I'm a recent math PhD graduate with 5 years of programming experience. I enjoy using math and software to solve real-world problems. Most of my work falls into the wide category of machine learning applications, with a particular focus on large-scale numerical algorithms and nonlinear optimization methods.
I have developed efficient methods for image segmentation, LASSO (basis pursuit denoising), signal/image processing, and phase retrieval. For more details about my work, please see my GitHub page.
As a software engineer, I am motivated by both the self-directed and team-oriented nature of my work. Personally, I am very self-motivated and love the challenge of large, complex problems. I enjoy going on deep dives to understand the high- and low-level details of state-of-the-art methods. As a colleague, I am driven by a sense of accountability to my team and advisor/manager. I care about the impact of my work and enjoy advancing my team's goals.
I recently completed my PhD in Mathematics at UC Davis under the advisorship of Zhaojun Bai.
My dissertation is on an eigenvalue optimization method for phase retrieval. See my Research Projects for more details.
When I'm not programming or studying, you can find me reading (e.g., The Expanse and Stormlight Archive), running, cooking, listening to podcasts (e.g., This American Life, StartUp, RadioLab, TED Radio Hour), or brewing beer.