About

Résuméthe record in full, on one page

The long version

I chose control engineering somewhat by accident. My plus-two marks weren't what I needed for the top courses: mechanical, computer, triple E. Control engineering was offered in just seven colleges across Tamil Nadu. Less competition, I thought. Maybe I'd get a gold medal. That was the whole plan. It was naive. I didn't get the medal either.

But what I did get, without looking for it, was a lens. Control theory gives you something: everything is a system. Anything that can be seen as a system can be modeled, understood, acted upon. I've never stopped seeing the world that way.

Then came Mu Sigma. Dheeraj and the whole complexity science orientation there aligned naturally with what I had already started building. Complexity, non-linearity, feedback, emergence, not just as engineering concepts but as a way of reading business problems and social systems.

I learned how to operate. I learned where the real friction is. I also noticed what I kept running into: the gap between knowing how to run a model and knowing why the model should work the way it does. Industry, under time pressure, lets you settle for "good enough." I stopped wanting to settle.

That's why I came to Columbia. The goal isn't to add credentials. The goal is to fill the gaps rigorously, to develop the theoretical foundation that makes my problem-solving genuinely different, not just experienced.

I'm not chasing the usual signals. I know what I've built, I know what I'm building toward. Building is the mechanism of becoming, not building to show something, but building as the way the thinking gets real and the person gets formed. The work is what matters. Manhattan is temporary.

How I work

Four ways of meeting the world, read as a loop: what I make changes what I see next. Curiosity runs through all four.

Art · seeing

Noticing, being present, getting the essence. The sketchbook, the kitchen, old Tamil poetry, and quality things to be around.

Philosophy · asking why

What it means, and what is worth caring about. Reading, reflecting, and questions kept for years.

Science · explaining how

The patterns and mechanisms underneath: an experiment against a baseline, one change at a time, failures counted as results.

Engineering · making

Turning what I understand into something that runs, for real people. Trigger, quick plan, handle the gaps, execute.

Why this place

Henry's essay A Website to Destroy All Websites names three things the web should be for: teaching and learning, connecting with friends, and coding. I took his three and made them mine: teaching and learning, connecting with the world, and problem solving for the world. All of it happens here first, in one place I own, and travels outward from here. It follows the IndieWeb: publish on your own site, own what you make, build for the long web, and have fun.

Now

Studying

Final semester of the M.S. in Data Science at Columbia, finishing December 2026.

Researching

Graduate student researcher at CRIS Lab, Columbia: causal and continual learning, world models, agents.

Teaching

Teaching assistant for Foundation Model Engineering, and AI and Games.

Building

A course on problem solving in the age of superintelligence, one session at a time.

Open to

Roles

Research engineering and applied science, after I graduate in December 2026. The résumé has the record in full.

Talks

Guest lectures and talks at universities and student groups, on problem solving, causal and continual learning, and AI in real systems.

Teaching

Course material here is open to teach from; tell me if you use it.

Research

Working on an open question together. The questions are a good place to start.

On the record

Published

Thirumurai, a Tamil Shaivite poetry dataset (LREC 2022) · Dravidian-language sentiment analysis (FIRE 2021) · two abstracts at the Ocean Society of India Conference 2023

Taught

Foundation Model Engineering · AI and Games · Causal Inference · Statistical Methods and Advanced Analytics · Applied Risk Analytics (teaching assistant, Columbia)

Studied

M.S. in Data Science, Columbia University · B.E. in Instrumentation and Control Engineering, Anna University

Elsewhere

GitHub

github.com/prabakaranc98: code for the builds and experiments

Hugging Face

huggingface.co/prabakaranchandran: models and datasets from the Lab

Substack

pracha98.substack.com: essays carried from here

LinkedIn

prabakaranchandrantheds: the record, and posts that point home

X

@PraCha98: short notes that point home

Everything is published here first; these are where it travels.