Rocco Servedio

Professor, Columbia University
Rocco Servedio is a professor in the Department of Computer Science at Columbia University. He graduated from Harvard University, where he was advised by Leslie Valiant, with a PhD thesis on efficient algorithms in computational learning theory. His research interests include computational complexity theory (concrete complexity, pseudorandomness, lower bounds and analysis of Boolean functions), computational learning theory (efficient algorithms and lower bounds in a range of models), randomness in computation, the study of algorithmic and information-theoretic reconstruction problems, and sublinear time algorithms for big-data settings, and the connections among these and related topics.

Program Visits

Visiting Scientist
Analysis and TCS: New Frontiers
complexity theory, learning theory, property testing, analysis of Boolean functions, randomness