Lydia T. Liu

I am assistant professor of Computer Science at Princeton University. Currently, I am most interested in the scientific and normative foundations of machine learning and algorithmic decision-making, with a focus on societal impact and welfare outcomes.

I obtained my Ph.D. in Electrical Engineering and Computer Sciences from University of California, Berkeley, in May 2022, advised by Moritz Hardt and Michael I. Jordan. In 2022-2023, I was a postdoctoral associate at Cornell University Computer Science, working with Jon Kleinberg, Karen Levy, and Solon Barocas in the Artificial Intelligence, Policy, and Practice (AIPP) initiative.

I am the recepient of an Amazon Research Award, a Microsoft Ada Lovelace Fellowship, an Open Philanthropy AI Fellowship, an NUS Development Grant, and an ICML Best Paper Award.

Prospective Students and Postdocs

Please read this page before reaching out. Thank you.

Selected Publications

• Lydia T. Liu, Solon Barocas, Jon Kleinberg, Karen Levy.
  On the Actionability of Outcome Prediction.
  Proceedings of the AAAI conference on Artificial Intelligence, to appear (2024). [arxiv]
  Research Summary featured by the Montreal AI Ethics Institute.

• Lydia T. Liu^*, Serena Wang^*, Tolani Britton^{^}, Rediet Abebe^{^}.
  Reimagining the Machine Learning Life Cycle to Improve Educational Outcomes of Students.
  Proceedings of the National Academy of Sciences 120.9 (2023): e2204781120. [arxiv]

• Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt.
  Delayed Impact of Fair Machine Learning.
  Proceedings of the 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, 2018. [arxiv]

News

This fall at Princeton I am teaching a new COS graduate seminar on “AI, Society, and Education”, focusing on intervention design and evaluation science for AI in education and broadly related societal applications.

My work as a poet.

Email: ltliu_at_princeton_dot_edu