Stefanie.

Hi, my name is Stefanie! Glad you found your way here. I recently defended my PhD in Safe AI at the Technical University of Munich, where I focused on building systems that are not only powerful, but also trustworthy and robust. My dream is to help create a world where we can use AI confidentely because we’ve taken the time to understand it and make it safe.

What sets me apart is my rare combination of theoretical depth and practical experience. With a degree in mathematics and a track record of tackling theoretical problems in my publications, I find beauty in writing proofs and thinking things through precisely. But I’m just as passionate about implementation: writing clean, reproducible code in Python or C++, and turingn and idea into something that persits. I’ve built an entire framework from the very idea until publication of a polished tool on PyPI.

I’ve always worked alongside studying: whether helping people with IT problems, developing ML solutions in the automotive industry, or exploring projects on my own. I value autonomy and tend to take initiative, especially when it means learning something new or building something meaningful. Curiosity is what drives me, and it doesn’t stop when I close my laptop. I like to understand things to their core, whether it is a concept in machine learning or a question that comes up over dinner.

I enjoy meaningful, knowledge-based discussion, and while I value harmony in a team, I’ll always prefer rational arguments when it comes to the work itself. My colleagues describe me as structured, organized, and reliable, but also as someone who brinst warmth to the group, always smiling and creating an open, respectful enviroment.