John Wright

John Wright is an Assistant Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His research centers on theoretical computer science with a focus on quantum computing, specifically quantum state learning, quantum complexity theory, property testing, and approximation algorithms. He is affiliated with the Simons Institute for the Theory of Computing.

Education includes a Ph.D. in Computer Science from Carnegie Mellon University (2016), advised by Ryan O'Donnell, and a B.Sc. in Computer Science from the University of Texas at Austin.

Research interests span quantum complexity, interactive proofs (e.g., MIP* = RE), quantum algorithms, and foundational aspects of quantum computation. His work bridges computer science, physics, and mathematics, with emphasis on understanding computational limits through quantum paradigms.

Publications primarily explore quantum complexity, algorithms, and verification, with recent trends including quantum cryptography, tomography, and hardness proofs. Articles frequently involve collaborations with researchers like Thomas Vidick, Henry Yuen, and Ryan O'Donnell.

Awards include the IEEE CS TCPAMI Young Researcher Award (2015).

Teaching covers graduate and undergraduate courses such as CS 170 (Efficient Algorithms and Intractable Problems) and CS 294 (Quantum Complexity Theory). He advises students in quantum computing research and collaborates extensively across institutions.

Labs/teams include the Quantum Computing group at UC Berkeley, with ties to the Simons Institute. Research support is managed by Amy Frithsen.