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Paul Beckman

Headshot of Paul Beckman
Program Year:
4
University:
New York University
Field of Study:
Mathematics
Advisor:
Michael O'Neil
Degree(s):
B.S. Computational and Applied Mathematics, University of Chicago, 2019

Practicum Experience(s)

Lawrence Berkeley National Laboratory (2023)

Practicum Supervisor(s):
Xiaoye
Li
Practicum Title:
Butterfly factorization from matrix-vector products

Annual Program Review Abstracts

Butterfly-Accelerated Gaussian Random Fields on Manifolds (2024)
Boundary Integral Methods for Computing Covariances in Inverse Source Problems (2023)
Fast Algorithms for Elliptic PDEs With Gaussian Boundary Noise (2022)

Publications

Christopher J. Geoga, Paul G. Beckman. “Nonparametric spectral density estimation from irregularly sampled data.” arXiv preprint arXiv:2503.00492 (2025).

Paul G. Beckman, Michael O'Neil. “A Nonuniform Fast Hankel Transform.” arXiv preprint arXiv:2411.03029 (2024).

Paul G. Beckman, Christopher J. Geoga. “Fast Adaptive Fourier Integration for Spectral Densities of Gaussian Processes.” Statistics and Computing 34, no. 6 (2024): 217.

Paul G. Beckman, Christopher J. Geoga, Michael L. Stein, and Mihai Anitescu. “Scalable Computations for Nonstationary Gaussian Processes.” Statistics and Computing 33, no. 4 (2023): 84. (2023).

David B. Williams-Young, Paul G. Beckman, and Chao Yang. “A Shift Selection Strategy for Parallel Shift-Invert Spectrum Slicing in Symmetric Self-Consistent Eigenvalue Computation.” ACM Transactions on Mathematical Software (TOMS) 46, no. 4 (2020): 1-31.

Awards

Courant Institute - Moses A. Greenfield Research Prize

University of Chicago - Computational and Applied Mathematics Departmental Honors (2019)