Hey there! I'm a software developer who fell for programming through competitive programming in high school, drawn in by a love of math and problem-solving. I studied Computer Science at Purdue University (with minors in Math and Economics), and this fall I'm heading to Carnegie Mellon for my M.S. in Computer Science.
These days I spend most of my time deep in low-latency systems, building real-time market-data and backend infrastructure for a proprietary trading desk, and tinkering with AI agents and retrieval systems on the side. I'm most at home where systems programming, AI, and quantitative finance overlap.
Outside of code, you'll find me strategizing over a game of Catan or on the tennis court. I'm currently looking for Summer 2027 internships, and I always enjoy meeting new people, so feel free to reach out!
Implemented a responsive, interactive UI using React, with complex state management and data caching. Built a scalable front end with React hooks and modular components. Used Redux and RTK Query for efficient state and data handling. Collaborated in a 5-person team, contributing 5000+ LOC across the full dev cycle, ensuring timely delivery and clean code with Git.
Developed a functional compiler and garbage collector for MiniScala, translating high-level code to assembly, showcasing strong foundations in language theory, systems programming, and memory management. Implemented key compiler phases: lexical analysis, AST construction, type-checking, and error handling. Designed language transformations, efficient value representations, and code optimizations (e.g., constant folding).
Built two game-playing engines for a nested-board game: minimax with alpha-beta pruning and a hand-tuned heuristic in C++, and Monte Carlo Tree Search with UCB1 in JavaScript. Bridged the two engines over a cross-process protocol for head-to-head play.