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I am a Computer Science and Artificial Intelligence double major at Purdue University on the Machine Learning track. I like projects where backend correctness, real product constraints, and thoughtful interaction design all matter at once.
Right now, I am building and piloting ClubLadders, teaching Java as an undergraduate TA for Purdue CS 180, and continuing to dig deeper into machine learning and systems.
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Live demo · Case study |
Source and benchmarks |
CURRENT BUILD ClubLadders — production match tracking, tournaments, Elo, and ML
TEACHING Undergraduate TA — Java, recursion, and object-oriented programming
LEARNING Machine learning, systems, and production backend design
PRODUCT VALUES Correctness · clear feedback · accessibility · responsive behavior
Python · FastAPI · TypeScript · Next.js · React · Java · C
PostgreSQL · Redis · SQLAlchemy · scikit-learn · Docker · GitHub Actions · AWS
- Built ClubLadders around correctness-sensitive workflows including guest-player claims, deterministic Elo replay, singles and doubles, and five tournament formats.
- Load-tested Gatekeeper at 100 concurrent users, reaching 180 requests per second with a 99.87% success rate and 735 ms p95 latency.
- Support 60+ students through weekly Purdue CS 180 labs and office hours.
- Previously led outreach to 200+ students and helped organize an 80+ participant AI builder hackathon.
Open to software engineering internships where I can work on products people actually use.