Member role: School Board
Matthias Hein is Bosch endowed Professor of Machine Learning and the coordinator of the international master program in machine learning at the University of Tübingen. He is member of the Excellence Cluster “Machine Learning: New Perspectives for Science” and the Tübingen AI Center. His main research interests are to make machine learning systems robust, safe and explainable and to provide theoretical foundations for machine learning, in particular deep learning. He serves regularly as area chair for ICML, NeurIPS or AISTATS and has been action editor for Journal of Machine Learning Research (JMLR) from 2013 to 2018. He is an ELLIS Fellow and has been awarded the German Pattern recognition award, an ERC Starting grant and several best paper awards (NeurIPS, COLT, ALT).
Wojciech Samek is a professor at TU Berlin, head of the AI Department at Fraunhofer HHI, and a fellow at BIFOLD and ELLIS Unit Berlin. His research focuses on explainable AI (XAI), covering method development, theoretical studies, and applications in medicine and geoscience. His pioneering contributions to XAI include key methods like Layer-wise Relevance Propagation (LRP) [1] and advancements in concept-level explainability, evaluation of explanations, and XAI-based model- and data improvement.
He has edited two books on XAI, served as a senior editor for IEEE TNNLS and associate editor for various other journals, and held area chair roles at NeurIPS, ICML, and NAACL. He is a member of Germany’s Platform for AI and serves on the boards of AGH University’s AI Center, HEIBRiDS, and ELIZA. He has received multiple best paper awards, including from Pattern Recognition (2020), Digital Signal Processing (2022), and the IEEE Signal Processing Society (2025).
[1] Bach, S, Binder, A, Montavon, G, Klauschen, F, Müller, K-R, Samek, W (2015). On Pixel-wise Explanations for Non-Linear Classifier Decisions by Layer-wise Relevance Propagation. PLOS ONE, 10(7):e0130140.
Abhinav Valada is a Full Professor (W3) at the University of Freiburg, where he directs the Robot Learning Lab. He is a member of the Department of Computer Science, the BrainLinks-BrainTools center, and a founding faculty of the ELLIS unit Freiburg. Abhinav is a DFG Emmy Noether AI Fellow, Scholar of the ELLIS Society, IEEE Senior Member, and Chair of the IEEE Robotics and Automation Society Technical Committee on Robot Learning.
He received his PhD (summa cum laude) working with Prof. Wolfram Burgard at the University of Freiburg in 2019, his MS in Robotics from Carnegie Mellon University in 2013, and his BTech. in Electronics and Instrumentation Engineering from VIT University in 2010. After his PhD, he worked as a Postdoctoral researcher and subsequently an Assistant Professor (W1) from 2020 to 2023. He co-founded and served as the Director of Operations of Platypus LLC from 2013 to 2015, a company developing autonomous robotic boats in Pittsburgh, and has previously worked at the National Robotics Engineering Center and the Field Robotics Center of Carnegie Mellon University from 2011 to 2014.
Abhinav’s research lies at the intersection of robotics, machine learning, and computer vision with a focus on tackling fundamental robot perception, state estimation, and planning problems to enable robots to operate reliably in complex and diverse domains. The overall goal of his research is to develop scalable lifelong robot learning systems that continuously learn multiple tasks from what they perceive and experience by interacting with the real world. For his research, he received the IEEE RAS Early Career Award in Robotics and Automation, IROS Toshio Fukuda Young Professional Award, NVIDIA Research Award, AutoSens Most Novel Research Award, among others. Many aspects of his research have been prominently featured in wider media such as the Discovery Channel, NBC News, Business Times, and The Economic Times.
