↓Skip to main content

About

Table of Contents

I’m a Machine Learning Researcher at Johns Hopkins Applied Physics Lab, where I work on multimodal generative AI systems and LLM-powered agent workflows for real-world applications. I have an MS in Computer Science (with a thesis on Non-Stationary Machine Learning and Optimal Transport) and dual BS degrees in Computer Science and Electrical Engineering from Johns Hopkins University.

These days I’m mostly interested in Machine Learning, Natural Language Processing, and building AI systems that actually work in production. Much of my research continues to focus on the work I started with The Cybernetics Implantable Devices Lab - small and interpretable models, optimal transport theory, and the tricky effects of temporal distribution shifts in real-world ML systems. I’m also a big fan of entrepreneurship and innovation 🚀. You’ll often find me brainstorming new projects and exploring ways to turn research ideas into practical solutions.

I’m drawn to the messy, interesting problems that live at the intersection of computer science and engineering - the kind where you need AI that actually works when things get complicated. If you’re working on similar challenges or just curious about this kind of work, I’d love to chat!

Selected Publications #

Teaching #

↑