I'm happiest in the messy middle of a project — the part where an idea has to survive real data, real people, and an actual deadline.

I came into AI fascinated by what becomes possible with enough data and the technology now emerging around it. But I've always been just as certain about the other half: that whatever I build has to matter to the people who'll actually use it. That combination — curiosity about what's possible, and a stubborn focus on whether it's actually useful — is what keeps pulling me deeper into the field.

That curiosity is also what moved me from Bulgaria to the Netherlands: I wanted to work on real projects with real clients, not just coursework. Since then I've deliberately built breadth — across language, vision, human behaviour, and robotics — because a versatile foundation is what lets me get productive fast in whatever a problem actually needs. The throughline never changes: I like to build, and I start from the person it's for.

I'm a data science & AI student now looking for an internship where I can keep doing exactly that — building systems that solve real problems for the people who use them.