Prof. Dr. Mario Fritz is a faculty at the CISPA Helmholtz Center for Information Security, an honorary professor at Saarland University, and a fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS). Until 2018, he led a research group at the Max Planck Institute for Computer Science. Previously, he was a PostDoc at the International Computer Science Institute (ICSI) and UC Berkeley after receiving his PhD from TU Darmstadt and studying computer science at FAU Erlangen-Nuremberg. His research focuses on trustworthy artificial intelligence, especially at the intersection of information security and machine learning. He is Associate Editor of the journal "IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)," coordinates the Helmholtz project "Trustworthy Federated Data Analytics," and has published over 100 scientific articles - 80 of them in top conferences and journals.
CVPR
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
CVPR
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
CVPR
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
NDSS
Network and Distributed Systems Security (NDSS) Symposium 2019Annual Network and Distributed System Security Symposium
Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
WACV
IEEE Winter Conference on Applications of Computer Vision (WACV)IEEE Winter Conference on Applications of Computer Vision (WACV)
ICLR
International Conference on Learning RepresentationsInternational Conference on Representation Learning (ICLR)
NeurIPS
Advances in Neural Information Processing Systems 31 (NeurIPS 2018)Conference on Neural Information Processing Systems
ECCV
Proceedings of the European Conference on Computer Vision (ECCV)European Conference on Computer Vision