About Me
I’m a student studying data science and economics, with side interests software engineering,
and DevOps. I’ve worked extensively across the web stack, from frontend and backend
development to systems design, infrastructure, and deployment. My experience also extends to
distributed software, where I’ve tackled challenges in scalability and performance.
Right now, I’m looking to deepen my knowledge in the data science process, CI/CD and explore
game development. Always eager to learn, build, and refine my skills, I enjoy taking on projects
that push my technical boundaries.
Education
University of California, San Diego
B.S in Data Science
Minor in Economics, Political Science
Expected Graduation: June 2027
GPA: 3.92
6L-24R
6L-24R
Skills
Proficient in:
- Langs: Typescript, Python, Java, Go, SQL
- Stacks/Services: Next.js, Svelte
- Services: NodeJS, MongoDB, PostgreSQL, Redis, Docker
- Cloud: AWS Lambda, ECS, ECR, AppSync, EC2, S3, RDS
Intermediate Profeciency in:
- Langs: R
- Stacks/Services: Vue, GraphQL
Learning:
- Rust
6R-24L
6R-24L
Projects
ShotWatch // shotwatch.io
ShotWatch is a basketball analytics website designed to help users analyze NBA player statistics and shot charts. The platform allows users to query and retrieve NBA video footage from a database of over 615,000 plays, applying advanced filters to isolate specific game moments.
Key Features
- Comprehensive NBA Footage Search: Users can query thousands of game clips based on various parameters.
- Advanced Filtering Options: Filter footage by shot location, shot distance, quarter, time remaining, player name, team, and more.
- Statistical Analysis & Visualization: Generate detailed shot charts and analytics to study player tendencies.
- Smooth User Experience: Designed with an intuitive UI, allowing analysts, coaches, and fans to explore basketball data seamlessly.