I work where artificial intelligence meets biology.

My path doesn't run in a straight line — molecular genetics, financial markets, and machine learning. The thread through all of it is an appetite for hard, open-ended problems, and the patience to chase them wherever they lead.

I grew up in Kerala, on the southern tip of India. I became a scientist there, learning by doing through the Kerala Forum for Science Literature; its magazines Eureka and Sasthra Keralam were my first window into research. That carried me to CCMB — often called the crown jewel of Indian biological research — which takes roughly ten students a cycle from thousands. It was also where I fell for computers; the first site I ever built, a lab page, felt cutting-edge twenty years ago and, somehow, is still online today.

The 2008 crash pulled me toward the markets. After four years as a post-doc at UC Davis I traded full-time, and learned that markets are ruled less by intelligence than by emotion. So I set out to remove the emotion — building an automated trading platform in Python and Django, scraping SEC-EDGAR filings and wiring into Interactive Brokers' API back when no other broker had one.

My research asked how a single cell becomes an entire organism. The questions that kept me up are the ones AI is finally making tractable: can we model a mutation's effect in silico, learn the signatures of a cell type, steer a stem cell's fate by tuning gene expression, build a digital model of human disease?

Here's the belief underneath all of it: the real power of AI isn't handing you the most probable answer to a question — it's that it can write complex code that produces deterministic, reproducible results. Give it the rules of a system and it makes them executable. Follow that far enough and the ambition is staggering: to codify an entire organism in code, and one day, perhaps, the universe itself.

That's why I'm drawn to the intersection of AI and biology. Everything before was preparation — the rigor of the bench, the discipline of the markets, the craft of shipping software. Curiosity is what connects them, and building is how I answer it.

Robotics is where my love of engineering meets teaching. For years I've coached, mentored, and judged competitive robotics — because the best way to grow the field is to grow the people in it.

Science, markets, machine learning, and the mind — a few of the books that shaped how I think.

Experiments in neural style transfer.