Speakers

LECTURERS

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    Angelo Cangelosi

    Department of Computer Science, University of Manchester (UK)

    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 was awarded a European ...

    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 was awarded a European Research Council (ERC Advanced) project in 2023. Cangelosi also is Turing Fellow at the Alan Turing Institute London, and Visiting Professor at Universita' Cattolica Milano and Hohai University. 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, with currently many UKRI/Horizon/US grants active (e.g. ERC Advanced, UKRI TAS Trust Node and CRADLE Prosperity, Horizon RIA PRIMI, MUSAE and TRAINCREASE, the Horizon MSCA TRAIL, PERSEO, eLADDA, and the US AFRL THRIVE++). Cangelosi has produced more than 300 scientific publications. He also has projects funding collaboration with industries such as Honda, BAE Systems and Jacobs. Cangelosi 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.

    Talk Title: Cognitive Robotics: From Babies to Robots and AI

    Abstract: This talk introduces the concept of Cognitive Robotics, i.e. the field that combines insights and methods from AI, as well as cognitive and biological sciences, to robotics (cf. Cangelosi & Asada 2022 for book open access). This is a highly interdisciplinary approach that sees AI computer scientists and roboticists collaborating closely with psychologists and neuroscientists. We will use the case study of language learning to demonstrate this highly interdisciplinary field, presenting developmental psychology studies on children's language acquisition and robots' experiment on language learning. Growing theoretical and experimental psychology research on action and language processing and on number learning and gestures in children and adults 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. In robotics and AI, these studies have important implications for the design of linguistic capabilities, in particular language understanding, in robots and machines for human-robot collaboration. This focus on language acquisition and development uses Developmental Robotics methods, as part of the wider Cognitive Robotics approach. During the talk we will present examples of developmental robotics models and experimental results with the baby robot iCub and with the Pepper robot. One study focuses on the embodiment biases in early word acquisition and grammar learning. The same developmental robotics method is used for experiments on pointing gestures and finger counting to allow robots to learning abstract concepts such as numbers. We will then present a novel developmental robotics model, and human-robot interaction experiments, on Theory of Mind and its relationship to trust. This considers both people's Theory of Mind of robots' capabilities, and robot's own 'Artificial Theory of Mind' of people's intention. Results show that trust and collaboration is enhanced when we can understand the intention of the other agents and when robots can explain to people their decision making strategies. The implications for the use of such cognitive robotics approaches for embodied cognition in AI and cognitive sciences, and for robot companion applications will also be discussed. The talk will also consider philosophy of science issues on embodiment and on machine's understanding of language, the ethical issues of trustworthy AI and robots, and the limits of current big-data large language models.

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    Karinne Ramirez-Amaro

    Department of Electrical Engineering, Chalmers University of Technology, Sweden

    Dr. Karinne Ramirez-Amaro is an Associate Professor at the Department of Electrical Engineering at the Chalmers University of Technology since 2022. In 2019, she became an Assistant Professor at Chalm...

    Dr. Karinne Ramirez-Amaro is an Associate Professor at the Department of Electrical Engineering at the Chalmers University of Technology since 2022. In 2019, she became an Assistant Professor at Chalmers in the research group of Mechatronics. Previously, she was a post-doctoral researcher at the Chair for Cognitive Systems at the Technical University of Munich (TUM). She completed her PhD (summa cum laude) at the Department of Electrical and Computer Engineering at the TUM, Germany in 2015. She received the Laura Bassi award granted by TUM and the Bavarian government in 2015, also in that year she received the prize of excellent Doctoral degree for female engineering students, granted by the state of Bavaria, Germany. In 2011, she received the Google Anita Borg scholarship. In 2009, she was granted a scholarship for a PhD research by DAAD – CONACYT grant. In 2022, Karinne was elected as a member of the Administrative Committee (AdCom) from the IEEE Robotics and Automation Society (RAS) and she is the chair of the IEEE RAS Women in Engineering (WiE). Her research interests include Semantic Representations, Interpretable methods, and Human Activity Recognition and Understanding.

