CV

The short, slightly more official version. Email is on the contact page; code is at github.com/Tu-Zhenzhao.

Education

University of Washington, Seattle
M.S., Applied Mathematics. 2024–present.

University of Wisconsin–Madison
B.S., Mathematics and Data Science. 2022–2024.

University of Utah
Mathematics, until transfer. 2020–2022.

Research

Current work is on network richness — the lazy versus rich training regimes of neural networks, and how width, depth, and parameterization interact. Broader interests: numerical methods, dynamical systems, and the theoretical limits of machine learning.

Earlier: image inpainting as L1-regularized optimization in the DCT domain (UW, 2025); ODE models of turbulence and a comparison of Runge–Kutta and Kalman filtering (UW–Madison, 2022–2024); SVD, PCA, and iterative linear solvers (Utah, 2021–2022).

Other

I have built more software than I have published papers, which I am trying to correct. Dean’s lists at Utah (2020–2022) and UW–Madison (Fall 2022). I used to tutor mathematics; I still write in two languages and take photographs when a place insists on it.