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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

Fellow Poster
: Butterfly-Accelerated Gaussian Random Fields on Manifolds (
2024
)
Fellow Poster
: Boundary Integral Methods for Computing Covariances in Inverse Source Problems (
2023
)
Fellow Poster
: 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)