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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.
Please read this page before reaching out. Thank you.
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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]
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.
Email: ltliu_at_princeton_dot_edu