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Who is Eshan Chattopadhyay? All about Indian-origin professor awarded prestigious Godel Prize
Eshan Chattopadhyay, an Indian-origin computer scientist and associate professor at Cornell University, has received the 2025 Gödel Prize—one of the highest recognitions in the field of theoretical computer science. He shares the award with David Zuckerman of the University of Texas at Austin for their influential research on randomness extraction—an area crucial to encryption, cybersecurity, and algorithm design.
The award was given for his breakthrough research paper titled 'Explicit Two-Source Extractors and Resilient Functions', which addresses a key challenge in computer science: how to generate high-quality randomness from unreliable sources, critical for secure computing and cryptographic systems.
Published initially at the ACM Symposium on Theory of Computing (STOC) in 2016, where it also won the Best Paper award, and later in the Annals of Mathematics in 2019, the paper introduced new techniques that have since shaped major advances in pseudo-randomness and complexity theory.
Chattopadhyay completed his BTech in computer science from IIT Kanpur in 2011, followed by a PhD at the University of Texas in 2016. He later held postdoctoral positions at the Institute for Advanced Study in Princeton and the Simons Institute for the Theory of Computing at UC Berkeley, two of the most prominent institutions in the field.
Named after legendary logician Kurt Gödel, the Gödel Prize is jointly awarded by the ACM SIGACT and the European Association for Theoretical Computer Science. It honours papers that have made lasting contributions to the field of theoretical computer science.
The research deals with randomness extraction- a fundamental concept in computer science and cryptography. It focuses on creating reliable randomness from two flawed or weak random sources, a challenge that has implications for everything from encryption systems to algorithm design.
In simple terms, imagine flipping two unfair coins and still being able to extract fair, unpredictable results. That's the essence of what Chattopadhyay and Zuckerman achieved, turning weak inputs into strong, usable randomness.
He told Cornell University that the recognition is an incredible honour. He shared that it feels 'surreal and gratifying' that the paper was placed in that category.
