I am Jannik, a data scientist with a strong foundation in Python, hyperparameter optimization, and scientific computing — and a deep interest in algorithm engineering.

My work is inspired by Sutton’s “Bitter Lesson”: building systems that learn from computation and data rather than relying on handcrafted solutions. I focus on designing scalable learning methods and optimization strategies that improve performance, generalization, and efficiency — allowing models to discover rather than be designed.

I’m driven by the challenge of bridging the gap between theoretical AI research and practical implementation, turning abstract ideas into working systems.

With my open source projects I want to give back to the incredible community we all owe so much to.

Feel free to contact me on LinkedIn.

If you want to support my open source work you can sponsor me here on GitHub or buy me a coffee.