About Marcel
From physics research to building reliable AI systems
My path started in experimental physics, where precision and uncertainty live side by side. Over time, I became more interested in how those principles apply to real-world systems — how to build technology that knows what it doesn’t know.
The Journey
Academic Foundation
I completed my PhD at Heidelberg University, focusing on light field reconstruction and 3D geometry algorithms. My work explored how to recover the shape, orientation, and material properties of reflective objects — places where classical computer vision breaks down.
Physics trained me to deal with uncertainty methodically. Every measurement carries limits — and understanding those limits often matters more than the value itself.
Industry Transition
In 2017, I joined AGT International as a data scientist while finishing my doctorate. That period bridged two worlds: scientific rigor and industrial reality. It showed me how analytical thinking could translate into systems that actually make decisions.
After earning my PhD in 2018, I continued refining that connection — building models that needed to work outside the lab, with all the noise and ambiguity that entails.
Building rabbitAI
In 2019, I co-founded rabbitAI to tackle one of the core challenges in AI: reliable ground truth. We design systems that capture the real world precisely enough for machine learning to trust it — from automotive cabins to industrial environments.
As CTO, I focus on connecting hardware, physics, and machine learning. The aim isn’t perfection but transparency: AI systems that make their assumptions visible and stay quiet when the data speaks in uncertain terms.