Prof. Jan Peters
Jan Peters is a full professor (W3) for Intelligent Autonomous Systems at the Computer Science Department of the Technische Universitaet Darmstadt since 2011, and, at the same time, he is the dept head of the research department on Systems AI for Robot Learning (SAIROL) at the German Research Center for Artificial Intelligence (Deutsches Forschungszentrum für Künstliche Intelligenz, DFKI) since 2022. He is also is a founding research faculty member of the Hessian Center for Artificial Intelligence. Jan Peters has received the Dick Volz Best 2007 US PhD Thesis Runner-Up Award, the Robotics: Science & Systems - Early Career Spotlight, the INNS Young Investigator Award, and the IEEE Robotics & Automation Society's Early Career Award as well as numerous best paper awards. In 2015, he received an ERC Starting Grant and in 2019, he was appointed IEEE Fellow, in 2020 ELLIS fellow and in 2021 AAIA fellow.
Despite being a faculty member at TU Darmstadt only since 2011, Jan Peters has already nurtured a series of outstanding young researchers into successful careers. These include new faculty members at leading universities in the USA, Japan, Germany, Finland and Holland, postdoctoral scholars at top computer science departments (including MIT, CMU, and Berkeley) and young leaders at top AI companies (including Amazon, Boston Dynamics, Google and Facebook/Meta).
Jan Peters has studied Computer Science, Electrical, Mechanical and Control Engineering at TU Munich and FernUni Hagen in Germany, at the National University of Singapore (NUS) and the University of Southern California (USC). He has received four Master's degrees in these disciplines as well as a Computer Science PhD from USC. Jan Peters has performed research in Germany at DLR, TU Munich and the Max Planck Institute for Biological Cybernetics (in addition to the institutions above), in Japan at the Advanced Telecommunication Research Center (ATR), at USC and at both NUS and Siemens Advanced Engineering in Singapore. He has led research groups on Machine Learning for Robotics at the Max Planck Institutes for Biological Cybernetics (2007-2010) and Intelligent Systems (2010-2021).
Speaker: Prof. Jan Peters
Affiliations: Technische Universitaet Darmstadt, Germany
Speaker: Prof. Angelo Cangelosi
Affiliations: University of Manchester and Alan Turing Institute, UK
Prof. Angelo Cangelosi
Angelo Cangelosi is Professor of Machine Learning and Robotics at the University of Manchester (UK) and co-director and founder of the Manchester Centre for Robotics and AI. He holds an European Research Council (ERC) Advanced grant. He also is Turing Fellow at the Alan Turing Institute London. His research interests are in cognitive and developmental robotics, neural networks, language grounding, human robot-interaction and trust, and robot companions for health and social care. Overall, he has secured over £38m of research grants as coordinator/PI, including the ERC Advanced eTALK, the UKRI TAS Trust Node and CRADLE Prosperity, the US AFRL project THRIVE++, and numerous Horizon and MSCAs grants. Cangelosi has produced more than 300 scientific publications. He is Editor-in-Chief of the journals Interaction Studies and IET Cognitive Computation and Systems, and in 2015 was Editor-in-Chief of IEEE Transactions on Autonomous Development. He has chaired numerous international conferences, including ICANN2022 Bristol, and ICDL2021 Beijing. His book “Developmental Robotics: From Babies to Robots” (MIT Press) was published in January 2015, and translated in Chinese and Japanese. His latest book “Cognitive Robotics” (MIT Press), coedited with Minoru Asada, was recently published in 2022.
Abstract: Growing theoretical and experimental research on action and language processing and on number learning and gestures clearly demonstrates the role of embodiment in cognition and language processing. In psychology and neuroscience, this evidence constitutes the basis of embodied cognition, also known as grounded cognition (Pezzulo et al. 2012). In robotics and AI, these studies have important implications for the design of linguistic capabilities in cognitive agents and robots for human-robot collaboration, and have led to the new interdisciplinary approach of Developmental Robotics, as part of the wider Cognitive Robotics field (Cangelosi & Schlesinger 2015; Cangelosi & Asada 2022). During the talk we will present examples of developmental robotics models and experimental results from iCub experiments on the embodiment biases in early word acquisition and grammar learning (Morse et al. 2015; Morse & Cangelosi 2017) and experiments on pointing gestures and finger counting for number learning (De La Cruz et al. 2014). We will then present a novel developmental robotics model, and experiments, on Theory of Mind and its use for autonomous trust behavior in robots (Vinanzi et al. 2019, 2021). The implications for the use of such embodied approaches for embodied cognition in AI and cognitive sciences, and for robot companion applications will also be discussed.
