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Felix Aertebjerg

PhD Student at Denmark's Technical University

felar [at] dtu [dot] dk

About Me

PhD student at DTU Energy and supervised by Assistant Prof. Arghya Bhowmik, as well as co-supervised by Prof. Juan Maria García Lastra. My focus areas are geometric deep learning and probabilistic modeling applied to the sciences, with a particular focus on solids and battery materials. 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

Publications

  • Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink thumbnail

    Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink

    Jonas Elsborg, Felix Ærtebjerg, Luca Thiede, Alán Aspuru-Guzik, Tejs Vegge, Arghya Bhowmik

    Preprint, 2026

    arXiv

Research Interests

  • MCMC, Gaussian Processes, Representation Learning
  • Geometric GNNs, Efficient Attenion, Bayesian ML
  • HPC, Scaling

Education

2026 - Present

PhD in Geometric Deep Learning

Technical University of Denmark

2023 - 2025

Master's Degree in Mathematical Modeling and Computation

Technical University of Denmark

Work Experience

2025 - 2026

Research Assistant

DTU Energy

2025 - 2026

Machine Learning Engineer for Power Trading

Energy Group

2024 - 2025

Machine Learning Engineer

DeepGruble