Andrew Drucker

Andrew Drucker is an Assistant Professor in the Department of Computer Science at the University of Chicago. He focuses on theoretical computer science, particularly computational complexity, to understand the inherent limits of efficient computation.

• PhD in EECS from MIT (2012), advised by Scott Aaronson
• Postdoctoral work at the Institute for Advanced Study (IAS) and University of Edinburgh

His research explores algorithmic paradigms for solving NP-hard problems, such as kernelization (preprocessing reductions) and intelligent random guessing, where clever trial-and-error strategies outperform naive approaches. He also investigates non-classical proof systems involving interaction, probabilistic verification, and quantum mechanics, as well as the efficiency gains from joint computation across multiple tasks. Additional interests include prediction, polynomial approximation, and algorithmic insights into human memory.

He participates in academic service as a program committee member for conferences like ITCS, FOCS, and CCC. Contact: andy.drucker@gmail.com