Scholar
Johann Brehmer
Google Scholar ID: ZdUMvCsAAAAJ
CuspAI
Citations & Impact
Citations
5,229
H-index
24
i10-index
31
Publications
20
Co-authors
8
list available
Publications
Resume (English only)
Academic Achievements
- Published 'The Open DAC 2025 Dataset for Sorbent Discovery in Direct Air Capture' (arXiv 2025) in material discovery.
- Authored multiple papers on geometric deep learning, including 'Geometric algebra transformer' (NeurIPS 2023) and 'Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics' (NeurIPS 2024).
- Pioneered simulation-based inference methods, with key papers in PNAS (2020), Computing and Software for Big Science (2020), and others.
- Published in top journals including Physical Review Letters, Physical Review D, The Astrophysical Journal, and SciPost Physics.
- Developed open-source tools like MadMiner for likelihood-free inference in particle physics.
Research Experience
- Research Scientist at CuspAI, Amsterdam.
- Previously worked at Qualcomm AI Research.
- Worked in Kyle Cranmer's lab at NYU.
- Worked in Tilman Plehn's group at Heidelberg University.
- Worked at Imperial College London.
