Relax.js
A React alternative in TypeScript: fine-grained signals/effects, a deterministic scheduler with priority lanes + budgets, and a Babel-compiled fast path with SSR, hydration and SSG.
Ravi Kishan/Software Engineer
Software engineer drawn to the systems others treat as magic — a UI runtime, a language interpreter, a container runtime and a distributed datastore, all built from scratch. The fastest way I understand a system is to rebuild it.

Built from first principles
A runtime, a search engine, a cache, a language, a distributed store and a load balancer — each rebuilt from the ground up.
All 69 repositories on GitHubA React alternative in TypeScript: fine-grained signals/effects, a deterministic scheduler with priority lanes + budgets, and a Babel-compiled fast path with SSR, hydration and SSG.
A lightweight full-text search engine in Go with an Elasticsearch-style inverted index, a web crawler and a ranking algorithm over indexed documents.
A Redis server reimplemented in Rust and Go — RESP protocol, core data structures and an event loop — because rebuilding it is the fastest way to actually understand it.
A programming language built from scratch in Java/C — lexer, parser, AST and tree-walking interpreter — inspired by Lox, shipped in a Dockerized execution environment.
A scalable, fault-tolerant key-value store in Go with sharding, replication and multithreaded request handling across nodes for high availability under node failure.
An NGINX/HAProxy-style load balancer in TypeScript — round-robin and weighted strategies, health checks and reverse-proxying across backend pools.
Featured projects
The work I'm proudest of right now — runtimes, developer tools and distributed systems, open and documented.
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#6The track record
Education

MCA — Master of Computer Applications
GPA 9.5 / 10

BCA — Bachelor of Computer Applications
GPA 9.6 / 10 · Gold Medalist

Higher Secondary (12th), Science — BSEB
74%

Matriculation (10th) — BSEB
84%
Highlights



Publications
Research that made it past review — a published patent application on applied AI over Indian epics.
App. No. 202541117128 · Filed Nov 2025 · Published 19 Dec 2025
A RAG system over the Bhagavad Gita reaching >95% retrieval accuracy across 5 languages — built with OpenAI embeddings, LangChain and FAISS/Pinecone, and evaluated with BLEU and BERTScore.
Open to hard problems
Distributed backends, AI agents, or performance work that needs to go fast. Let's talk.