Konrad Voelkel

Academic Teacher for Data Science at Heinrich-Heine-Universität Düsseldorf. Before, I was working at Osnabrück University (within the group "Geometrie und Topologie" and the Graduiertenkolleg GK1916, "Combinatorial Structures in Geometry"). Before that, I did my PhD at the Graduiertenkolleg GK1821, "Cohomological Methods in Geometry" Freiburg, Germany), working on applications of homotopy theory to algebraic geometry (motivic homotopy theory). My PhD advisor was Matthias Wendt.

My interests range from computer science to physics, with logics in between. My focus in research has been on motivic homotopy theory of algebraic varieties and applications. More recently, I've been looking into data science and machine learning, in particular manifold learning, topological data analysis, geometric machine learning.

I was also very active in the coordination team of the regional group of Scientists for Future Osnabrück, a science communication effort, where we organized a lecture series for the public on climate change, among many more outreach actions.

Within the political party Bündnis 90 / Die Grünen, I was on the board of the Stadtverband Osnabrück before moving to Düsseldorf.

Preprints of my work can be found on the arXiv. My PhD thesis is published at the University of Freiburg FREIDOK.

You can contact me, look at my CV or look up where you've seen me and which upcoming conferences and summer schools I will attend.

I used to blog about mathematics,
and recommend reading those blog posts I liked most.

There is an RSS feed.

tl;dr - in the enterprise context, you'll start with rapid prototyping using GPT-4 (or another LLM) but eventually end up with a far smaller but just as capable specialized distilled model. That's the journey I see from PoC to prod.

🚨 NEW COMPETITION ALERT 🚨
Can you build a model to correctly identify fungi species? Check out the latest competition on Hugging Face 🤗 FungiCLEF2023: https://huggingface.co/spaces/competitions/FungiCLEF2023

Load More

Author: