I'm a Software Engineer II at Air. I build backend services and user-facing features for an AI workflow platform, including human review tools, LLM streaming, and file ingestion.
I enjoy building reliable backend systems and full-stack applications. This site also collects projects and research from my time at Lehigh University.
I graduated from Lehigh University with a B.S. in Computer Science and Business.
Earlier projects include an MLB Game Predictor website and the Mountain Hawk Food Finder iOS app.
During a summer research project, I trained mathematical and agent-based models using historical CDC data. I also created data visualizations to explore the spread of influenza. My team's agent-based influenza modeling project came in second place in the Lehigh Summer Research Day Expo.
Outside of work, I spend time playing fantasy football, listening to music, and editing videos. I have played baseball since elementary school and like to play pick-up basketball with friends. I also enjoy participating in hackathons and programming challenges.
At STEM-SI, I trained models to study the spread of influenza. With Lehigh Blockchain, I researched hierarchical consensus and built prototype Verkle trees in Rust, including polynomial commitments and membership proofs.
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MLB Game Predictor is a machine learning-driven web application, leveraging over 2,430 game records from the MLB Stats API to forecast game outcomes with 60% accuracy. Powered by Spring Boot and integrating linear regression and random forest models, it processes and filters 20+ datasets using NumPy and Pandas. The platform serves 500+ active users monthly, offering data-driven predictions for baseball enthusiasts.
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OhConnections is a baseball-centric web application inspired by the New York Times’ ‘Connections,’ designed to challenge players with MLB-specific grouping puzzles. The platform integrates state management and real-time user interaction logic to deliver a seamless and engaging experience. Within its first month, OhConnections achieved 1,000+ active users, driven by a visually intuitive interface that fosters high retention and user engagement.
GitHub ViewMountain Hawk Food Finder is a full-stack iOS application designed to streamline dining at Lehigh University, especially after the closure of a major dining hall limited student options. The app offers daily menus, user-generated item ratings, and real-time business hours. Featuring seamless Apple Maps integration, it enables students to navigate remaining campus eateries efficiently. Built with a robust backend to manage user data and ratings, it provides a visually appealing and intuitive solution to enhance dining convenience amidst changing campus dynamics.
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Solidity Semiswap is a decentralized exchange (DEX) built in Solidity, implementing an ERC-20 to Ether automatic market maker. Designed for a Blockchain Systems class, it allows users to seamlessly provide, estimate, and withdraw liquidity, as well as swap between ERC-20 tokens and Ether. The platform demonstrates core principles of decentralized finance through efficient smart contract design and user-focused functionality.
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