I am a WiSE Gabilan Assistant Professor of Computer Science at USC. Previously, I was a Research Scientist at Google, a Privacy Advisor at Snap, and a Ph.D. student in Computer Science at Stanford.
My research develops and deploys algorithms and technologies that enable data-driven innovations while preserving privacy and fairness. I also study and address the societal implications of algorithms and machine learning.
Current PC(s) and Service: Member of the Design Committee for OpenDP, a community effort to build tools for enabling privacy-protective analysis of sensitive data. Steering Committee of the National Academies of Sciences, Engineering and Medicine for “Challenges and New Approaches for Protecting Privacy in Federal Statistical Programs” (2019).
News: Recipient of the NSF 2020 CAREER Award. Received a Security and Privacy Research Award for research on differential privacy from Google, a Mozilla Research grant for studying ad preference controls, an NSF SaTC Medium for "Understanding the Privacy and Societal Risks of Advanced Advertising Targeting and Tracking", and an NSF SaTC Frontiers for "Protecting Personal Data Flow on the Internet". Selected as a VMware Research Fellow for “Data Privacy: Foundations and Applications” at the Simons Institute (see my recent talk on "Societal Concerns in Targeted Advertising"). Invited Speaker for WSDM 2019 and Trustworthy AI Symposium.
Prospective Students: I have open PhD and post-doc positions for motivated students with an interest in privacy, algorithmic fairness, and societal implications of AI.
Basileal Imana, Aleksandra Korolova, John Heidemann
To appear in The Web Conference (WWW 2021)
Muhammad Ali, Piotr Sapiezynski, Aleksandra Korolova, Alan Mislove, Aaron Rieke
To appear in Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM 2021)
Popular press: Washington Post, Wired, New Scientist, Daily Mail, Daily Dot, Science Blog
Michael P. Kim, Aleksandra Korolova, Guy N. Rothblum, Gal Yona
Proceedings of 11th Conference on Innovations in Theoretical Computer Science (ITCS 2020)
Proceedings of 3rd ACM Conference on Fairness, Accountability, and Transparency (FAT* 2020)
Peter Kairouz, H. Brendan McMahan, Brendan Avent, [27 others], Aleksandra Korolova, [27 others]
To appear in Foundations and Trends in Machine Learning (2021)
Muhammad Ali, Piotr Sapiezynski, Miranda Bogen, Aleksandra Korolova, Alan Mislove, Aaron Rieke
Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW 2019)
CSCW Honorable Mention Award, CSCW Recognition of Contribution to Diversity and Inclusion,
Cited in Facebook's Civil Rights Audit Report
Presentation at FTC PrivacyCon (2020)
Popular press: The Intercept, The Economist, Wired, The Hill, Motherboard, Reuters, Business Insider, The Verge,
NBC News, US News, Fast Company, Quartz, WSJ, The Register, MIT Technology Review, The Atlantic, Vox (video).
Amos Beimel, Aleksandra Korolova, Kobbi Nissim, Or Sheffet, Uri Stemmer
Proceedings of Conference on Information-Theoretic Cryptography (ITC 2020)
Privacy in Machine Learning Workshop @ NeurIPS (2019)
Brendan Avent, Yatharth Dubey, Aleksandra Korolova
Proceedings of the 20th Privacy Enhancing Technologies Symposium (PETS 2020)
Selected for presentation Privacy in Machine Learning Workshop @NeurIPS (2018)
Irfan Faizullabhoy, Aleksandra Korolova
Workshop on Technology and Consumer Protection (ConPro) @S&P (2018)
Poster at FTC PrivacyCon (2018)
Popular press: Gizmodo, Business Insider, The Guardian
Guillermo Baltra, Basileal Imana, Wuxuan Jiang, Aleksandra Korolova
Workshop on Technology and Consumer Protection (ConPro) @S&P (2020)
Vasyl Pihur, Aleksandra Korolova, Frederick Liu, Subhash Sankuratripati, Moti Yung, Dachuan Huang, Ruogu Zeng
Privacy in Machine Learning and Artificial Intelligence Workshop @ICML (2018)
4th Workshop on the Theory and Practice of Differential Privacy @CCS (2018)
Deployed by Snap
Jun Tang, Aleksandra Korolova, Xiaolong Bai, Xueqiang Wang, Xiaofeng Wang
3rd Workshop on the Theory and Practice of Differential Privacy @CCS (2017)
Popular press: Wired, EFF
Brendan Avent, Aleksandra Korolova, David Zeber, Torgeir Hovden, Benjamin Livshits [bibtex, slides, video]
26th USENIX Security Symposium (2017)
Journal of Privacy and Confidentiality Vol. 9 (2) (2019)
