I'm a Computer Science student at Princeton University minoring in Statistics & Machine Learning. I build cool things.
Feb 2025 - Present
Developed machine learning models to predict engine failures. Built predictive engine behavior models using signal processing, mathematics, and physics.
Jan 2025 - Feb 2025
Revamped Fan AI, an algorithm that predicts how engaged a fan is with their sports team. Augmented the feature engineering process and built an in-house comprehensive database of zipcode prosperity scores in the US.
Summers 2023, 2024
Created a new customer invites system, boosting user acquisition by up to 25-50% using React and Firebase. Added the infrastructure necessary for an "import from Google" feature.
Summer 2024
Designed large-data simulations through the Princeton Computing Cluster to conduct quantitative research. Designed and tested a Python program for calculating and visualizing molecular tension, yielding an accurate way to quantify induced simulation tension on chromatin.
Summer 2023
Created a lifestyle-watching app that helps prevent up to 40% of cancer cases through habit-changing. Designed a backend storage system through Hive. Assisted the front-end team with animation design.
Nov 2022 - May 2023
Designed C++ backend code in Unreal engine that integrated the OAuth 2.0 plugin for multi-platform login capabilities. Created and implemented the character movement framework to interact seamlessly with a soft-body physics engine.
Nov 2022 - May 2023
Taught computer science and mathematics concepts in understandable ways (ex. 2D array representation, motion physics, etc.) Was called "Mister" for the first time.
Summer 2022
Co-authored an IEEE research paper investigating a novel AI application in mobile device security. Led the AI model development of the project, engineering models that achieved >92.5% accuracy without overfitting. Designed a MATLAB program to extrapolate unique statistical properties of structure-borne sound recordings.
Coauthored a research paper on AI and a novel method for biometric identification. Presented at the MIT Undergraduate Research Technology Conference.
Demonstrated that English encodes sentiment within the phonetic pronunciation of words, a proof of concept for a lightweight NLP smart-sentiment model.
Used LSTM neural networks to predict Starcraft II match outcomes with 92% accuracy, beating past research by almost 10%.
Designed an optimized C++ homogenous gas engine, beating a Python-based one by 1000% in speed. Modeled accurate particle collisions and derived the Boltzman Distribution via sim.
Designed an animated react profile without templates. Let my love for coffee and clean design shine through.
Beyond my technical work, I am active on campus in various leadership roles. Here is some of the work I've been doing.
Promoted to Head of Software / Computer Vision, and currently designing a low-cost autonomous vehicle platform.
Two-year partnerships officer @ TigerLaunch, the world’s largest student-run entrepreneurship competition.