About

About. I studied mechatronics engineering—systems built on top of the usual science, motors and control and the rest of it. What stuck wasn't the building so much as what sat underneath. An internship at a physics lab outside my college was the first time I felt that pull clearly: the pleasure of understanding something from first principles, not just making it work. By the time I finished my degree I was still reading physics on my own, a little quantum here, a little classical there, with no real plan beyond knowing I wasn't done.

Like a twenty-one-year-old trying to stand on his own feet, I took a corporate job writing database queries. It paid the bills. In the evenings, and often well into the night, I kept at the physics anyway—slowly, without a syllabus—until I was sure enough to jump back into academia. When I finally got into a physics PhD, it felt like arriving somewhere I'd been heading for a long time. IISER Mohali was a new institute still being built in the foothills of the Himalayas—fresh campus, fresh thinking, and at the time one of the few places in India open to someone with an unconventional background like mine. I went for dynamical systems and chaos. That was the part that finally grabbed me and didn't let go.

My first postdoc took me to Germany—my first time living there, in a country where physics has deep roots and you feel it without anyone having to say so. I ended up in Oldenburg, a small town in the northwest, in a theoretical ecology lab working on synchronization in food webs. I learned a fair amount of ecology and not quite enough German.

Toward the end of that stint I started drifting into machine learning and AI—showing up at conferences more or less at random, without a tidy reason, just because the questions looked interesting. Around then Bill Ditto at NC State was steering his lab from applied chaos toward what he called AI for physics, and looking for someone at that intersection. I happened to be moving in the same direction. I joined, and worked on physics-informed neural networks for chaotic systems.

Now I'm at the Jackson Laboratory, carrying the same habits of thought into cell dynamics and animal behavior.

Predrag Cvitanović says a scientist owns the method, not the subject. That's the closest thing to a plan I ever had.

What I'm up to now is on the research page. (I also drink an indefensible amount of tea—the one variable I've never managed to control.)