Aleksandra (Seša) Slavković is a Professor of Statistics and Associate Dean for Graduate Education in Eberly College of Science at Penn State.
She received her PhD (2004) and M.S. (2001) in Statistics, and a Master of Human-Computer Interaction (1999) from Carnegie Melon University. She received her B.A. in Psychology from Duquesne University (1996).
Her research interests include methodological developments in the area of data privacy and confidentiality in the context of small and large scale surveys, health, genomic, and network data. Her focus is on the interplay of tools from statistics and computer science that leads to formal privacy protection -such as differential privacy- and broad data access, but also offers guarantees of accurate statistical inference needed to support reliable science and policy. Other past and current research interests include evaluation methods for human performance in virtual environments, statistical data mining, application of statistics to information sciences and social sciences, algebraic statistics, and causal inference.
In her role as associate dean for graduate education, Slavković supports the enhancement of the graduate programs in her college and works closely with its office of diversity and inclusion to foster a positive climate for all members of the college. She also works with students and faculty to improve graduate student mentoring, and oversees the Science Achievement Graduate Fellows Program designed to recruit, recognize and promote outstanding students seeking a doctoral degree in each of the college’s seven departments and who have demonstrated interest in the advancement of women in sciences.
Slavković is the editor of Statistics and Public Policy, and associate editor of the Annals of Applied Statistics and Journal of Privacy and Confidentiality. She is a former chair of the American Statistical Association (ASA) Privacy and Confidentiality committee and the Social Statistics SectionFello. She currently serves on the NORC Advisory Committee on Statistics and has served on a number of National Academy of Sciences/National Research Council committees. She has held appointments at the Institute for Computational and Data Sciences at Penn State University since 2015, and at the Department of Public Health Sciences, Penn State College of Medicine, since 2010. She joined Penn State Statistics Department as an Assistant Professor in 2004. She has also held visiting scholar positions at Cornell University, University of California Berkeley, University of Minnesota and Utrecht University. In the statistics department she served as Associate Head for Diversity and Equity (2014-2017) and Associate Head for Graduate Studies (2013-2018)
Honors and Awards
- Fellow, The Institute of Mathematical Statistics (2021)
- Fellow, The American Statistical Association (2018)
- The 2017 Graduate School Alumni Society Graduate Program Chair Leadership Award, Penn State University
- Elected member, The International Statistical Institute (2012)
- J. Awan and A. Slavkovic (2019). “Differentially Private Inference for Binomial Data”. Journal of Privacy and Confidentiality, 10(1). https://doi.org/10.29012/jpc.725
- J Awan, A Kenney, M Reimherr, A Slavkovic (2020). “Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA”. Proceedings of the 36th International Conference on International Conference on Ma- chine Learning (ICML 2019), 97:374–384. https://arxiv.org/abs/1901.10864
- Joshua Snoke and Aleksandra Slavkovic (2018). “pMSE Mechanism: Differentially Private Synthetic Data with Maximal Distributional Similarity”. International Conference on Privacy in Statistical Databases (PSD 2018). 138-159.
- Snoke, J., B. Nowok, G. M. Raab, C. Dibben, and A. Slavkovic (2018). “General and specific utility measures for synthetic data.” Journal of Royal Statistical Society A (JRSS-A),Volume181,Issue3,663-688. https://doi.org/10.1111/rssa.12358
- Karwa, V., Krivitsky, P. and Slavkovic, A., (2017) “Sharing Social Network Data: Differentially Private Estimation of Exponential Family Random Graph Models.” Journal of Royal Statistical Society, Series C (JRSS-C). Volume 66, Part 3, 1-20.
- Karwa, V., and Slavkovic, A. (2016) “Inference using noisy degrees: Differentially Private β-model and synthetic graphs.” The Annals of Statistics. Volume 44, Number 1, 87-112. http://arxiv.org/abs/1205.4697
- Slavkovic ́, A., Zhu, X. and Petrovic, S. (2015) “Fibers of multi-way contingency tables given conditionals: relation to marginals, cell bounds and Markov bases.” Annals of the Institute of Statistical Mathematics. Vol. 67, pages 621-648. Published online June 25, 2014: DOI 10.1007/s10463-014-0471-z
- Yu, F., Fienberg, S., Slavkovic, A, Uhler, C. (2014) “Scalable Privacy-Preserving Data Sharing Methodology for Genome-Wide Association Studies.” Journal of Biomedical Informatics. Special Issue on Informatics Methods in Medical Privacy. Vol. 50., pages: 133-141. http://arxiv.org/abs/1401.5193
- Slavkovic, A. B. (2010). “Partial Information Releases for Confidential Contingency Table Entries: Present and Future Research Efforts.” Journal of Privacy and Confidentiality. Vol. 1, Issue 2, Article 9.