Building intelligent systems from the ground up.
Student. ML engineer in progress.
Depth over breadth, always.
I'm a CS (AI & ML) student based in Bengaluru, working through a structured roadmap to become a core ML engineer with MLOps capability.
My approach is depth over breadth — every project is deliberately ordered, building compounding understanding from first principles to production systems.
Dual-model LightGBM system — regressor for AQI delta, classifier for spike risk. Does construction intensity explain AQI variability beyond weather? R² improved +26.6%, spike recall +27%. Served via FastAPI + Docker.
Generalized neural network via configurable layer_dims, ReLU hidden + sigmoid output, full backpropagation with L2 regularization. 96.67% accuracy on make_moons. NumPy only — no PyTorch, no TensorFlow. Just the math, made to run.
Open-source contribution to AI-Scientist-V2 — research automation tooling for LLM-driven scientific paper generation pipelines.
ML from Scratch — a series building every core algorithm by hand, from the math up. No black boxes. Published on Hashnode, cross-posted to LinkedIn and X.
Open to research collaborations
and problems worth losing sleep over.
Reach out — I respond.