Long Story Short
Personal ProjectA web app that turns any book into a short-form, podcast-style audio summary—written by AI and narrated in seconds.
I'm a full-stack software engineer with a background in product design and statistics. I care about good UX, thoughtful interfaces, and measuring whether what we build actually works.
I graduated from Harvard in May 2025 with a degree in Statistics and Computer Science, where my thinking was shaped by courses in AI and reinforcement learning, usable interactive systems design, statistical inference, and visualization. I'm especially interested in building AI products that are robust and useful in real contexts. My work sits at the intersection of software, product, and data, including a custom API log explorer for Hume AI and user-facing data export and notification features at Sigma Computing.
Outside of work, I'm interested in probabilistic decision-making (poker), working with physical systems (pottery), and observing real-world behavior (photography).
A web app that turns any book into a short-form, podcast-style audio summary—written by AI and narrated in seconds.
An AI-powered recipe generator that creates customizable recipes from ingredients in your virtual pantry—no grocery run required.
An interactive data visualization exploring how climate change affects polar bear populations—featuring animated migration paths, sea ice trends, and diet analysis.
Explorations in things I find interesting.
Developed a modified Monte Carlo Tree Search algorithm with domain-specific pruning heuristics for a sequential card game, improving win rates from 39% to 51% over greedy baselines.
Extended classical adverse selection models with dynamic Bayesian learning to analyze how claim denial rates influence consumer dropout behavior and insurer market equilibria.
Applied OLS, LASSO, Ridge, and tree-based regression methods to evaluate urban tree characteristics as predictive bioindicators of air quality across 46 U.S. cities.