felar [at] dtu [dot] dk
About Me
Fresh PhD student at DTU Energy. My focus areas are geometric deep learning and porbabilistic modeling applied to the sciences, with a particular focus on solids. My approach is to embrace modern compute and algorithms and to adapt them to physically meaningful representations. Specifically, I believe that Machine Learning methods must be both explainable (trust-worthy) and efficient (scalable).
Outside of AI4X, my personal passions are time-series data and small language models. Weather forecasting is fx. a fascinating problem, it requires the model to both be able to capture complex physical systems and the dynamics of change therein. SMLs are cool too, they capture the pareto frontier of compute and intelligence so well. In the future, I hope to be able to run a Opus quality model on my laptop.
News
- [Jan 2026]The preprint of ELECTRAFI is out! arXiv:2601.13351
Publications
Coming soon...
Research Interests
- MCMC, Gaussian Processes, Representation Learning
- Geometric GNNs, Efficient Attenion, Bayesian ML
- HPC, Scaling
Education
PhD in Geometric Deep Learning
Technical University of Denmark
Master's Degree in Mathematical Modeling and Computation
Technical University of Denmark
Work Experience
Research Assistant
DTU Energy
Machine Learning Engineer for Power Trading
Energy Group
Machine Learning Engineer
DeepGruble