# CV

Author: Zhenzhao Tu

The short, slightly more official version. Email is on the [contact](/contact/) page; code is at [github.com/Tu-Zhenzhao](https://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](/research/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.