David Liu
PhD Student
Research interests
- Algorithmic Fairness
- Explainable AI
- Computational Reproducibility
Education
- BSE in Computer Science with Certificate in Statistics and Machine Learning, Princeton University
Recent publications
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When Collaborative Filtering is not Collaborative: Unfairness of PCA for Recommendations
Citation: David Liu , Jackie Baek, Tina Eliassi-Rad. (2025). When Collaborative Filtering is not Collaborative: Unfairness of PCA for Recommendations FAccT, 2974-2990. https://doi.org/10.1145/3715275.3732190 -
Examining Responsibility and Deliberation in AI Impact Statements and Ethics Reviews
Citation: D. Liu, P. Nanayakkara, S. Sakha, G. Abuhamad, S.L. Blodgett, N. Diakopoulos, J. Hullman, T. Eliassi-Rad. Examining Responsibility and Deliberation in AI Impact Statements and Ethics Reviews. In Proceedings of the 2022 AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES), August 2022. -
Successes and Struggles with Computational Reproducibility: Lessons from the Fragile Families Challenge
Citation: Liu, David M., and Matthew J. Salganik. “Successes and Struggles with Computational Reproducibility: Lessons from the Fragile Families Challenge.” Socius, (January 2019). doi:10.1177/2378023119849803
