Systems Builder & Open Source Creator
I build from first principles — compilers, CLIs, AI pipelines, and full-stack systems. Not just code that works, but architecture that lasts.
I started writing code the way most engineers do — copying patterns, assembling libraries. Then I built a compiler from scratch in C11 with no parser generators, no external runtime. That changed how I see software.
Every abstraction is a trade-off. Every layer has a cost. I'm interested in understanding systems at the level where trade-offs become visible — and building things that are intentional about them.
My work spans from low-level systems programming (lexers, ASTs, IR generation) to production AI pipelines (YOLOv8 inference, CNN training) to developer tooling (dependency-aware scaffolding, plugin architectures). The through-line is depth.
I'm a CS undergrad at Parul University who prefers shipping over theorizing. Technical Head at CDC. Published to npm. 10+ production systems deployed.
Understanding one layer deeply teaches you how every layer above it works. I invest in fundamentals because they compound.
How you structure code is how you structure future optionality. Good architecture makes teams faster, not slower.
Deployed imperfect systems teach more than perfect designs that never ship. Iteration is the mechanism, not a fallback.
A CLI on npm reaches more developers than any closed system. Building in public creates accountability and compounds value.
A dependency-aware project scaffolding engine for the modern stack.
Built a full monorepo CLI toolchain published to npm as @systemlabs/foundation-cli. The core is a DAG-based PromptGraph engine that resolves module dependencies before writing a single file, an atomic FileTransaction system, and a plugin SDK that lets the community extend the engine via sandboxed lifecycle hooks. 28 built-in modules across 7 categories. 5 packages. Full TypeScript. CI/CD via GitHub Actions.
A JavaScript compiler written in C11. No shortcuts. No parser generators.
Built a full compilation pipeline from scratch in C11 — lexer, recursive-descent parser, AST construction, semantic analysis, intermediate representation, control flow graph, optimization passes (constant folding, dead code elimination), and QBE IR emission to native Linux binaries. This is the kind of project you build when you want to understand how languages actually work.
Full-stack AI system for smart-city pothole detection and civic reporting.
Built for municipal evaluation — a complete citizen-to-government pipeline. Citizen portal, admin console, YOLOv8 inference service in Flask, Node.js API, MongoDB backend, geolocation reporting, Firebase auth, Recharts analytics dashboards, and Leaflet map visualizations for government monitoring.
CNN trained on 884,900 samples with corrective feedback loop.
Trained a convolutional neural network from scratch to classify handwritten characters with 97.94% accuracy on 884,900 samples. Served inference via a Flask UI that supports freehand drawing input — and a corrective feedback mechanism to improve predictions over time.
I'm currently open to full-time roles, collaborations, and interesting open-source projects. If you're building something that requires genuine depth — reach out.