Christopher Wang
I am a PhD candidate in mathematics at Cornell University. My primary research interests are randomized numerical linear algebra and operator learning. My advisor is Alex Townsend. Before Cornell, I was an undergraduate at Columbia University, where I worked with Ioannis Karatzas on bandit problems. I am supported by the NSF GRFP.
I subscribe to the commitments of the Just Mathematics Collective and the Leiden Declaration on AI and Mathematics.
- CV
- email: cyw33 at cornell dot edu
- research
- Convergence of pivoted Cholesky algorithm for Lipschitz kernels (with S. Jeong and A. Townsend), submitted, 2026. [arXiv]
- Oblivious subspace injection is not enough for relative error (with A. Townsend), submitted, 2026. [arXiv]
- Beyond singular value gaps in randomized subspace approximation (with A. Townsend), submitted, 2026. [arXiv]
- The Gittins index is optimal for dynamic allocation with conditionally independent filtrations, Adv. Appl. Probab., to appear, 2026. [arXiv]
- Operator learning for hyperbolic partial differential equations (with A. Townsend), J. Mach. Learn. Res. 26(199), 1-44, 2025. [arXiv] [journal]
- Extensions of true skewness for unimodal distributions (with Y. Kovchegov, A. Negrón, C. Pertel), Math. Methods Stat. 33(3), 239-258, 2024. [arXiv] [journal]
- teaching
- MATH 2310: Linear Algebra for Data Science @ Cornell
FA26 & SP26 (TA) - MATH 4061: Intro to Modern Analysis I @ Columbia
SP22 (TA) - MATH 1011: Calculus I @ Columbia FA21 (TA)
- service
- I am an outreach co-chair for Cornell AWM and helped organize the 2023-2026 Cornell Julia Robinson Math Festivals
- In 2022, I mentored research projects on data-driven recovery of Green's functions as part of the Cornell Summer REU
- I volunteer occasionally with the Cornell Little Math Circle and with the directed reading program
- more about me