I'm a UC San Diego junior majoring in Probability & Statistics, with a second major in Economics. I perform statistical analyses, study market trends, write software, and play games.
Skills and education
I am proficient in several programming languages. I am most skilled in modern Python implementations, especially 3.12. Atop data processing tools like Pandas, NumPy, and SciPy, I am also practiced in web scraping. I typically engage in web scraping using bs4 and Requests For Humans, but I have used other libraries in the past.
I also know R, SQL, C, bash, and few other languages. I've even managed to implement a few, such as a tiny FORTH-like and a working Brainfuck interpreter.
My favorite type of statistical regression is the linear regression. I love its simplicity and effectiveness. However, that's not the only method I know. I also can use A/B testing, the multi-armed bandit method, random forests, and various types of neural network algorithm.
Highlights
These are my favorite publicly-visible projects! Feel free to check them out.
How to cheat at Wordle
Wordle is a simple game with a lot of underlying complexity. In this article, I discuss how I used information theory and probability theory to create a tool to play Wordle as efficiently as possible.
Read it!About Snackflation
I built a fully automatic tool to predict market behavior and price indices of popular snack foods. It works by using a simple linear regression model to predict the future value of snacks such as potato chips. I regressed prices against the date and found that the date tends to have a statistically-significant impact upon price. This reflects well-known notions of inflation as predicted by many empirical models, which state that (during short runs) a market tends to be in an inflationary state rather than a deflationary state and all goods' prices will therefore rise over time, often at rates which are somewhat consistent.
Read it!