    Talk Title: Stretching the Limits of Knowledge Representations in Robotics

    Abstract: Knowledge representations are often used to store experiences of learned tasks. To what extent can autonomous robots learn, store and re-use their experiences? In this talk, I will introduce our latest work on defining flexible and adaptable Knowledge representations in robotics. I will explain a novel learning method that generates compact and general semantic models to infer human activities. Our proposed representations allow robots to adapt to different sources of information, for example, videos, robot sensors, virtual reality, etc. This learning method allows robots to obtain and determine a higher-level understanding of a demonstrator’s behavior via semantic representations. First, the low-level information is extracted from the sensory data, and then a meaningful semantic description, the high-level, is obtained by reasoning about the intended human behaviors. The introduced method has been assessed on different robots, e.g. the iCub, REEM-C, PR2, and TOMM, with different kinematic chains and dynamics. Furthermore, the robots use different perceptual modalities, under different constraints and in several scenarios ranging from making a sandwich to driving a car assessed on different domains (home-service and industrial scenarios). One important aspect of our approach is its scalability and adaptability toward new activities, which can be learned on-demand. Overall, the presented compact and flexible solutions are suitable for tackling complex and challenging problems for autonomous robots.

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    Alice Smith

    Department of Industrial and Systems Engineering, Auburn University, USA

    ALICE E. SMITH is the Joe W. Forehand, Jr. Distinguished Professor of the Industrial and Systems Engineering Department at Auburn University, where she served as Department Chair from 1999-2011. She ...

    ALICE E. SMITH is the Joe W. Forehand, Jr. Distinguished Professor of the Industrial and Systems Engineering Department at Auburn University, where she served as Department Chair from 1999-2011. She also has a joint appointment with the Department of Computer Science and Software Engineering. Previously, she was on the faculty of the Department of Industrial Engineering at the University of Pittsburgh from 1991-99, which she joined after industrial experience with Southwestern Bell Corporation. Dr. Smith has degrees from Rice University (BSCE), Saint Louis University (MBA), and Missouri University of Science and Technology (PhD) along with a recent BA in Spanish from Auburn University. Dr. Smith's research focus is analysis, modeling, and optimization of complex systems with emphasis on computation inspired by natural systems integrated with traditional operations research and statistical approaches. She holds one U.S. patent and several international patents and has authored publications which have garnered over 17,500 citations, an H Index of 50, and an i10 Index of 126 (Google Scholar). Dr. Smith is on the top half of the List of Top 2% of Scientific Researchers worldwide recently compiled by Stanford University based on publishing impact. Her books include Women in Computational Intelligence: Key Advances and Perspectives on Emerging Topics and Women in Industrial and Systems Engineering: Key Advances and Perspectives on Emerging Topics, both published by Springer. Several of her papers are among the most highly cited in their respective journals including the most cited paper of Reliability Engineering & System Safety and the 4th most cited paper of IEEE Transactions on Reliability. Dr. Smith has been a principal investigator on over $10 million of sponsored research with funding by Department of Homeland Security, NASA, U.S. Department of Defense, Missile Defense Agency, National Security Agency, NIST, U.S. Department of Transportation, Frontier Technologies Inc., Lockheed Martin, Adtranz (now Bombardier Transportation), the Ben Franklin Technology Center of Western Pennsylvania, and U.S. National Science Foundation, from which she has been awarded 18 distinct grants including a CAREER grant and an ADVANCE Leadership grant. She is a four-time Fulbright Scholar (2013, 2016, 2017, 2020) with residencies in Turkey, Chile, and Colombia. For accomplishments in research, education, and service she was named the Joe W. Forehand, Jr. Distinguished Professor in 2023 and previously she was the Joe W. Forehand / Accenture Distinguished Professor, the H. Allen and Martha Reed Professor, and the Philpott‐ WestPoint Stevens Professor, all at Auburn University. Dr. Smith is a Life Fellow of the Institute of Electrical and Electronics Engineers (IEEE), a Fellow of the Institute for Operations Research and Management Science (INFORMS) and of the Institute of Industrial and Systems Engineers (IISE), and a senior member of the Society of Women Engineers, a member of Tau Beta Pi, and a Registered Professional Engineer. She is a current IEEE Distinguished Lecturer and has given numerous keynote/plenary talks at international conferences. Dr. Smith is a current IEEE CIS Ad Com member and her leadership roles in conferences sponsored by IEEE are numerous.