Selected for presentation in Private and Secure Machine Learning Workshop @ICML (2017)
Selected for presentation in 3rd Workshop on the Theory and Practice of Differential Privacy @CCS (2017)
William Brendel, Fangqiu Han, Luis Marujo, Luo Jie, Aleksandra Korolova
Poster in The Web Conference (WWW 2018)
Aleksandra Korolova, Vinod Sharma
8th ACM Conference on Data and Application Security and Privacy (Codaspy'2018)
FTC PrivacyCon (2017)
[video (starting at 0:30:35)]
Basileal Imana, Aleksandra Korolova, John Heidemann
NDSS Workshop on DNS Privacy (DNSPRIV '2018)
Abdulaziz Alhadlaq, Jun Tang, Marwan Almaymoni, Aleksandra Korolova
10th Workshop on Hot Topics in Privacy Enhancing Technologies (HotPETS'2017 )
Sai Teja Peddinti, Aleksandra Korolova, Elie Bursztein, Geetanjali Sampemane [bibtex]
IEEE Symposium on Security & Privacy (S&P'2014)
Invited to Special Issue of IEEE Security and Privacy Magazine (2015)
Úlfar Erlingsson, Vasyl Pihur, Aleksandra Korolova [bibtex]
21st ACM Conference on Computer and Communications Security (CCS'2014)
Runner up for the 2015 PET Award
Popular press: Google Research Blog, ComputerWorld, CNET, CDT, The Economist, MIT Technology Review
Krishnaram Kenthapadi, Aleksandra Korolova, Ilya Mironov, Nina Mishra [bibtex]
Journal of Privacy and Confidentiality, Volume 5, Issue 1, Pages 39-71 (2013)
Ph.D. Thesis [bibtex]
Winner of the 2011-2012 Arthur L. Samuel Thesis Award,
for the best Ph.D. thesis in the Computer Science department at Stanford.
Aleksandra Korolova [bibtex]
Journal of Privacy and Confidentiality, Volume 3, Issue 1, Pages 27-49 (2011)
Workshop version in IEEE International Workshop on Privacy Aspects of Data Mining (PADM ’2010)
Co-winner of the 2011 PET Award [Press release]
Popular press: New York Times, Gawker
Ashwin Machanavajjhala, Aleksandra Korolova, Atish Das Sarma [bibtex]
37th International Conference on Very Large Databases (VLDB ’2011)
Popular press: MIT Technology Review (arXiv Blog)
Aleksandra Korolova, Krishnaram Kenthapadi, Nina Mishra, Alexandros Ntoulas [bibtex]
18th International World Wide Web Conference (WWW ’2009)
Nominated for Best Paper Award
Popular press: Microsoft Research, New Scientist
Aleksandra Korolova, Rajeev Motwani, Shubha U. Nabar, Ying Xu [bibtex]
ACM 17th Conference on Information and Knowledge Management (CIKM ’2008)
Poster version in 24th International Conference on Data Engineering (ICDE ’2008)
Popular press: ACM Crossroads Magazine
Aleksandra Korolova, Ayman Farahat, Philippe Golle [bibtex]
14th International World Wide Web Conference (WWW ’2005)
Aleksandra Korolova [bibtex]
Discrete Mathematics, Volume 292, Issues 1-3, Pages 107-117 (March 2005)
I received my Ph.D. in Computer Science from Stanford, where I was a Cisco Systems Stanford Graduate Fellow advised by Prof. Rajeev Motwani (RIP, Rajeev) and Prof. Ashish Goel. My Ph.D. thesis focused on protecting privacy when mining and sharing user data, and has been recognized by 2011-2012 Arthur L. Samuel Thesis Award for the best Ph.D. thesis in the Computer Science department at Stanford.
While at Stanford, I was fortunate to intern at Microsoft Research, Facebook, Yahoo! Research, and PARC.
I grew up in Latvia and graduated from Riga secondary school #40, spending fun weekends preparing for math olympiads at NMS and learning algorithms at Progmeistars. I am indebted for the many opportunities I have had to my family, amazing teachers at the above institutions, and to the George Soros Foundation. My outstanding high school mathematics teacher, Viktor Glukhov, now teaches and organizes math circles in London. If you visit or live in Riga, rent an apartment or office space in the center of Riga.
I loved spending my college years at MIT, and especially enjoyed the classes taught by Prof. Patrick Winston. I first tried doing research in Dan Spielman's error-correcting codes class and Joe Gallian's Duluth REU. At Stanford, I enjoyed learning randomized algorithms, algorithmic game theory, cognitive science and design thinking. I also had fun advocating for graduate student interests as part of the Graduate Student Council, and serving as a mentor and Center for Teaching and Learning liason for Computer Science TAs.
In my free time, I enjoy traveling, skiing, and playing tennis.
I proudly support MEET, MIT, EFF, and The Markup.