I am a Quantitative Analyst on the Fixed Income ETF Portfolio Management desk at Invesco. Before becoming a Quant, I completed a Master's in Applied Mathematics at the University of Illinois in Chicago, focusing primarily on Numerical Partial Differential Equations. Even longer ago, I attended the University of California, Berkeley, where I studied Applied Math and Physics.

I like working on problems in Optimization (especially Mixed-Integer Programming), PDEs and Data Science. I also believe the title "Quant" isn't an excuse to leave everything in a Jupyter notebook, and consequently spend a good chunk of time configuring my development environment to find bugs as I write them.

I work on a few opensource projects in my spare time. The use cases are relatively niche, but if you maintain a static blog, need to do security identifier validation in Polars, or want some simple scripts for a tmux/suckless Linux setup, you might be interested!

Here are some lecture notes I took as an undergraduate at Cal. These are provided as-is with zero-editing (except PDEs II), and are probably not a great primary source if you're in any of these classes. These are mostly here for my own reference, and because they include some nice TiKz pictures.

• Partial Differential Equations II (Sung-Jin Oh, Spring 2022)
• Metric Differential Geometry (Rui Wang, Spring 2020)
• Complex Analysis (Peter Koroteev, Spring 2020)
• Real Analysis (Rui Wang, Fall 2019)
• Quantum Mechanics II (Ehud Altman, Fall 2019)
• Analytic Mechanics (Stuart Bale, Fall 2019)