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nberdi/README.md

Nauryzbek Berdi

Full-Stack & Backend Engineer | CS @ Berea College (graduating May 2027)

I build systems that scale. Currently focused on distributed backend architecture, AI/ML pipelines, and medical imaging applications.

🎯 Recent Work

  • Computational Medical Imaging – Research Intern at Brigham and Women's Hospital / Harvard Medical School (May–July 2026). Built a pipeline for 3D coronary artery reconstruction from CTA imaging to support cardiac surgery planning.
  • Distributed Job Queue System – TaskFlow: Async job processing with Redis/BullMQ, idempotent retry logic, and real-time status updates. Production-grade patterns documented.
  • RAG-Powered Document Analysis – LexAI: Legal document QA system using vector embeddings, pgvector, and GPT-4o with clause-level citations.
  • Automated Code Review – ReviewBot: GitHub App performing AI-powered inline code review on every PR.

💻 Skills

Languages: Python, JavaScript, TypeScript, SQL, C++
Backend & Infrastructure: Node.js, Express, FastAPI, PostgreSQL, Redis, Docker, distributed systems
Frontend: React, Next.js, Tailwind CSS
AI/ML: RAG pipelines, vector embeddings, LangChain.js, PyTorch, OpenAI & Anthropic APIs

🔗 Connect

Pinned Loading

  1. LexAI LexAI Public

    RAG-powered legal document analyzer with PDF upload, AI chat, and clause-level citations.

    TypeScript

  2. ReviewBot ReviewBot Public

    AI-powered GitHub App that reviews pull requests and posts inline code comments.

    TypeScript

  3. TaskFlow TaskFlow Public

    Distributed background job queue with Redis, BullMQ, PostgreSQL, and a real-time admin dashboard. Process long-running tasks asynchronously with durable queueing, retry logic, and webhook callbacks.

    TypeScript