Tim-Henrik Buelles
thbuelles (at) gmail (dot) com
About
I'm a Research Scientist at Pythia Labs. I was trained as a Mathematician, now I train neural nets. More technically (less funny), I currently work on multi-task learning for generative and probabilistic modeling. Previously, I was a Postdoctoral Scholar in Mathematics at Caltech working with Prof. Graber on geometric deep learning and applications in string theory. I did my PhD in Mathematics at ETH Zürich with Prof. Pandharipande. My thesis focuses on generating functions of enumerative invariants derived from Calabi–Yau geometries in superstring theory. Before that, I did my MSc and BSc in Mathematics at the University of Bonn where I worked with Prof. Huybrechts on algebraic cycles and motives of K3 surfaces.
Research
My research was published in Journal of Algebraic Geometry, Forum of Mathematics, and Manuscripta Mathematica.
After spending a few years in academia, I shifted my attention to the mathematical foundations of machine learning. At Pythia Labs, I am currently working on generative models for protein design and drug discovery. We train continuous-time (ODE / SDE-based) generative models on biomolecular data such as sequential 1D amino acid data and geometric 3D structure data. For each modality or task, we have a toolbox for probabilistic modeling, architecture, feature learning, scaling, deployment, etc. Sounds good.. but.. how to integrate into a single model that can perform multiple conditional generative tasks? Oh, and please make it end-to-end, efficient, scalable, robust, fine-tunable, and ready for production..
Teaching
From 2016 to 2023, I was an instructor for Mathematics at the University of Bonn, ETH Zürich, and Caltech, teaching Linear Algebra, Abstract Algebra, Group Theory, Galois Theory, Algebraic Geometry..
Personal
You'll find me either reading papers, writing code, or riding my bike. A long day out on quiet mountain roads never gets old to me. Admittedly, I do indulge in the occassional run and hike too. The Zürich Marathon '22 is a memory that will stay with me forever. Check Strava for all of my ups and downs through training, traveling, and adventures.