Product · AI · Builder
CS student at UIUC, product builder, and lifelong tinkerer,
currently shipping AI-powered products from idea to deployed reality.
"I grew up curious about how things work, then how to make them work better."
I got curious about AI back in middle school, watching it start to reshape industries. That curiosity took me from a research lab, training machine learning models to catch heart disease early from cardiac signals, into product roles at AI-driven startups, most recently helping a Peter Thiel-backed identity-verification company sharpen its APIs and grow. Now I'm continuously building, still chasing the AI product that lets me put that impact at scale.
I thrive in fast, ambiguous environments: finding the opportunity, building the solution, and iterating on what the data tells me. Outside of internships, I'm usually deep in a side project, most recently Findster.ai, teaching an app to recognize lost belongings the way a person would, and before that, co-founding Cheer, an award-winning team-management app for youth sports. Fair warning: I'm an extreme perfectionist and borderline unreasonably detail-oriented, so if a button is 2px off, I will notice, and I will fix it.
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Also built at hackathons: Shopix, a visual product-search AI app (team project, UIUC Product Hackathon), designed an AI recommendation flow with NLP review filtering and chatbot-driven search.
Cambridge Centre for International Research · AI for Healthcare Researcher, 2023
Trained KNN, CNN, RF, and Naive Bayes models in Python to detect heart disease from echocardiograms, building an end-to-end pipeline from preprocessing through model training, evaluation, and deployment-ready outputs.
DECA
Product
AI & Data
Tools
Let's build something.