MSCS @ Northeastern University (Boston) • I build AI-powered apps and the platforms that keep them fast and reliable.

• Built a production RAG system (LangChain) for a government client
• Shipped performance wins across 40+ apps (100× faster cache loads, 5× faster page loads)
• Rust-first tooling for deployment automation and developer workflows

Looking for: 2026 internship / co-op roles in AI/ML or platform engineering.

Links: Blog • Resume • LinkedIn • Email

• Languages: Rust, Python, Java, TypeScript/JavaScript, SQL, Bash
• App/AI: LangChain, Flask, Angular, Postgres, WebSockets
• Infra/DevOps: Linux, Docker, GitHub Actions, Prometheus/Grafana, Kubernetes

• Hikari — lightweight deployment manager for small VM fleets
  Rust + Docker + WebSockets • config watcher → deploy/update/cleanup
  Notes: AES-256 config encryption, daemon mode, and an agent/server design (axum + tokio + Postgres).
  Write-ups: Daemon mode • Realtime scaling

• Autodeploy — single Rust binary that turns a TOML config into a working local deployment
  Generates Docker Compose on the fly + interactive TUI (git2, inquire).
  Write-up: Hassle-free deployments

• Fetal Health Classification — ML pipeline for CTG-based risk classification
  Python (scikit-learn/SciPy) + Flask backend + Angular UI • Dockerized end-to-end
  Reported accuracy: 97.8%

• Documan (Java rewrite) — digital library backend rewrite + infra experiments
  (Original platform: 4,000+ students / 200k+ file deliveries — details in resume)

• Observability (metrics / logs / tracing) + notes for modern workloads
• DNS privacy + running your own resolver stack
• Deployment automation lessons from Hikari + Autodeploy

Read here: Blog home