I'm Ravinder Reddy Atla — a solo ML researcher building a personal chess AI lab on top of 10,000+ personal games and the Lichess elite database. My work sits at the intersection of behavioral modelling, human-AI alignment, and skill progression — using chess as a model system where ground truth exists and data is abundant.
I'm particularly interested in what makes human decision-making at different skill levels measurably distinct, and whether those differences can be used to build genuinely personalised coaching systems — not just engine analysis with a friendlier UI.
Individual decision-making signatures — how move distributions, time allocation, and positional preferences form stable, identifiable fingerprints across time.
What measurably changes in how people think and decide as skill increases — building a behavioral atlas of improvement, not just an Elo trajectory.
Personalised coaching that accounts for who you are, not just what the engine recommends — matching study material to your specific behavioral profile.
Chess as a model system for studying how humans learn from and collaborate with superhuman AI — and how AI can be made genuinely useful to humans, not just optimal.
First post coming after C1 ships.