Erdal Kayacan holds a Ph.D. in electrical and electronic engineering from Bogazici University, Turkey. After a post-doc at  KU Leuven‘s division of mechatronics, biostatistics and sensors (MeBioS), he worked in  Nanyang Technological University  at the  School of Mechanical and Aerospace Engineering. Currently, he is associate professor at  Aarhus University, Department of Engineering, where he leads the Artificial Intelligence in Robotics (Air Lab) laboratory. Dr. Kayacan is co-author of a text book “Fuzzy Neural Networks for Real Time Control Applications, Concepts, Modeling and Algorithms for Fast Learning“. He is  an Associate Editor of  IEEE Transactions on Fuzzy Systems  and  Technical Editor of the  IEEE/ASME Transactions Mechatronics.

Robert Babuska is a Professor of Intelligent Control and Robotics at TU Delft, and he has over 24 years of experience with research in control, system identification, computational intelligence, and machine learning, with applications in process control, mechatronics and robotics. Current research interests: reinforcement learning, adaptive control, nonlinear state estimation, control and system identification. In 2012 he founded the TU Delft Robotics Institute. He has served as the Chairman of the IFAC technical committee on Cognition and Control.

Jens Kober is an associate professor at TU Delft, Netherlands. He is a member of the Cognitive Robotics department (CoR), the TU Delft Robotics Institute, and RoboValley. Jens is the recipient of the IEEE-RAS Early Academic Career Award in Robotics and Automation 2018. His Ph.D. thesis has won the 2013 Georges Giralt PhD Award as the best Robotics PhD thesis in Europe in 2012. Jens was an assistant professor at TU Delft (2015-2019), first at the Delft Center for Systems and Control (DCSC) and later at CoR. He worked as a postdoctoral scholar (2012-2014) jointly at the CoR-Lab, Bielefeld University, Germany and at the Honda Research Institute Europe, Germany. From 2007-2012 he was working with Jan Peters as a master's student and subsequently as a Ph.D. student at the Robot Learning Lab, Max-Planck Institute for Intelligent Systems, Empirical Inference Department (formerly part of the MPI for Biological Cybernetics) and Autonomous Motion Department. Jens graduated in Spring 2012 with a Doctor of Engineering “summa cum laude” from the Intelligent Autonomous Systems Group, Technische Universität Darmstadt. Jens is an IEEE Senior Member and ELLIS Scholar. Jens served as co-chair of the IEEE-RAS TC Robot Learning (2016-2021), as the Virtual Conference Arrangements Chair for Robotics: Science and Systems 2020, and as a Program Chair for the Conference on Robot Learning 2020. He currently serves as the Finance Chair for the International Conference on Advanced Intelligent Mechatronics 2021, as senior editor for the IEEE Robotics and Automation Letters, as associate editor for the IEEE Transactions on Robotics and for the IEEE/ASME Transactions on Mechatronics, as editorial board member of the Journal of Machine Learning Research, as editor for the IEEE/RSJ International Conference on Intelligent Robots and Systems, as well as area chair/associate editor for numerous conferences. He has served as reviewer for most well-known journals and conferences in the fields of machine learning and robotics.

Abhinav Valada is an Assistant Professor and Director of the Robot Learning Lab at the University of Freiburg. He is a member of the Department of Computer Science, a principal investigator at the BrainLinks-BrainTools Center, and a founding faculty of the European Laboratory for Learning and Intelligent Systems (ELLIS) unit at Freiburg. He received his Ph.D. in Computer Science from the University of Freiburg in 2019 and his M.S. degree in Robotics from Carnegie Mellon University in 2013. His research lies at the intersection of robotics, machine learning and computer vision with a focus on tackling fundamental robot perception, state estimation and control problems using learning approaches in order to enable robots to reliably operate in complex and diverse domains. Abhinav Valada is a Scholar of the ELLIS Society, a DFG Emmy Noether Fellow, and co-chair of the IEEE RAS Technical Committee on Robot Learning. He is an Associate Editor for the IEEE Robotics and Automation Letters, IEEE International Conference on Robotics and Automation, and IEEE/RSJ International Conference on Intelligent Robots and Systems. He regularly serves as an Area Chair and in the Program Committees of several top conferences such as Robotics: Science and Systems (RSS), Conference on Robot Learning (CoRL), AAAI Conference on Artificial Intelligence (AAAI), and European Conference on Artificial Intelligence (ECAI).

Alexandros Iosifidis is a Professor at Aarhus University, Denmark. He leads the Machine Learning & Computational Intelligence group at the Department of Electrical and Computer Engineering, and the Machine Intelligence research area of the University's Centre for Digitalisation, Big Data and Data Analytics. He has contributed to more than thirty R&D projects financed by EU, Greek, Finnish, and Danish funding agencies and companies. He is a Senior Member of ΙΕΕΕ and he was as an Officer of the Finnish IEEE Signal Processing-Circuits and Systems Chapter from 2016 to 2018. He is a member of the EURASIP Technical Area Committee on Visual Information Processing, and a member of the IEEE Technical Committee on Machine Learning for Signal Processing. He has (co-)authored 92 journal papers, 121 papers in international conferences and workshops and contributed 10 chapters to edited books in his area of expertise. He has co-edited the book “Deep Learning for Robot Perception and Cognition”, Elsevier, 2022. He is currently the Associate Editor in Chief of Neurocomputing for neural networks area, an Area Editor of Signal Processing: Image Communication, and an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems. He was an Area Chair for IEEE ICIP (2018-2022), a Technical Program Committee Chair for EUSIPCO (2019,2021), and Publicity co-Chair for IEEE ICME 2021.

Nikolaos Passalis received the B.Sc. degree in informatics, the M.Sc. degree in information systems, and the Ph.D. degree in informatics from the Aristotle University of Thessaloniki, Thessaloniki, Greece, in 2013, 2015, and 2018, respectively. Since 2019, he has been a post-doctoral researcher with the Aristotle University of Thessaloniki, while from 2018 to 2019 he also conducted post-doctoral research at the Faculty of Information Sciences, Tampere University, Finland. He has (co)authored more than 45 journal articles, 60 conference papers and contributed 8 chapters to edited books in his area of expertise. Over 1600 citations have been recorded to his publications and his H-index is 21 according to Google scholar. His research interests include deep learning, machine learning, computer vision, robotics, and neuromorphic computation.

Anastasios Tefas received the B.Sc. in informatics in 1997 and the Ph.D. degree in informatics in 2002, both from the Aristotle University of Thessaloniki, Greece. Since 2022 he has been Professor at the Department of Informatics, Aristotle University of Thessaloniki. Dr. Tefas participated in 30 research projects financed by national and European funds. He is the Coordinator of the H2020 project OpenDR, “Open Deep Learning Toolkit for Robotics”. He is Area Editor in Signal Processing: Image Communications journal. He has co-authored 135 journal papers, 255 papers in international conferences and contributed 17 chapters to edited books in his area of expertise. He has co-organized more than 15 workshops, tutorials and special sessions. He has co-edited the book “Deep Learning for Robot Perception and Cognition”, Elsevier, 2022. Over 8000 citations have been recorded to his publications and his H-index is 45 according to Google scholar. His current research interests include computational intelligence, deep learning, machine learning, digital signal and image analysis and retrieval, computer vision and robotics.