Daniel Cremers received Bachelor degrees in Mathematics (1994) and Physics (1994), and a Master’s degree in Theoretical Physics (1997) from the University of Heidelberg. In 2002 he obtained a PhD in Computer Science from the University of Mannheim, Germany. Subsequently he spent two years as a postdoctoral researcher at the University of California at Los Angeles (UCLA) and one year as a permanent researcher at Siemens Corporate Research in Princeton, NJ. From 2005 until 2009 he was associate professor at the University of Bonn, Germany. Since 2009 he holds the Chair of Computer Vision and Artificial Intelligence at the Technical University of Munich. His publications received several awards, including the ‘Best Paper of the Year 2003’ (Int. Pattern Recognition Society), the ‘Olympus Award 2004’ (now called ‘German Pattern Recognition Award’), the ‘2005 UCLA Chancellor’s Award for Postdoctoral Research’ and the ‘ECCV 2024 Koenderink Test of Time Award’. For pioneering research he received a Starting Grant (2009), two Proof of Concept Grants (2014 & 2018), a Consolidator Grant (2015) and an Advanced Grant (2020) by the European Research Council. Professor Cremers has served as associate editor for several journals including the International Journal of Computer Vision, the IEEE Transactions on Pattern Analysis and Machine Intelligence and the SIAM Journal of Imaging Sciences. He has served as area chair (associate editor) for ICCV, ECCV, CVPR, ACCV, IROS, etc, and as program chair for ACCV 2014. In 2018 he organized the largest ever European Conference on Computer Vision in Munich with 3300 delegates. He is member of the Bavarian Academy of Sciences and Humanities. He served as honorary member of the Dagstuhl Scientific Directorate. In December 2010 he was listed among “Germany’s top 40 researchers below 40” (Capital). On March 1st 2016, Prof. Cremers received the Gottfried Wilhelm Leibniz Award, the biggest award in German academia. The year 2022/23 he spent on sabbatical at Oxford University hosted by the Deparment of Engineering and as a visiting fellow of Exeter College. According to Google Scholar, Prof. Cremers has an h-index of 123 and his papers have been cited 79669 times. According to Guide2Research he is among the most influential computer scientists in Germany. From 2020 until 2023, he was listed among the top 10 most influential scholars in robotics of the last decade. Since 2023, he serves as President of the European Computer Vision Association. He engages as co-founder, advisor and business angel to several startups.
Stefan Roth received the Diplom degree in Computer Science and Engineering from the University of Mannheim, Germany in 2001. In 2003 he received the ScM degree in Computer Science from Brown University, and in 2007 the PhD degree in Computer Science from the same institution. Since 2007, he is on the faculty of Computer Science at Technische Universität Darmstadt, Germany, where he is currently full professor (W3). His research interests include learning approaches to scene understanding, image generation, and motion estimation as well as explainable AI. He received several awards, including the Olympus-Prize 2010 of the German Association for Pattern Recognition (DAGM), the Heinz Maier-Leibnitz Prize 2012 of the German Research Foundation (DFG), the Longuet-Higgins Prize 2020, as well as various paper awards. He is the recipient of two grants from the European Research Council (ERC), a Starting Grant in 2013 and a Consolidator Grant in 2020. He is a Fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS) and directs both the ELLIS Unit at TU Darmstadt and the DAAD-funded Zuse School ELIZA. He serves as program chair of CVPR 2022 and ECCV 2024, as well as regularly as an area chair for CVPR, ICCV, and ECCV. He is a member of the editorial board of the International Journal of Computer Vision (IJCV). He also serves on the scientific councils & boards of TU Darmstadt, TU Graz, Austria, as well as Idiap Research Institute, Switzerland.
Carsten Rother received his diploma degree with distinction in 1999 from the University of Karlsruhe/Germany, and his PhD degree in 2003 from the Royal Institute of Technology (KTH) Stockholm/Sweden. From 2003 until 2013 he was researcher in the Computer Vision Group at Microsoft Research Cambridge/UK, lead by Andrew Blake. From 2014 until 2017 he was full Professor at TU Dresden/Germany. Since 2017 he is full Professor at Uni Heidelberg/Germany, heading the Computer Vision and Learning Lab. He is also coordinating director of the Heidelberg Collaboratory for Image Processing (HCI) and an AI consultant for companies. In the last years, two start-ups emerged from his lab https://rabbitai.de/ and https://www.copresence.tech/. His research interests are in the field of computer vision and machine learning, including related fields such as human-computer interaction and computational imaging. He has been working on a broad range of applications, such as image generation, image editing (incl. image segmentation, alpha matting, and deconvolution), image matching (incl. stereo matching, and scene flow), scene understanding (incl. 6D object pose estimation), and Bio-Imaging (incl. cell tracking). He has published over 270 articles (current H-index 93) at international conferences and journals. He received eight awards, including awards at CVPR ’13, CVPR ’05, CHI ’07, BMVC ’16 and ACCV ’14. He was awarded the DAGM Olympus prize in 2009. He has co-developed two Microsoft Products, GrabCut for Office 2010 and AutoCollage. He received prestigious funding awards, such as an ERC Consolidator Grant. He serves as area chair for major conferences and he has been associated editor for T-PAMI.