I am currently a member of technical staff at Radical AI, where I am working on building foundation models for material discovery.

I started out working across startups and big tech, picking up internships in everything from backend security and hardware to breathing wearables, gaze tracking, and multilingual data. It gave me a solid foundation, but mostly it showed me I was more curious about how things worked, which meant when I got into research it was an easy fit.

Since then, I developed the cognitive architecture for a pet robot, integrating perception, autonomy, and behavior, and worked with Amazon on comparing the performance, memory, and adversarial resilience of SSM and transformer architectures.

My main interests lie in foundational theory, interaction, and the intersection of AI and the physical sciences. While you don’t have to do what you love to be successful, I’m lucky enough to always find myself working on projects I love—and honestly, it makes work way more fun than it probably should be.