Jason Gaitonde

Jason Gaitonde is an Assistant Professor at Duke University's Fuqua School of Business and concurrently serves as a Postdoctoral Associate and Instructor in Mathematics at MIT. His research bridges theoretical computer science, algorithms, game theory, networks, and machine learning in strategic contexts. He holds a Ph.D. in Computer Science from Cornell University (advised by Éva Tardos) and dual undergraduate degrees in Mathematics (B.S., Yale University) and Economics (B.A.).

His work focuses on theoretical problems at the intersection of algorithms, learning, game theory, networks, and randomness. Notable interests include strategic queuing systems, opinion dynamics in networks, and the design of sample-efficient learning algorithms. He has collaborated with prominent researchers such as Elchanan Mossel and Jon Kleinberg.

• Education:
• Ph.D. in Computer Science, Cornell University
• B.S. in Mathematics (Distinction), Yale University
• B.A. in Economics, Yale University

His publications explore topics like the price of anarchy in queuing systems, polarization in social networks, and pseudorandom generators. He has taught courses such as MIT's 18.424 Information Theory and Cornell's CS 6850 on Network Structures. His work frequently appears in top conferences like STOC and EC, with a focus on advancing the theoretical foundations of computer science and economics.