I am a researcher and engineer with more than 7 years of AI research experience and 12 years of general software engineering experience across academia and industry. Currently, I am a senior research scientist at Google DeepMind focusing on uncertainty estimation and robustness and safety evaluation of generative AI, both in vision and language applications. I helped develop and ship the first large-scale image watermarking system, called SynthID. In 2022, I finished my PhD at the Max Planck Institute for Informatics where I worked on adversarial robustness, quantization and uncertainty estimation with deep neural networks, focused on computer vision applications. My PhD was awarded the dissertation award of German Association for Pattern Recognition in 2022, an outstanding paper award at the CVPR 2021 CV-AML workshop, a Qualcomm Innovation Fellowship in 2019 and I was selected to participate in the Heidelberg Laureate Forum. Before, I finished both my MSc and Bsc at RWTH Aachen University, being supported by a Germany Scholarship and awarded the STEM Award IT and RWTH Aachen’s Springorum Denkmünze for my Msc. As part of my studies, I spent time at the Max Planck Institute for Intelligent Systems, researching 3D reconstruction from sparse point clouds using deep neural networks. I also worked on pedestrian detection at Hyundai MOBIS, line segment and keypoint tracking at Fyusion, and spent a semester abroad at Georgia Tech working on video segmentation. My bachelor thesis led to the largest evaluation and benchmark of superpixel segmentation algorithms to date. In parallel to my research, I worked as a web engineer until 2021, developing web applications for small and medium-sized business and web analytics solutions at the Fraunhofer Institute for Communication, Information Processing and Ergonomics. Large parts of my work is public on GitHub, with more than 6k stars and 2.7k forks and I blog at davidstutz.de.
Last updated: 17.11.2023