Prasad Raghavendra received his PhD in Computer Science and Engineering from the University of Washington, advised by Venkatesan Guruswami. He then spent a year at Microsoft Research New England as a postdoc, and two years on the faculty at Georgia Tech. He earned a dual degree (Btech/Mtech) in Computer Science from IIT Madras. He has received a NSF CAREER Award, and a Best Paper Award and Best Student Paper Award at the 2008 ACM Symposium on Theory of Computing. Raghavendra's research focuses on approximation algorithms, hardness of approximation, computational complexity theory and coding theory.
- Geometry of Polynomials, Spring 2019. Visiting Scientist.
- Lower Bounds in Computational Complexity, Fall 2018. Visiting Scientist.
- Summer Cluster: Challenges in Quantum Computation, Summer 2018. Visiting Scientist.
- Bridging Continuous and Discrete Optimization, Fall 2017. Visiting Scientist and Workshop Organizer.
- Pseudorandomness, Spring 2017. Visiting Scientist.
- Algorithmic Spectral Graph Theory, Fall 2014. Visiting Scientist, Program Organizer and Workshop Organizer.
- Real Analysis in Computer Science, Fall 2013. Visiting Scientist, Program Organizer and Workshop Organizer.