Hi! My name is George Noarov, I am a 3rd year CS PhD student at the University of Pennsylvania fortunate to be advised by Michael Kearns and Aaron Roth. Before coming to Penn, I graduated Magna Cum Laude from Princeton University with a BA in Mathematics, and was fortunate to be mentored by Mark Braverman and Matt Weinberg.
I am broadly interested in theoretical computer science and machine learning. My current focus is on fairness in ML and distribution-free uncertainty quantification (in particular, conformal prediction), as well as on algorithmic game theory and online learning.
Throughout my academic journey, I have participated in several enriching research visits and industry internships, including as a visiting graduate student for the Data-Driven Decision Processes semester at Simons Institute, Berkeley, and as an intern at Goldman Sachs.
I am grateful to be the recipient of several academic awards, including the Undergraduate Award in Applied and Computational Mathematics and Princeton’s Shapiro Prize for Academic Excellence, and fellowships, including a Joseph Henry Summer Fellowship. I am also a member of the Phi Beta Kappa and Sigma Xi honor societies.
You can check out my papers by navigating to the Publications page or by visiting my Google Scholar profile.