I'm an undergrad at Cornell studying Computer Science and Mathematics.
I'm interested in improving how machine learning models are trained, optimized, and implemented across both research and applied contexts. My current interest lies in vision systems and AI agents.
I help contribute to ML research with Professor Jennifer Sun's lab group, where I've been benchmarking and experimenting with vision models. On the industry side, I've worked as a software engineer at Emergence AI and ST Engineering iDirect. This summer I'm interning with Microsoft CoreAI.
I also love to dance Bhangra, play basketball, and do food challenges.
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
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
Here's my notepad, where I post reactions or reflections after coming across a tweet, paper, video, book, or some content makes me think. These notes are often free-form and loosely organized.
