Aleksandra profile picture

I am an Assistant Professor of Computer Science and Public Affairs at Princeton University. I'm also excited to be part of Princeton's Center for Information Technology Policy.

I study societal impacts of algorithms, machine learning and AI, and develop and deploy algorithms and technologies that enable data-driven innovations while preserving privacy, fairness and robustness. I also design and perform AI audits.

Contact

korolova@princeton.edu

309 Sherrerd Hall, Princeton, NJ 08540

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Join my Group

Reach out by email if you would like to collaborate.

Prospective Ph.D. students should apply to the Ph.D. program in the Department of Computer Science or in the School of Public and International Affairs and indicate an interest in working with me in your statement.

Prospective postdocs should apply to CITP's Fellows Program and reach out to me directly.

News and updates

Feb
2026
:

Looking forward to attending IASEAI 2026, and discussing my group's forthcoming paper, "Measuring Validity and Fairness in LLM-based Resume Screening".

Oct
2025
:

Excited to welcome Blossom Metevier, Max Springer, Hayoung Jung, Bohdan Turbal, and Anderson Lee to my research group!

Oct
2025
:

Congratulations to Zeyu on two papers at NeurIPS 2025: ReliabilityRAG and LiveCodeBench Pro (one of a few benchmarks cited by Gemini 3 Pro in its eval).

Sep
2025
:

Congratulations to Jane on being named a 2026 Siebel Scholar!

Sep
2025
:

New undergraduate minor in Computing, Society and Policy, which I direct, is available for enrollment.

Research

Privacy, algorithmic fairness, accountability and transparency are currently at the center of key debates across academia, industry and policy. My research sits at the intersection of these topics and aims to leverage algorithmic thinking in order to provide new solution spaces that allow for a better balance between individual interests, societal goals, and technical innovation.

I develop algorithmic and systems advances that can enable data-driven innovations while preserving individual privacy, defined in the paradigm of differential privacy.

I work to understand how opaque AI systems (including generative AI) may be affecting individuals and society, and to develop algorithmic techniques for mitigating their negative consequences.

Read Research Statement

Recent Publications

An External Fairness Evaluation of LinkedIn Talent Search
Tina Behzad, Siddartha Devic, Vatsal Sharan, Aleksandra Korolova, David Kempe

Proceedings of the 40th Annual AAAI Conference on Artificial Intelligence (AAAI 2026).

Selected for oral presentation at the Special Track on AI for Social Impact.

Press
ReliabilityRAG: Effective and Provably Robust Defense for RAG-based Web-Search
Zeyu Shen, Basileal Imana, Tong Wu, Chong Xiang, Prateek Mittal, Aleksandra Korolova

Proceedings of the 39th Annual Conference on Neural Information Processing Systems (NeurIPS 2025).

Press
External Evaluation of Discrimination Mitigation Efforts in Meta’s Ad Delivery
Basileal Imana, Zeyu Shen, John Heidemann, and Aleksandra Korolova

Proceedings of ACM Conference on Fairness, Accountability, and Transparency (FAccT 2025).

In Privacy Law Scholars Conference (PLSC 2025).

Best Paper Award (FAccT 2025).

Press
See All Publications

Privacy

fairness