Prof. Gianluca Antonelli
Gianluca Antonelli is Full Professor at the ``University of Cassino and Southern Lazio''. His research interests include marine and industrial robotics, multi-agent systems, identification. He has published more than 60 international journal papers and 130 conference papers, he is author of the book ``Underwater Robots'' (Springer, 2003, 2006, 2014, 2018) and co-authored the chapter ``Underwater Robotics'' for the Springer Handbook of Robotics, (Springer, 2008, 2016). From 2016 to 2021 he has been member elected of the "IEEE Robotics & Automation Society" (RAS) Administrative Committee, he has been coordinator of the EuRobotics Topic Group in Marine Robotics, he has been secretary of the IEEE-Italy section, he has been chair of the IEEE RAS Italian Chapter, he has been Chair of the IEEE RAS Technical Committee in Marine Robotics. He served in the Editorial Board of the IEEE Transactions on Robotics, IEEE Transactions on Control Systems Technology, Springer Journal of Intelligent Service Robotics. He is Fellow IEEE since 2021. Since October 2020, he is top 1% in the field "Industrial Engineering & Automation" according to common metrics and the SCOPUS database. Since December 2021, he is top 100 Italian scientists according to google scholar h-index in the category "Electronics and Electrical Engineering".
Speaker: Prof. Gianluca Antonelli
Affiliations: University of Cassino and Southern Lazio, Italy
Speaker: Prof. Zhaojie JU
Affiliations: University of Portsmouth, UK
Prof. Zhaojie JU
Zhaojie Ju is Chair in Machine Learning and Robotics at the University of Portsmouth, Principle Investigator of EU Interreg Project, Director of Healthcare and Wearable Robotics Research, and Chair of IEEE SMC Portsmouth Chapter. He has attracted over €10 million research fund as PI/CoI and authored/co-authored over 250 publications in journals, book chapters, and conference proceedings (over 100 SCI-index papers). He has received 7 Best Paper Awards and 1 Best AE Award in ICRA2018. His research interests include machine intelligence, pattern recognition and their applications in human robot interaction/collaboration, robot skill learning and healthcare & wearable robotics.
Prof. Ju is an Associate Editor of several journals, such as IEEE TRANSACTIONS ON CYBERNETICS, IEEE TRANSACTIONS ON NEUROL NETWORKS AND LEARNING SYSTEMS and IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS. He is JSPS Fellow and IEEE Senior Member.
Abstract: Autonomous interaction abilities are important for robot-assisted therapy systems to assess children with autism spectrum disorder (ASD). This talk presents a multi-modal sensing system that automatically extracts and fuses sensory features such as body motion features, facial expressions, and gaze features, further assessing the children behaviours by mapping them to therapist specified behavioural classes. Experimental results show that the developed system has a capability of interpreting characteristic data of children with ASD, thus has the potential to increase the autonomy of robots under the supervision of a therapist and enhance the quality of the digital description of children with ASD. The research outcomes pave the way to a feasible machine-assisted system for their behaviour assessment.
Prof. Haibo Liu
Haibo Liu, is professor and Ph.D. supervisor of school of mechanical engineering at Dalian University of Technology (DUT), China. He received his B.Eng. and Ph.D. degrees in Mechanical and Electrical Engineering from DLUT, in 2006 and 2012, respectively. He is IEEE member, ASME member, senior member of Chinese Society of Mechanical Engineering. He has served as the Guest Editor of the Frontiers in Mechanical Engineering, Frontiers in Materials and China Measurement & Testing Technology, and deputy secretary general of the SAC/TC22 International Standardization Working Committee. His main research interests include, Measurement-machining integrated manufacturing, On-machine measurement, Phase-change fixturing based adaptive machining, Industrial-robot aided manufacturing. He has published over 80 peer-reviewed SCI/EI journal papers like International Journal of Machine Tools and Manufacture, International Journal of Mechanical Sciences, and IEEE/ASME Transactions on Mechatronic, and over 100 authorized or pending patents. He holds over 20 major projects, including National Natural Science Foundation of China, the sub-project of the Science Challenge Project, the sub-projects of the National Key Research and Development Program and National Science and Technology Major Project of China, etc. He is the recipient of the 1st prize for Liaoning Science and Technology Progress Award (twice), the 1st prize for Science and Technology Progress Award of China Machinery Industry Federation. He was awarded the Young Changjiang Scholars Program of the Ministry of Education in 2022 and the Liaoning Provincial Outstanding Youth Fund Program in 2020.
Speaker: Prof. Haibo Liu
Affiliations: Dalian University of Technology, China