Mussab.

My Story

I started writing code because I wanted to build things — not to follow a career path. The first project that mattered was a small web tool I built for a local business, and the feedback loop of shipping something real and watching people use it was immediately addictive. That instinct has driven everything since.

Over the past three years I've built across the full stack — healthcare platforms, recruitment portals, AI-powered SaaS tools, restaurant ordering systems — through Flowpath, the studio I co-founded. Each project taught me something the previous one couldn't: how to design a schema for a multi-tenant system, how to integrate an LLM into a production workflow, how to think about UX when the end user isn't technical.

The pivot toward machine learning wasn't a pivot at all — it was the inevitable next question. The same curiosity that made me want to build software made me want to understand the mathematics underneath it. I started with statistics, moved into numerical methods, and found myself reading papers on Monte Carlo methods for particle physics experiments. Building a research-grade radioactive decay simulation was the moment I understood that physics and ML share a common language: probability.

I applied to the KEK/J-PARC summer student programme in Japan because I want to work inside that language — in a real experimental facility, with real data, alongside researchers who have spent careers thinking about these problems. That is the direction I am heading.