About
Hey, I'm Felix — a data scientist, engineer, and the person behind Akribic.
I hold a Ph.D. in Physics from the Technical University of Munich and have spent the past decade working at the intersection of machine learning, data science, and real-world product development. Before that I did research at Johns Hopkins University and Princeton, where I focused on time series analysis, forecasting, and manifold learning.
Professionally, I've led data science teams and built production ML systems — most notably Transformer-based recommender systems deployed globally at adidas, delivering measurable, multi-million-dollar business impact. I've also established an enterprise-wide AI Hub and led the integration of Generative and Agentic AI technologies into products and workflows.
Before adidas, I served as Team Lead AI at intive, managing a team of ten ML professionals and delivering projects in computer vision, speech processing, and recommender systems. I also worked as an AI Strategist at the Fraunhofer Institute, focusing on explainable AI and efficient neural networks for edge devices.
Why Akribic?
Akribic is where I share hands-on experiments, workflows, and practical lessons learned while building with AI automation tools. The name derives from the Greek akribeia — meaning precision and thoroughness — which is exactly how I try to approach every problem.
I started this blog because I believe the best way to learn new technology is to build with it and then write about what actually worked. You'll find articles on AI agents, automation pipelines, recommender systems, and multimodal AI.
Want to work together or just say hi?
I'm always happy to chat about AI, data science, or interesting project ideas.