Manuel Günther is an Assistant Professor in AI and Machine Learning at the University of Zurich with 11 years of research and engineering experience bridging classical image processing and modern deep learning. He teaches deep learning, has supervised seven PhD students and over 60 bachelor/master theses, and is planning a transition to a professorial role after June 2026. His work focuses on robust, fair and explainable image-based AI—especially on face and medical imagery—while developing evaluation metrics and defenses against unexpected inputs and attacks. Practically minded, he has contributed to C++ and Python open-source toolchains (including Bob and Caffe optimizations) and now implements PyTorch libraries such as Gabor wavelets and tools for evaluating algorithms under unknown inputs. He often combines traditional feature-based methods with deep neural networks to improve interpretability and robustness, reflecting a long-standing commitment to reproducible, production-ready implementations.
11 years of coding experience
13 years of employment as a software developer
Dr.-Ing. Biometrie, Dr.-Ing. Biometrie at Ruhr University Bochum
Diplom-Informatiker Informatik, Diplom-Informatiker Informatik at Technische Universität Ilmenau
Abitur Hauptfächer: Mathematik, Informatik, Abitur Hauptfächer: Mathematik, Informatik at Spezialschulteil für Mathematik/ Naturwissenschaften & Informatik; Albert-Schweitzer-Gymnasium Erfurt
Contributions:2 PRs, 51 pushes, 2 branches in 1 year 4 months
bobpython-bindingspythonmeasure
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