Tested whether Jev, TypeSafe's low-latency decision model, could return calibrated probability distributions over a typed question and fixed choices. Simulated Jev calls paragraph-by-paragraph across murder mystery novels to track when it could pin down the murderer.
// Personal project · with roommate · Oct 2026
Reimplemented the famous "Show, Attend and Tell" paper in PyTorch and extended it with adaptive attention (λ-tuned sentinel gating) and VQA. Analyzed the tradeoffs of soft attention mechanisms for vision-language tasks and presented poster.
// Cornell CS 4782: Deep Learning · team of 3 · May 2026
An interactive demo on Variational Autoencoders, trained using Fashion-MNIST dataset to visualize latent space. Include sections on architecture, latent space demo, and KL divergence explanation, and made in Cornell's CS 4782: Deep Learning course.
// Cornell CS 4782: Deep Learning · individual · Apr 2026
A trading backtester built with a Cornell Data Science team sponsored by Millennium's Systematic Data Platform team. Extended with short-selling functionality and realistic trading costs (ADV caps, borrow costs, market impact). Used to implement and backtest a Customer-Supplier Momentum strategy.
// Cornell Data Science × Millennium · team of 10 · Mar 2026
A RAG system that indexes Cornell Data Science's GitHub repositories to answer deep technical questions about past projects, with a focus on intelligently chunking and storing context from large codebases.
// Cornell Data Science · team of 6 · May 2025
Built and deployed a full-stack scheduling website for my freshmen year roommate's barber business.
// Freelance · individual · Aug 2025
A genetic algorithm that optimizes drone coverage paths under energy constraints, developed as a senior research project at TJHSST.
// TJHSST Senior Research Lab · with one lab partner · Mar 2024
