Vishesh Karwa's research addresses the challenges in performing statistical inference using complex and/or massive data such as networks, high-dimensional contingency tables, and data that are missing or incomplete. His work is at the intersection of statistics, machine learning and theoretical computer science, and is motivated by many real-world problems with applications in social, political and behavioral sciences. Currently, his work focuses on statistical foundations of data privacy and confidentiality, causal inference under network interference, finite-sample inference for network models and high-dimensional contingency tables, and selective inference and adaptive data analyses.
- Data Privacy: Foundations and Applications, Spring 2019. Patrick J. McGovern Research Fellow.