Aleksandra Slavkovic

Huck Chair in Data Privacy and Confidentiality; Professor of Statistics and of Public Health Sciences

Aleksandra Slavkovic

Research Summary

Methodological developments in the area of data privacy and confidentiality in the context of small and large scale surveys, health, genomic, and network data.

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Privacy Random Graphs Synthetic Data Graph Model Social Networks Exponential Family Statistics Propensity Score Classification And Regression Trees Graph In Graph Theory Linear Regression Graph Inference Modeling Estimator Similarity Model Hiv Latent Class Norm Count Data Sharing Statistical Models Genomics Disclosure Control

Most Recent Publications

Supporting Knowledge Sharing and Awareness in Emergency Management Planning: A Design Research

GREGORIO CONVERTINO, HELENA MENTIS, Aleksandra Slavkovic, MARY ROSSON, J Carroll,

SUPPLEMENTARY MATERIAL FOR “CAUSAL INFERENCE IN TRANSPORTATION SAFETY STUDIES: COMPARISON OF POTENTIAL OUTCOMES AND CAUSAL DIAGRAMS”

Vishesh Karwa, Aleksandra Slavkovic,

Characterizing Joint Distributions for Contingency Tables with Applications to Statistical Disclosure Limitation

Aleksandra Slavkovic,

Privacy in Statistical Databases

Aleksandra Slavkovic, A Smith,

Differentially Private Estimators \& Basic Statistical Inference

Aleksandra Slavkovic,

SEMINAR

Aleksandra Slavkovic,

Statistical Data Privacy: A Song of Privacy and Utility

Aleksandra Slavković, Jeremy Seeman, 2023, Annual Review of Statistics and Its Application on p. 189-218

A LATENT CLASS MODELING APPROACH FOR GENERATING SYNTHETIC DATA AND MAKING POSTERIOR INFERENCES FROM DIFFERENTIALLY PRIVATE COUNTS

Michelle Pistner Nixon, Andrés F. Barrientos, Jerome P. Reiter, Aleksandra Slavkovic, 2022, Journal of Privacy and Confidentiality

Shape And Structure Preserving Differential Privacy

Carlos Soto, Karthik Bharath, Matthew Reimherr, Aleksandra Slavkovic, 2022,

Problems on Random Graphs under Local Differential Privacy

Jonathan Hehir, Siddharth Vishwanath, Aleksandra Slavkovic, X Niu, 2022,

Most-Cited Papers

Ten Simple Rules for the Care and Feeding of Scientific Data

Alyssa Goodman, Alberto Pepe, Alexander W. Blocker, Christine L. Borgman, Kyle Cranmer, Merce Crosas, Rosanne Di Stefano, Yolanda Gil, Paul Groth, Margaret Hedstrom, David W. Hogg, Vinay Kashyap, Ashish Mahabal, Aneta Siemiginowska, Aleksandra Slavkovic, 2014, PLoS Computational Biology

Scalable privacy-preserving data sharing methodology for genome-wide association studies

Fei Yu, Stephen E. Fienberg, Aleksandra B. Slavković, Caroline Uhler, 2014, Journal of Biomedical Informatics on p. 133--141

Inference using noisy degrees: Differentially private β-model and synthetic graphs

Vishesh Karwa, Aleksandra Slavković, 2016, Annals of Statistics on p. 87-112

General and specific utility measures for synthetic data

Joshua Snoke, Gillian M. Raab, Beata Nowok, Chris Dibben, Aleksandra Slavkovic, 2018, Journal of the Royal Statistical Society. Series A: Statistics in Society on p. 663-688

Sharing social network data: differentially private estimation of exponential family random-graph models

Vishesh Karwa, Pavel N. Krivitsky, Aleksandra B. Slavković, 2017, Journal of the Royal Statistical Society. Series C: Applied Statistics on p. 481-500

Differentially private exponential random graphs

Vishesh Karwa, Aleksandra B. Slavković, Pavel Krivitsky, 2014, on p. 143-155

Differentially private uniformly most powerful tests for binomial data

Jordan Awan, Aleksandra Slavković, 2018, Advances in Neural Information Processing Systems on p. 4208-4218

pMSE mechanism: Differentially private synthetic data with maximal distributional similarity

Joshua Snoke, Aleksandra Slavković, 2018, on p. 138-159

Statistical models for incorporating data from routine HIV testing of pregnant women at antenatal clinics into HIV/AIDS epidemic estimates

Ben Sheng, Kimberly Marsh, Aleksandra B. Slavkovic, Simon Gregson, Jeffrey Eaton, Le Bao, 2017, AIDS on p. S87-S94

Structure and Sensitivity in Differential Privacy: Comparing K-Norm Mechanisms

Jordan Awan, Aleksandra Slavković, 2021, Journal of the American Statistical Association on p. 935-954