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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Homepage
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Citations & Impact
All-time
Citations
26,756
H-index
56
i10-index
165
Publications
20
Co-authors
83
list available
Contact
No contact links provided.
Publications
42 items
Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy
2026
Cited
0
Task-Aware Calibration: Provably Optimal Decoding in LLMs
2026
Cited
0
Transferable SCF-Acceleration through Solver-Aligned Initialization Learning
2026
Cited
0
EgoDyn-Bench: Evaluating Ego-Motion Understanding in Vision-Centric Foundation Models for Autonomous Driving
2026
Cited
0
Interpolating Discrete Diffusion Models with Controllable Resampling
2026
Cited
0
Exact Certification of Neural Networks and Partition Aggregation Ensembles against Label Poisoning
2026
Cited
0
Amplified Patch-Level Differential Privacy for Free via Random Cropping
2026
Cited
0
Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
2026
Cited
0
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Resume (English only)
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
83 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)
Co-author 4
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
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