Draft:Aleksandra Korolova

Aleksandra Korolova is a Latvian - American Computer Scientist. She is an Assistant Professor of Computer Science and Public Affairs at Princeton University and Associated Faculty at Princeton's Center for Information Technology Policy. Her research develops privacy-preserving and fair algorithms, studies individual and societal impacts of machine learning and AI, and performs AI audits for algorithmic bias.

Privacy
Korolova's research has been one of the first to identify privacy vulnerabilities in targeted advertising systems.

Korolova's work led to the first industry deployment of differential privacy, Google's RAPPOR, demonstrating its feasibility in the  local model.

Algorithmic Fairness
Korolova developed new black-box audit methodologies for isolating the role of ad delivery algorithms from other confounding factors. Her application of these methodologies demonstrated that Facebook's ad delivery algorithms lead to discriminatory outcomes in housing and employment advertising and to a filter bubble in political ad delivery.

Recognition
Korolova's Ph.D. thesis titled "Protecting Privacy when Mining and Sharing User Data" won the Arthur Samuel Award for outstanding Computer Science Ph.D. thesis at Stanford University.

Korolova's work on demonstrating privacy vulnerabilities due to microtargeted advertising was recognized by the 2011 PET Award for Outstanding Research in Privacy Enhancing Technologies.

Korolova's work on discrimination through ad delivery received an Honorable Mention at the CSCW conference in 2019.

She is the recipient of the 2020 National Science Foundation CAREER Award.

Korolova was awarded the 2024 Sloan Research Fellowship in Computer Science

She won bronze medals at the 1998 and 2000 International Mathematics Olympiad.