David Zuckerman

David Zuckerman is a Professor in the Department of Computer Science at the University of Texas at Austin, holding an Endowed Professorship. He earned an A.B. in Mathematics from Harvard University (1987) and a Ph.D. in Computer Science from UC Berkeley (1991). His research focuses on pseudorandomness, computational complexity, and their applications, particularly randomness extractors. He has held postdoctoral positions at MIT, Hebrew University, and visiting roles at institutions like the Institute for Advanced Study.

His major awards include the 2025 Gödel Prize and the 2024 National Academy of Sciences Michael and Sheila Held Prize for his groundbreaking work on two-source extractors. He has advised numerous students, including Eshan Chattopadhyay, Raghu Meka, and Abhishek Bhowmick, who have achieved notable academic and industry roles.

Zuckerman’s research explores the role of randomness in computing, with contributions to coding theory, cryptography, and distributed computing. His work on two-source extractors solved a long-standing open problem, enhancing both theoretical computer science and Ramsey Theory. He has also contributed to practical applications like pseudorandom generators and robust randomized algorithms.

Current students include Gautam Chandrasekaran, Michael Jaber, and Vinayak Kumar. His career includes organizing major workshops like DavidFest (2025) and lecturing globally on topics like spectral graph theory and pseudorandomness. Key contributions span over 30 years, with impactful papers in STOC, FOCS, and the Annals of Mathematics.