chair for AISTATS 2022.
  • 10/19: I gave a talk at Data & Society’s Meeting on Fair ML in Health about risk scoring models in healthcare.
  • 7/19: I had a blast helping out with UCSF’s AI4ALL program! I presented on dataset bias and helped mentor a project team using electronic medical records to predict opioid overdose and other conditions.
  • 3/19: I’m excited to help teach the new ML for biomedicine course at UCSF. This is perhaps the first official ML course at UCSF and I’m looking forward to teaching again!
  • 6/18: Honored to receive a Microsoft Research Dissertation Grant.
  • 6/17: Grateful to receive the American Statistical Association Wray Jackson Smith Award

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Code & Data

Publications and Preprints

Journal and Conference Papers


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