Christopher Musco is an Assistant Professor in the Computer Science and Engineering department at NYU’s Tandon School of Engineering. Christopher’s research focuses on the algorithmic foundations of data science and machine learning. He studies methods for efficiently processing and understanding data, often working at the intersection of theoretical computer science, numerical linear algebra, and optimization.
Christopher received his Ph.D. in Computer Science from the Massachusetts Institute of Technology and B.S. degrees in Applied Mathematics and Computer Science from Yale University.
Research Interests
Scalable machine learning, foundations of data science, numerical linear algebra, theory of algorithms, randomized algorithms, sketching and streaming
