Aaron Archer, PhD

Aaron F. Archer is a research scientist at Google in New York City, where he leads the Large-Scale Optimization team within the NYC Algorithms and Optimization group, applying mathematical techniques to improve efficiency across Google Search, YouTube, Ads, and Cloud infrastructure. Archer graduated first in his class with a bachelor’s degree in mathematics from Harvey Mudd College in 1998, then earned his doctoral degree in operations research from Cornell University in 2004, advised by Éva Tardos and supported by a Hertz Fellowship. His doctoral thesis examined mechanisms for discrete optimization with rational agents, blending combinatorial optimization with algorithmic game theory. After Cornell, Archer spent more than nine years in the Algorithms and Optimization department at AT&T Shannon Research Laboratory before joining Google in 2013. His research spans mathematical programming — including linear, integer, and convex programming — approximation algorithms, graph algorithms, online algorithms, network design, load balancing, and unsupervised machine learning. Among his notable applied contributions at Google is the development of Prequal, a load balancing system deployed across YouTube and other production services that dramatically reduced tail latency and error rates while enabling systems to run at substantially higher utilization.