Sudeepa Roy

Sudeepa Roy is an Associate Professor of Computer Science at Duke University, affiliated with the Department of Computer Science. Her research spans databases, data management, and data analysis, focusing on foundational aspects of big data processing and responsible data analysis. She has held postdoctoral positions at the University of Washington and has been a visiting scientist at institutions such as UC Berkeley and RelationalAI. Roy has contributed to numerous conferences and workshops, including serving as a PC Co-Chair for ACM SIGMOD 2026 and PC Chair for the 28th International Conference on Database Theory (ICDT) 2025. She teaches courses on databases and causal inference and has advised multiple graduate and undergraduate students.

Sudeepa Roy is a researcher in the field of databases, focusing on the development of methods for explaining query answers, ensuring privacy in provenance-aware systems, and improving the efficiency of database operations. Her work explores the intersection of causality, explanations, and privacy in data management. Roy's research includes the design of tools for translating Simulink models into model checker input languages, as well as the exploration of causal inference and pattern-based counterbalances for query explanation. Her contributions span both theoretical and applied aspects of database systems, with an emphasis on enhancing transparency and security in data-driven applications.