Cameron Musco

Cameron Musco joined CICS in September 2019. Previously, he was a postdoctoral researcher at Microsoft Research New England. He completed his PhD in computer science at MIT, where he was a member of the Theoretical Computer Science and Theory of Distributed Systems groups. Musco received a BS in computer science and applied mathematics from Yale University.

Cameron Musco studies algorithm design, with a focus on applications in data science and machine learning. His work is interdisciplinary, drawing on tools from theoretical computer science, numerical linear algebra, optimization, statistics, and biology. He is particularly interested in the power of randomized approximation algorithms and in streaming, distributed, and low-memory computation. His most significant contributions have been in developing fast randomized methods for fundamental linear algebraic problems. Musco is also interested in computational phenomena in biological systems, including ant colonies and neural networks. He believes that studying these systems can lead to unique insights into the nature of algorithmic robustness, randomized computation, and simple distributed protocols.

Musco has received an NSF Career award and an NSF Graduate Research Fellowship. He is also a recipient of the UMass CICS Dean's Award for Anti-Racism Leadership. He regularly reviews and serves on program committees for top venues in theoretical computer science, machine learning, and numerical computation, and is the recipient of several top reviewer awards.