Member role: Academic Fellow
Jun.-Prof. Dr. Maria Kalweit holds the Tenure-Track CRIION Professorship for Bioinformatics: AI for Oncology Research at the Department of Computer Science, University of Freiburg. She earned her PhD in Computer Science from the University of Freiburg in 2022 under Prof. Joschka Boedecker. She also serves as Chief Scientific Officer at the Collaborative Research Institute Intelligent Oncology (CRIION) of the Mertelsmann Foundation gGmbH. Her research centers on robust, efficient, and explainable machine learning for oncology, with a focus on limited-data settings, biological variability, and technical heterogeneity. Her work has resulted in multiple patents and a digital biomarker. Her paper “Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller” received the Best Paper Award at IJCNN 2018. She has further been recognized with the Wolfgang-Gentner-Nachwuchsförderpreis (2023) and the Gips-Schüle-Nachwuchspreis in Technikwissenschaften (2024).
Hinrich Schuetze is Professor for Computational Linguistics and co-director of the Center for Information and Language Processing at the University of Munich (LMU Munich). He received his PhD from Stanford in 1995 for his early research on embeddings (ACL Test-of-Time Paper Award). He then worked on natural language processing and information retrieval technology at Xerox PARC, at several Silicon Valley startups and at Google 1995-2004 and 2008/9. Hinrich is a coauthor of Foundations of Statistical Natural Language Processing (with Chris Manning) and Introduction to Information Retrieval (with Chris Manning and Prabhakar Raghavan). He was awarded a European Research Council Advanced Grant in 2017. Hinrich served as president of the Association for Computational Linguistics in 2020. He is a fellow of ACL, ELLIS and HessianAI.
Simone Schaub-Meyer is an assistant professor and leads the research group Image and Video Analysis at the Technical University of Darmstadt. She is an ELLIS member and a member of the Hessian Center for Artificial Intelligence (hessian.AI). The focus of her research is on developing efficient, robust, and understandable methods and algorithms for image and video analysis. She received the renowned Emmy Noether Programme (ENP) grant from the German Research Foundation (DFG), supporting her research on Interpretable Neural Networks for Dense Image and Video Analysis. She obtained her doctoral degree from ETH Zurich, advised by Prof. Dr. Markus Gross and in collaboration with Disney Research Zurich. Her doctoral thesis was awarded the ETH Medal.
Tim Welschehol is a research group leader in the Robot Learning Lab at the university of Freiburg. He is a member of the Department of Computer Science and the BrainLinks-BrainTools center.
He received his PhD in Robotics working with Prof. Wolfram Burgard at the Autonomous Intelligent Systems group in 2020. After his PhD, he worked as a postdoctoral researcher (2020-2022) and subsequently as commissary lead (2022-2023) of the Autonomous Intelligent Systems group.
His research work is in the field of robot learning with focus on mobile manipulation and long horizon reasoning. The overarching goal of his research is to enable robots to autonomously learn, reason and act in human centered environments. His most acknowledged work, which was awarded with the Ewald Marquardt Zukunftspreis 2023 and a best paper award, is “Learning Navigation for Arbitrary Mobile Manipulation Motions in Unseen and Dynamic Environments”.
Group Leader and Head of the Department for Distributed Intelligence / Autonomous Learning,
Tübingen University, Department of Computer Science
Jilles Vreeken is tenured faculty at the CISPA Helmholtz Center for Information Security, honorary professor at Saarland University, and fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS). He obtained his Ph.D. in 2009 from Utrecht University, was a post-doctoral researcher at Antwerp University until 2013, and both independent research group leader (W2) at Saarland University and senior researcher at the Max Planck Institute for Informatics until 2018. His research focuses on developing well-founded theory and efficient methods that give clear and actionable insight into large, complex data and models. In more general terms, he likes data mining, machine learning, and causal inference.
Jakob has been Professor for “Machine Learning in Science” since May 2020. The W3 professorship has been set up as part of the Cluster of Excellence “Machine Learning: New Perspectives for the Sciences”. He is also an Adjunct Research Scientist at the Max Planck Institute for Intelligent Systems, Director of the Bernstein Center for Computational Neuroscience, and an ELLIS Fellow and member of the ELLIS Unit Tübingen. He serves as a speaker of the DFG Collaborative Research Center SFB 1233 Robust Vision, the Excellence Cluster Machine Learning: New Perspectives for Science and the EKFS-training group ClinBrAIn: AI for Clinical Brain Research.
Jakob studied mathematics at Oxford University, worked as a PhD student at the Max Planck Institute for Biological Cybernetics in Tübingen, as a postdoc at the Gatsby Unit at University College London, and as a Bernstein Fellow in Tübingen. He was a Max Planck Group Leader at the Caesar Research Centre in Bonn, a Professor at the Centre for Cognitive Science at TU Darmstadt, and from 2018 to 2020, Professor of Computational Neuroengineering at TU Munich. He was a member of the Young Academy at the German Academy of Sciences Leopoldina (2013-2018), and a FENS Kavli Scholar of Excellence (2018-2023).
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.