About Me

I'm a Computer Science graduate from Queen Mary University of London who builds end-to-end products that solve real problems. I love taking on technical challenges that don't have obvious solutions and turning them into working systems that people actually use.

What I Build

I specialize in full-stack development with a focus on AI and LLM applications. Recently, I fine-tuned a Qwen3-4B model on medical dialogue data and built a complete RAG pipeline with vector search across 500+ documents, deploying the entire stack to production. I've also developed a VR language learning application where users have real-time conversations with NPCs in 38+ languages, integrating speech recognition, LLM-powered dialogue generation, and dynamic narrative systems.

I'm technically adaptable and enjoy learning new frameworks quickly—whether it's working with LangGraph for agent workflows, deploying on GCP and RunPod, or building with Next.js and React. I care deeply about user experience and making complex technology feel simple.

Real-World Impact

One of my most satisfying projects was a Python automation tool that reduced a repetitive 2-hour task to 15 minutes. Seeing my team adopt it immediately and use it every week showed me the value of solving friction points that people face daily. I've also managed technical infrastructure for live events with 1,000+ concurrent viewers, where there's no room for error and real-time problem-solving is essential.

I'm excited about working on problems that push boundaries—especially in AI, automation, and user-facing products where technology directly improves how people work or learn.

Let's connect if you're working on something interesting and need someone who can ship quality code, pick up new technologies quickly, and contribute from day one.