The IMOL Community

Gianluca Baldassarre received a bachelor and master in economics in 1998, and a Specialization Course in “Cognitive Psychology and Neural Networks” in 1999, from the Sapienza University of Rome, Italy. He received a PhD in Computer Science in 2003, from the University of Essex, Colchester, U.K. He later joined the Italian Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy where he was: Postdoc; Researcher since 2006, Associate Researcher since 2020, and Director of Research since 2021; Coordinator of the Research Group ISTC-CNR “Laboratory of Embodied Natural and Artificial Intelligence” since 2006; Coordinator of various EU Projects among which “IM-CLeVeR – Intrinsically Motivated Cumulative Learning Versatile Robots”, 2009-2013, and “GOAL-Robots – Goal-based Open-ended Autonomous Learning Robots”, 2016-2021. He is the President of the “Advanced School in AI” since 2018, and is co-founder and partner of the start-up AI2Life, a CNR spin-off, since 2020. His research interests are on open-ended learning of sensorimotor skills driven by extrinsic and intrinsic motivations, autonomous learning robots, neural networks and hierarchical reinforcement learning, system-level computational models of brain and behaviour, and the synergies between studies of natural and artificial intelligence.

Bruno C. da Silva is an Assistant Professor in the College of Information and Computer Sciences at the University of Massachusetts. Prior to joining the University of Massachusetts, Bruno was an associate professor at the Institute of Informatics at the Federal University of Rio Grande do Sul (UFRGS), in Brazil. Before that, he worked as a postdoctoral associate at the Aerospace Controls Laboratory at MIT (2015). Bruno received his Ph.D. in Computer Science from the University of Massachusetts (2014), under the supervision of Prof. Andrew Barto. Both his MSc. (2007) and B.S. cum laude (2004) degrees are in Computer Science from the Federal University of Rio Grande do Sul, in Brazil. Bruno worked as a visiting researcher, on several occasions, at the Laboratory of Computational Neuroscience, in Rome, Italy, developing novel control algorithms for humanoid robots. He has also worked at Adobe Research, in California, developing large-scale machine learning techniques for digital marketing optimization. Bruno's research interests lie in the intersection of machine learning, reinforcement learning, optimal control theory, and robotics, and include the construction of hierarchical policies, active learning, Bayesian optimization applied to control, and machine learning algorithms with high-probability safety and fairness guarantees.

Cédric Colas is a postdoctoral researcher in the Computational Cognitive Science Lab at MIT. He holds a Master's degree in Cognitive Science from École Normale Supérieure in Paris and obtained a PhD in Artificial Intelligence from the University of Bordeaux under the supervision of Olivier Sigaud and Pierre-Yves Oudeyer. His PhD thesis introduced the concept of autotelic learning as a computational framework for endowing artificial agents with the ability to represent and pursue their own goals. Through the co-evolution of goal generation and goal achievement processes, autotelic learning makes the first steps towards a computational model of human’s ability to grow repertoires of skills throughout a lifetime. His current research interests include the examination of the role of linguistic interactions in shaping the goal representations of artificial agents.

Daniel Polani is Professor of Artificial Intelligence, Director of the Centre of Artificial Intelligence, Robotics and Neural Systems (CAIRNS) and Head of the Adaptive Systems Research Group at the School of Physics, engineering and Computer Science at the University of Hertfordshire.
His research interests include principles of cognition, intelligence and robotics from first, especially information-theoretic, principles. Ramifications of this research range from practical applications to more fundamental questions, such as the role of embodiment, intrinsic motivations and taskless utilities, to questions from cognitive science, psychology, social science, and biology.

Georg Martius is leading the research group on Autonomous Learning at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. Before joining the MPI in Tübingen, he was a postdoc fellow at the IST Austria and was a postdoctoral researcher at the Max Planck Institute for Mathematics in the Sciences in Leipzig. He received his Ph.D. from the University of Göttingen and his computer science degree from University of Leipzig. His research focus is on machine learning for robotics, including internal model learning, reinforcement learning, intrinsic motivations, representation learning, differentiable combinatorial optimization and haptics.

