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.

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 (Summer 2024)

I am presenting work with my students and collaborators (Liu et al 2024, Raji and Liu 2024, Stroebl et al 2024) at the ICML 2024 Workshop on Humans, Algorithmic Decision-Making and Society: Modeling Interactions and Impact!
I will be an invited speaker at TTIC Workshop on Data-Driven Decision Processes: From Theory to Practice (August 26-28).

My work as a poet.

Email: ltliu_at_princeton_dot_edu