Prof. Anindya De

(BT/CSE/2008)

Prof. Anindya De is an Associate Professor and Graduate Chair in the Department of Computer and Information Science at the University of Pennsylvania. His research lies at the intersection of theoretical computer science, algorithms and machine learning, with particular emphasis on Boolean function analysis, computational complexity, learning theory, high-dimensional probability and geometry. More recently, his research has increasingly explored the theoretical foundations of AI safety and alignment. He received his B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Kanpur, in 2008 and subsequently earned his Ph.D. in Computer Science from the University of California, Berkeley, in 2013 under the supervision of Prof. Luca Trevisan. His doctoral research focused on theoretical computer science, including extractors, pseudorandomness and complexity-theoretic questions. During his time at IIT Kanpur, Prof. De distinguished himself academically, receiving the President's Gold Medal in 2008 for the best academic performance among all departments in his graduating class. His early research at IIT Kanpur included work on fast integer multiplication using modular arithmetic, which subsequently appeared at the Symposium on Theory of Computing (STOC). Following his Ph.D., Prof. De spent two years at the Institute for Advanced Study in Princeton, first as a Member and then as a Visitor, working with renowned mathematician Avi Wigderson. He subsequently held a post-doctoral position at Rutgers University before joining Northwestern University as an Assistant Professor in 2015. He joined the University of Pennsylvania in 2019 as an Assistant Professor and was promoted to Associate Professor. His research has produced influential contributions across theoretical computer science. His work on Boolean functions and learning theory has addressed problems involving testing, approximation, computational complexity and the structure of high-dimensional functions. He has also contributed to algorithms for trace reconstruction, monotonicity testing, extractors and pseudorandomness, helping advance the theoretical understanding of what can and cannot be efficiently learned or computed. Prof. De has also contributed to the theoretical foundations of machine learning. His research examines fundamental questions about learning algorithms, including their computational limitations, statistical behaviour and the mathematical structure underlying learnable functions. This work connects classical theoretical computer science with modern questions in machine learning and artificial intelligence. More recently, his research interests have expanded toward AI safety and alignment, reflecting his interest in the theoretical foundations required to make increasingly capable AI systems reliable and robust. His broader research portfolio therefore connects algorithms, complexity theory and learning theory with emerging questions about the safety and behaviour of advanced AI systems. Prof. De's research has received significant recognition. He received the NSF CAREER Award in 2021, the IBM Pat Goldberg Memorial Best Paper Award in 2014 and was co-winner of the Best Student Paper Award at the Theory of Cryptography Conference in 2012. He has also contributed extensively to the broader theoretical computer science community through service on program committees for leading conferences including STOC, FOCS, COLT, ALT and ITCS. He also serves as an Associate Editor for the SIAM Journal of Computing. His research has received support from the National Science Foundation, including through his CAREER Award, and the UK AI Security Institute. Through his research and academic leadership, Prof. De has helped strengthen the theoretical foundations of algorithms, machine learning and computational complexity while increasingly engaging with one of the most important emerging questions in computer science: how to build AI systems whose behaviour can be understood, evaluated and aligned with human objectives.
Honouring his pioneering contributions to Theoretical Computer Science, Algorithms, Machine Learning and Computational Complexity, and his distinguished impact on advancing the mathematical foundations of learning and emerging research in AI safety and alignment, IIT Kanpur confers upon Prof. Anindya De the Young Alumni Award 2026 under the category of Academic Excellence.