Vieri Giuliano Santucci is a researcher at the Institute of Cognitive Sciences and Technologies of the Italian National Council of Research (ISTC-CNR, Rome). He holds a Ph.D. in Computer Science at the University of Plymouth (UK), an M.S. degree in theories and techniques of knowledge, faculty of Philosophy (University of Rome “La Sapienza”) and a B.Sc. degree in Philosophy (University of Pisa). His research mainly focuses on cognitive/autonomous robotics and machine learning (and in particular reinforcement learning), developing robotic architectures and algorithms for intrinsically motivated open-ended learning. He is also interested in topics related to cognitive sciences and computational neuroscience.

Rania Rayyes is a junior professor in AI and Robotics at Karlsruhe Institute for Technology (KIT), Germany. Before joining KIT, she worked as postdoctoral researcher for two years at the Institute for Robotics and Process Informatics (IRP), Technische Universitat Braunschweig, Germany. She received a PhD degree in Computer Science (specialisation: AI & Robotics) from Technische Universitat Braunschweig, Germany, in 2020. During her studies, she did her research internship at Sony Computer Science Laboratories, Inc. Tokyo, Japan for five months and joined Google Get Ahead summer program in 2019. R. Rayyes has received several awards and grants during her academic career including: Robotics Talent award for her Ph.D dissertation, the Superior Graduate award for her Mechatronics Bachelor degree, German Academic Exchange Service (DAAD) Scholarship for PhD study, and two AnitaB.org Scholarships for Grace Hopper Celebration. Her research interests include developing new AI systems for real robot applications with focus on efficient online learning, self-exploration, deep learning, human-robot learning and sensorimotor learning.

Richard J. Duro received a M.S. degree in Physics from the University of Santiago de Compostela, Spain, in 1989, and a PhD in Physics from the same University in 1992. He is currently a Full Professor in the Department of Computer Science and head of the Integrated Group for Engineering Research at the University of A Coruña within the CITIC-Center for research in ICT. His research interests include cognitive robotics, open-ended learning, and engineering applications of AI.

Jochen Triesch received his Diploma and Ph.D. degrees in Physics from the University of Bochum, Germany, in 1994 and 1999, respectively. After two years as a post-doctoral fellow at the Center for Visual Science and the Computer Science Department of the University of Rochester, NY, USA, he joined the faculty of the Cognitive Science Department at UC San Diego, USA as an Assistant Professor in 2001. In 2005 he became a Fellow of the newly founded Frankfurt Institute for Advanced Studies (FIAS), in Frankfurt am Main, Germany. In 2006 he received a Marie Curie Excellence Center Award of the European Union. In 2007 he was awarded the Johanna Quandt Chair for Theoretical Life Sciences at FIAS. He also holds professorships at the Department of Physics and the Department of Computer Science and Mathematics at the Goethe University in Frankfurt am Main, Germany. From 2019 to 2021 he held a visiting professorship at the Universite ́ Clermont Auvergne, France. During the same period he also chaired the IEEE Technical Committee on Cognitive and Developmental Systems. His research interests span Computational Neuroscience, Developmental Robotics/AI, and Machine Learning.

Stephane Doncieux received a PhD from Université Pierre and Marie Curie in 2003 and his habilitation in 2010. He is now Professor in Computer Science at ISIR (Institute of Intelligent Systems and Robotics), Sorbonne University, CNRS, in Paris, France. He is deputy director of the ISIR, a multidisciplinary robotics laboratory with researchers in mechatronics, signal processing computer science and neuroscience. Until that date, he was in charge of the AMAC multidisciplinary research team (Architectures and Models of Adaptation and Cognition). He was coordinator of the DREAM FET H2020 project from 2015 to 2018 (http://robotsthatdream.eu/). His research is in cognitive robotics, with a focus on learning and adaptation with a developmental approach.