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 to social, political and behavioral sciences. Some of the problems that he currently works on include: (1) Statistical foundations of data privacy and confidentiality, (2) Causal inference under network interference, (3) Finite-sample inference for network models and high-dimensional contingency tables, and (4) Selective inference and adaptive data analyses.
- Data Privacy: Foundations and Applications, Spring 2019. Patrick J. McGovern Research Fellow.