ORGANIZERS

Timo Sämann

Timo Sämann is a Product Technical Leader and Expert at Valeo within the Research Group for Automated Driving in Germany and specialized in visual perception with deep learning methods. He leads projects on how to make deep neural networks safer and is doing his PhD at the Technical University of Ilmenau. He was the main organizer of the SAIAD workshops in 2019 and 2020 and is a member of several program committees at AI conferences and workshops.

Thomas Stauner

Thomas studied computer science at Technical University of Munich and University of Edinburgh. He received his PhD degree at Technical University of Munich in the area of cyber-physical systems. After joining BMW Group he was concerned with lifecycle management of the hardware/software system in the vehicles and with software development for eMobility. He was responsible for software integration of electric drive software and for the embedded software development process and its tooling at BMW. Currently he is responsible for paving the way for safety-related machine learning applications at BMW, with focus on computer vision.

Stefan Milz

received his Ph.D. degree in Physics from the Technical University of Munich. He is Managing Director of Spleenlab.ai, a self-founded machine learning company focusing on safety-critical mobility applications (UAV, Automated Driving, Air-Taxis) deploying SLAM, sensor-fusion, perception functions into the real world with regard to saftey standards. He is also a research fellow at the TU-Ilmenau. Stefan Milz is the author and co-author of more than 60 patents and more than 60 publications.

Markus Enzweiler

Markus Enzweiler received the PhD degree in computer science from the University of Heidelberg, Germany, in 2011. Since 2010, he has been with Mercedes-Benz R&D. His current work focuses on scene understanding and AI for self-driving cars. In 2012, he was awarded both the IEEE Intelligent Transportation Systems Society Best PhD Dissertation Award and the Uni-DAS Research Award for his work on vision-based pedestrian recognition. He was part of the Daimler team that received the IEEE Intelligent Transportation Systems Society Outstanding Application Award in 2014. Since 2014, he is a junior fellow of the German Informatics Society.

Frédérik Blank

Frédérik Blank holds a double-diploma in electrical engineering from Technical University Darmstadt (Germany) and Ecole Supérieure d'Electricité Gif-sur-Yvette (France). From 2007 to 2015 he worked for ABB AG in various positions as researcher, software developer, project manager and product manager in the area of data analytics, optimization and map-based visualization techniques for distributed infrastructure automation. Since 2015 he has been working at Robert Bosch GmbH as project leader in multiple large automated driving joint pre-development projects with focus on (assured) artificial intelligence and tele-operated driving.

Seyed Eghbal Ghobadi

Seyed Eghbal Ghobadi is a professor of computer vision and machine learning at Technische Hochschule Mittelhessen -University of Applied Sciences in Germany. He studied Electrical Engineering at Technical University of Braunschweig and received his PhD in 2010 from Center for Sensor Systems at University of Siegen in the field of computer vision and machine learning. From 2010 to 2017, he was with General Motors/Opel and worked as Algorithm Design Engineer on driving assistance system projects. From 2017 to 2021, he was the AI Technical Specialist in Advanced Engineering department of PSA/Opel with the main working focus on automated driving using artificial intelligence. His main interest lies in the field of deep learning for computer vision as well as quality assurance for artificial intelligence.

Oliver Wasenmüller

Oliver Wasenmüller is full Professor at the Mannheim University for Applied Science. His research is in the intersection of Computer Vision and Artificial Intelligence with a focus on automotive. Previously he was a team leader for "machine vision and autonomous vehicles" at the German Research Center for Artificial Intelligence (DFKI). He is both speaker and reviewer in many scientific conferences in this field and co-organizes the ACM Computer Science in Cars Symposium (CSCS) as well as the IEEE IV Workshop on Online Map Validation and Road Model Creation.

Oliver Grau

Oliver Grau works for Intel Labs in Germany on topics of automated driving. He joined Intel as co-director of the Intel-Visual Computing Institute and he worked previously as a Lead Technologist for BBC R&D in London, UK on computer vision projects for innovative media production systems.

Peter Schlicht

Peter Schlicht studied mathematics with a minor in computer science in Göttingen and received his doctorate in pure mathematics from the University of Leipzig. After a two-year research stay at the Ecole Polytechnique Fédérale (EPFL) in Lausanne (Switzerland), he joined Volkswagen Group Research in 2016 as an AI architect. In 2020, he joined CARIAD as the lead of the competence center on Artificial Intelligence. He is particularly interested in methods for monitoring, robustifying and verifying safety of deep neural networks, as well as raising data and energy efficiency in the development and inference of DNNs in automotive industry.

Fabian Hüger

Fabian Hueger holds a Dipl.-Ing. and Dr.-Ing. in Electrical Engineering by University of Kassel. During a Fulbright Scholarship he received a M.Sc. in Electrical and Computer Engineering at University of California Santa Barbara. He joined Volkswagen Group Research in 2010 and is currently performing research on AI technologies for automated driving.

Ruby Moritz

Ruby Moritz studied Bioinformatics at the Martin-Luther-University Halle-Wittenberg in Halle and switched to Computer science for her doctorate at the University of Leipzig. After a two year Post-doc at the Otto-von-Guericke-University in Magdeburg she joined Volkswagen Group Researchs Architecture and AI-Team. Always her prime research interest was and is the analysis and design of systems complex enough to be rendered as black-box. Her current goal is to make autonomous driving measurably safe.

Joachim Sicking

Joachim Sicking is a data scientist and machine learning researcher at Fraunhofer IAIS with a background in physics. He is interested in methods of distributed machine learning and their application in the field of autonomous driving. Another focus of his work are ML projects in the context of industrial IoT with a focus on questions of failure prediction and production optimization.

Google Sites

Report abuse