I am an Associate Professor in the CS department at Northwestern University, and by courtesy, the IEMS department. I'm a member of the Theory CS Group and my research interests are broadly in theoretical computer science. I work on the algorithmic foundations of machine learning, data science, combinatorial optimization, and more recently, quantum information. I am particularly interested in using paradigms that go Beyond Worst-Case Analysis to obtain good algorithmic guarantees.

I serve as the Institute Director (2023-24) and a Site Director (Northwestern) of the Institute for Data, Economics, Algorithms and Learning (IDEAL), a NSF-funded collaborative institute across Northwestern, TTI Chicago, UIC, U of Chicago, and IIT. My research is also supported by an NSF CAREER award, an NSF AITF award CCF-1637585 (with David Sontag), CCF-2154100 (with Julia Gaudio) and the Google Research Scholar program .

Prior to joining Northwestern in Fall 2015, I was at Courant, NYU for a year as a part of the Simons Collaboration on Algorithms and Geometry , and was a Simons Postdoctoral Research Fellow with the Theory Group at Carnegie Mellon University. I obtained my PhD from Princeton University in Computer Science with Prof. Moses Charikar. Prior to that, I finished my bachelor's degree in CS from the Indian Institute of Technology Madras in 2007. I spent the first fifteen years of my life in Pondicherry, a beautiful town in Southern India, where Pi Patel hails from.

CS212: Mathematical Foundations of Computer Science. Fall 2015, 2016, 2017, Spring 2019, Fall 2019, Winter 2021, Fall 2022.
CS496: Graduate Algorithms. Winter 2016, 2017, Spring 2018, Winter 2019, Winter 2022.
CS 396/496: Foundations of Quantum Computation & Quantum Information Winter 2022 (co-taught with S. Rao), Winter 2024.
CS 335: Intro to the Theory of Computation (co-taught with Jason Hartline) Fall 2020, Spring 2022.
CS 496: Foundations of Reliable Machine Learning Fall 2021, Fall 2023.
CS 497: Recent Highlights in Theoretical CS Winter 2022.
CS496: Theoretical Foundations of Data Science Spring 2021.
CS496/ ECE495: Algorithmic Aspects of Network Inference Spring 2020 (co-taught with R. Berry).
CS496: Topics in Theoretical Machine Learning. Winter 2018.
CS 496 : Beyond Worst-Case Analysis. Spring 2017.