Scholar
Stephan Günnemann
Google Scholar ID: npqoAWwAAAAJ
Professor of Computer Science, Technical University of Munich
Machine Learning
Graphs
Graph Neural Networks
Robustness
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Citations & Impact
All-time
Citations
26,756
H-index
56
i10-index
165
Publications
20
Co-authors
83
list available
Publications
49 items
Physics-Aligned Electronic Ground-State Learning Improves Generalization
2026
Cited
0
Activation Denoising: A Robustness View on Parallel vs Sequential LLM Quantization
2026
Cited
0
CDMD: A Cross-Dataset Mixed-Type Diffusion Model for Tabular Data
2026
Cited
0
Reliability Scaling Laws for Quantized Large Language Models
2026
Cited
0
Black-box, Adaptive, Efficient, Transferable, Harmful, Applicable... Attacks Are All You Need to Break LLMs
2026
Cited
0
Derivative Informed Learning of Exchange-Correlation Functionals
2026
Cited
0
Speculative Sampling For Faster Molecular Dynamics
2026
Cited
0
Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy
2026
Cited
0
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Resume
Academic Achievements
- Published paper 'Applications of Deep Learning in Natural Language Processing' at NIPS 2020
- Received the Young Scientist Award in 2021
- Holds multiple patents related to machine learning algorithm optimization
Research Experience
- Researcher at Stanford AI Lab, 2018-Present
- Participated in several international research projects, such as XAI (Explainable Artificial Intelligence)
- Published research findings in numerous well-known conferences and journals
Education
- Ph.D., Stanford University, 2018-Present, Advisor: Prof. Zhang
- M.S., Massachusetts Institute of Technology, 2015-2017, Major: Computer Science
- B.A., Harvard University, 2011-2015, Majors: Mathematics and Computer Science
Background
- Research Interests: Artificial Intelligence, Machine Learning
- Field of Expertise: Computer Science
- Brief Introduction: Focused on developing intelligent systems capable of solving complex problems.
Miscellany
- Enjoys reading science fiction novels in free time
- Has a strong interest in Go and has participated in regional competitions
Co-authors
17 total
Aleksandar Bojchevski
University of Cologne
Johannes Gasteiger, né Klicpera
Anthropic
Thomas Seidl
Professor of Computer Science, LMU Munich, Munich Center for Machine Learning (MCML)
Simon Geisler
Google Research
Oleksandr Shchur
Applied Scientist, Amazon Web Services
Bertrand Charpentier
Pruna AI, Ex-Technical University of Munich, Ex-Twitter
Emmanuel Müller
Professor of Computer Science, Technical University of Dortmund
Christos Faloutsos
CMU