Scholar
Moritz Haas
Google Scholar ID: O0PrX4sAAAAJ
PhD Student, University of Tübingen
Citations & Impact
Citations
55
H-index
4
i10-index
2
Publications
6
Co-authors
8
list available
Publications
Resume (English only)
Academic Achievements
- Recognized as a top reviewer for NeurIPS 2024 and as a notable reviewer for ICLR 2025; main publications include 'On the Surprising Effectiveness of Large Learning Rates under Standard Width Scaling', 'mup^2: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling', and others.
Research Experience
- Was a PhD student in the ‘Theory of Machine Learning’ group at the University of Tübingen; currently working at Amazon AGI Foundations.
Education
- PhD in Theory of Machine Learning from the University of Tübingen, supervised by Ulrike von Luxburg and Bedartha Goswami; MSc in Mathematics from Ruprecht Karls Universität Heidelberg; BSc in Mathematics from Ruprecht Karls Universität Heidelberg.
Background
- Currently working as an Applied Scientist in the AGI Foundations team at Amazon. My goal is to develop a mechanistic understanding of deep learning that results in practical benefits. Additionally, I am trying to improve statistical methods in climate science.
Miscellany
- Interests include Deep Learning Theory, Scaling Theory, Statistics, and Machine Learning in Climate Science.
