Researcher

Christopher Musco

Christopher Musco is a computer scientist whose research develops efficient algorithms for large-scale data analysis and machine learning. He studied applied mathematics and computer science at Yale, completed a computer science Ph.D. at MIT in 2018, worked as a Research Instructor at Princeton, and joined NYU Tandon as an assistant professor in 2019. His research on big-data processing earned an NSF CAREER Award in 2021, and his paper on Shapley-value estimation was selected as an ICLR spotlight in 2025. The Polar Express earned an ICLR 2026 Outstanding Paper Honorable Mention; Musco is an Institute Associate Professor at NYU, where he studies efficient algorithms and modern machine learning.

Timeline

  1. 2018

    Yale and MIT degrees

    He earns a Ph.D. in computer science at MIT in 2018 after studying applied mathematics and computer science at Yale; before MIT, he works as an engineer at Redfin.

  2. 2018–2019

    Research instructor at Princeton

    Before joining NYU, he works as a Research Instructor at Princeton and teaches Advanced Algorithm Design (COS 521) in Fall 2018. By 2019, Princeton's TCS group includes him among its instructors and lists New York University as his affiliation.

  3. 2019

    Assistant professor at NYU Tandon

    NYU Tandon names him a new assistant professor in its Department of Computer Science and Engineering in 2019. His research tackles how to scale statistical methods to large datasets for machine learning and data-driven discovery.

  4. 2021

    An NSF CAREER Award

    He receives the 2021 NSF Faculty Early Career Development Award for work on processing and analyzing massive datasets. His project applies matrix sketching to compress large datasets and aims to make big-data processing more accessible.

  5. 2025

    A Shapley estimation spotlight

    In 2025, his paper with R. Teal Witter, Provably Accurate Shapley Value Estimation via Leverage Score Sampling, is selected as an ICLR spotlight.

  6. 2026

    An ICLR Outstanding Paper Honorable Mention

    With Noah Amsel, David Persson, and Robert Gower, he coauthors The Polar Express: Optimal Matrix Sign Methods and Their Application to the Muon Algorithm, which receives an ICLR 2026 Outstanding Paper Honorable Mention. The work uses approximation theory to design polynomial approximations for the polar decomposition used in the Muon optimizer, with GPU computation and low-precision arithmetic in view.

  7. As of October 2026

    Institute associate professor at NYU

    He is an Institute Associate Professor of Computer Science and Engineering at NYU and belongs to its Theoretical Computer Science Group and VIDA Center. His research develops efficient algorithms for science and engineering and studies algorithmic aspects of modern machine learning, including fast inference and retrieval.

Career

  1. Since 2019New York UniversityAssistant Professor
  2. 2018–2019Princeton UniversityResearch Instructor
  3. RedfinEngineer

Education

  1. 2018Massachusetts Institute of TechnologyPhD
  2. Yale University

Sources and credits

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  1. Christopher Musco chrismusco.com. Checked 21 October 2026.
  2. NYU Computer Science Department cs.nyu.edu. Checked 21 October 2026.
  3. TCS @ Princeton Alumni: 2019 theory.cs.princeton.edu. Checked 21 October 2026.
  4. New Faculty 2019 engineering.nyu.edu. Checked 21 October 2026.
  5. Professor Christopher Musco receives NSF award for promising young researchers engineering.nyu.edu. Checked 21 October 2026.
  6. Announcing the ICLR 2026 Outstanding Papers blog.iclr.cc. Checked 21 October 2026.