Research
I am an Assistant Professor / Courant Instructor (postdoc) at New York University, sponsored by Christopher Musco.
I have a joint appoinment with Mathematics at Courant and Computer Science and Engineering at Tandon.
Broadly, my research aims to develop methods to support the scientists taking on the problems of today.
An overview of my research interests along with more detailed introductions to particular directions can be found here as well as by following the [intro] links on papers listed below.
I am committed to making my research accessible and to facilitating the reproducibility/replicability of my work.
Code to generate the figures from my papers can be found on Github.
Please feel free to contact me with any questions or concerns about my research.
More information can be found in my curriculum vitae (cv).
Collaboration
I’m always interested in finding things to collaborate on (and people to collaborate with). I’m especially interested in cross-disciplinary work.
I believe strongly in the value of undergraduate research and am currently working with a number of undergraduate students on research projects.
- Robert Chen (NYU)
- Kevin Li (NYU)
- Skai Nzeuton (Stuyvesant)
- Yilu Pan (NYU)
- Yixin Wang (NYU)
- Qichen Xu (UW)
If you’re an undergrad student in the NYC area interested in research or grad school, please feel free to reach out.
In submission
[6]
GMRES, pseudospectra, and Crouzeix's conjecture for shifted and scaled Ginibre matrices
Tyler Chen, Anne Greenbaum, and Thomas Trogdon.
2023
.
[5]
Stability of the Lanczos algorithm on matrices with regular spectral distributions
Tyler Chen and Thomas Trogdon.
2023
.
[4]
Near-Optimality Guarantees for Approximating Rational Matrix Functions by the Lanczos Method
Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, and Chris Musco.
2023
.
[3]
A posteriori error bounds for the block-Lanczos method for matrix function approximation
Qichen Xu and Tyler Chen.
2022
.
[2]
On the fast convergence of minibatch heavy ball momentum
Raghu Bollapragada, Tyler Chen, and Rachel Ward.
2022
.
[1]
Randomized matrix-free quadrature for spectrum and spectral sum approximation
Tyler Chen, Thomas Trogdon, and Shashanka Ubaru.
2022
.
Publications
[8]
Krylov-aware stochastic trace estimation
Tyler Chen and Eric Hallman.
SIAM Journal on Matrix Analysis and Applications.
2023
.
to appear
[7]
Low-Memory Krylov Subspace Methods for Optimal Rational Matrix Function Approximation
Tyler Chen, Anne Greenbaum, Cameron Musco, and Christopher Musco.
SIAM Journal on Matrix Analysis and Applications.
2023
.
[6]
Numerical computation of the equilibrium-reduced density matrix for strongly coupled open quantum systems
Tyler Chen and Yu-Chen Cheng.
The Journal of Chemical Physics.
2022
.
[5]
Error Bounds for Lanczos-Based Matrix Function Approximation
Tyler Chen, Anne Greenbaum, Cameron Musco, and Christopher Musco.
SIAM Journal on Matrix Analysis and Applications.
2022
.
[4]
Analysis of stochastic Lanczos quadrature for spectrum approximation
Tyler Chen, Thomas Trogdon, and Shashanka Ubaru.
Proceedings of the 38th International Conference on Machine Learning.
2021
.
[3]
On the Convergence Rate of Variants of the Conjugate Gradient Algorithm in Finite Precision Arithmetic
Anne Greenbaum, Hexuan Liu, and Tyler Chen.
SIAM Journal on Scientific Computing.
2021
.
[2]
Non-asymptotic moment bounds for random variables rounded to non-uniformly spaced sets
Tyler Chen.
Stat.
2021
.
[1]
Predict-and-recompute conjugate gradient variants
Tyler Chen and Erin C. Carson.
SIAM Journal on Scientific Computing.
2020
.
Here are links to my Google Scholar profile and ORCID: 0000-0002-1187-1026.
Talks
Slides for my talks and a list of upcoming travel can be found here.
Thesis
I did my PhD in the Department of Applied Mathematics at the University of Washington where I was advised by Anne Greenbaum and Tom Trogdon.
Lanczos based methods for matrix functions
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[source]
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