Hi! My name is Andrew Chung.
I am a Master's student at UC Berkeley's School of Information studying data science with a background in management consulting. I'm passionate about applying technical and business thinking to help companies solve strategic problems.
This summer, I completed an internship as a Technical Program Manager Intern at Apple, where I designed and launched an internal vetting tool to facilitate international market entry. It was a fun (remote) experience :)
Outside of work, I enjoy playing tennis, golf, and basketball. I am also a big fan of board games, discussing philosophy, and playing the cello (especially in ensembles!).
If you're interested in learning more, you can find my resume and projects below.
Some of My Projects
Last Updated: 02/2020
MAPPING STREET SAFETY: NAVIGATION SYSTEM
PREDICTING ALL-NBA SELECTIONS
MEDICARE PAYMENTS OVERVIEW
A friend and I designed a navigation system that provides users with routes based on their levels of safety, while not sacrificing too much time and simplicity. I built the backend, which mainly consists of a large multi-directed, weighted graph in Python. The current build can navigate all of Berkeley, CA and is under consideration for grant funding.
I created a prediction model to better predict All-NBA selections. Numerous prediction models were used (random forest, logistic regression, deep learning), but the sequential neural net demonstrated superior performance (8% greater precision than traditional NBA prediction methods). I also ran clustering and PCA to find some interesting trends about the composition of the league today.
I was curious to explore Medicare payments in the U.S. In R, I ran high-level statistical analyses and visualizations on the official Medicare.gov dataset, segmenting by demographics, geography, and illness types. I also implemented a random forest model to predict average Medicare payment amounts based on patient characteristics.