Hi there! I am a computer science and business student at Lehigh who is focused on simplifying user interactions with technology, finding unaddressed niches, and delivering innovative solutions to users. I strive to be an early adopter of new technology so that I can deliver innovative products to users.
I have experience in machine learning, both in an industry and research setting. I also enjoy building web applications for my projects, clubs, and internships. Recently, I’ve delved into Blockchain and iOS development.
Now, I'm excited to create user-friendly UX/UI experiences and build secure, scalable backend systems. My commitment to staying current with industry trends drives my pursuit of professional growth. I'm actively seeking opportunities to contribute my skills to innovative web development and software engineering projects.
With experience in designing machine learning models and scraping/presenting large amounts of data, I've developed a MLB Game Predictor website and the Mountain Hawk Food Finder iOS app.
Last summer, I trained mathematical models and agent-based models based on historical data obtained by the CDC. I also created powerful data visualizations to provide actionable insights into mitigating influenza spread. 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.
I’ve previously interned at STEM-SI, a research-intensive program in which I trained models to track the spread of influenza. I research for the Lehigh Blockchain group, where I currently am developing a Stellar-like hierarchical consensus mechanism to model a global cross-CBDC payment solution. Last fall, I was involved with making pseudo verkle trees in Rust using the Marlin and ark_works cryptographic libraries. In creating the verkle tree, I worked on creating polynomial commitments, inserting nodes into the trie, and verifying proof of membership and non-membership.
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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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