ShreeChaturvedi

I built an agent that drives the whole ML lifecycle through a 12-tool MCP registry behind human approval gates, running every model-generated cell inside a hardened Docker sandbox with no network, a read-only rootfs, and a non-root user. The preprocessing path is a scaffold.

I built a multi-stage NLP smart-input pipeline (chrono-node, compromise, and a custom priority parser) that resolves overlapping parser claims by priority first, then per-tag confidence. The serverless path dropped Prisma for raw pg, while a parallel Express + Prisma stack still ships alongside it.

I wrote an MNIST MLP and hand-vectorized its hot paths with arch-dispatched AVX-512, AVX2, and NEON kernels over 64-byte-aligned, blocked-tiled matrices, no BLAS or PyTorch pulled in. OpenMP wins on big matrices and regresses small ones ~7x, so it is gated by size, not waved off.

I wrote a C++23 expression language and compiled it to WebAssembly: tokenizer, recursive-descent parser, tree-walking evaluator, user functions, and recursion. It runs live in-browser on this project's own case page. It uses double everywhere with exact == comparisons, called out in the README.