Summary
Aaron Roth is a professor of computer science at the University of Pennsylvania with over a decade of experience researching machine learning, algorithmic fairness, differential privacy, and algorithmic game theory. He progressed from assistant to full professor at Penn while holding industry-affiliated roles such as an Amazon Scholar and previous research positions at Microsoft, blending theoretical rigor with practical collaboration. Trained with a PhD from Carnegie Mellon and a BA in Math and CS from Columbia, he focuses on designing algorithms that balance utility and privacy in strategic settings. His work often bridges theory and real-world impact, informing how systems make fair decisions under privacy constraints. Notably, he maintains long-term ties to industry research labs, reflecting a consistent interest in translating academic insights into deployable technologies.
10 years of coding experience
10 years of employment as a software developer
BA, Mathematics and Computer Science, BA, Mathematics and Computer Science at Columbia University
PhD, Computer Science, PhD, Computer Science at Carnegie Mellon University