    Talk Title: Drones For Last Mile Logistics with A Medical Humanitarian Application

    Abstract: This seminar discusses novel approaches for employing drones to accomplish logistical tasks in diverse environments. Drones, working in tandem with traditional transportation vehicles and with humans, offer environmentally friendly and cost-effective alternatives for moving small items such as medicines, electronic devices, and assembly parts. This talk will cover several research projects which involve a combination of mathematical modeling, computational optimization, simulation in virtual environments, and actual physical experimentation and trials. While using drones has challenges in terms of human interaction and practicality of operating in certain environments, they are more pragmatic than might be expected for some situations. One focus is on rural last mile healthcare supplies delivery where drones resupply trucks with newly available orders and prescriptions. Another focus is on assembly facilities where drones bring needed parts to works at their stations on the line. This latter setting is indoors where GPS cannot be used for drone positioning and guidance so alternative methods must be employed.

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    Javier Ruíz Del Solar San Martín

    Departamento de Ingeniería Eléctrica, Universidad de Chile, Chile

    Dr. Javier Ruiz del Solar is Professor of Electrical Engineering at the Universidad de Chile and Executive Director of the Advanced Mining Technology Center. He is interested on robots, autonomous sys...

    Dr. Javier Ruiz del Solar is Professor of Electrical Engineering at the Universidad de Chile and Executive Director of the Advanced Mining Technology Center. He is interested on robots, autonomous systems and learning. His research focuses on two areas, fundamental research in perception and learning, and applications of robotics technology in the real-world, mainly in mining. In the last years his has focused on the application of deep reinforcement learning to mobile robot applications.

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    Javier Preciozzi

    Universidad de la República & DigitalSense, Uruguay

    Javier Preciozzi is co-founder of Digital Sense Technologies, a company specialized on image processing and computer vision. In 2016 he obtained his PhD degree at Facultad de Ingeniería of Universidad...

    Javier Preciozzi is co-founder of Digital Sense Technologies, a company specialized on image processing and computer vision. In 2016 he obtained his PhD degree at Facultad de Ingeniería of Universidad de la República (Uruguay), with specialization on satellite image processing. In this context, he worked on projects for the CNES (Centre National d'Études Spatiales, France) and CESBIO (Centre d'Etudes Spatiales de la BIOsphere, France). His main research interests are satellite image processing and biometrics.

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    J. Matias Di Martino

    Universidad Católica del Uruguay, Uruguay and Duke University, USA

    Full Professor of Informatics and Computer Science at UCU (Uruguay) and an Adjunct Research Professor at Duke University (USA). He has extensive experience researching, educating, and providing profes...

    Full Professor of Informatics and Computer Science at UCU (Uruguay) and an Adjunct Research Professor at Duke University (USA). He has extensive experience researching, educating, and providing professional consulting. Matias loves working on AI projects that intersect industry and academia; in particular, his interests include image processing, machine learning, time series analysis, remote sensing, and computer vision. He has taught undergraduate and graduate courses at the university level, led large-scale research projects, and published over 50 peer-reviewed scientific papers in top journals and conferences.

    Talk Title: A gentle introduction to contrastive learning and its application to improve keypoint detection and matching in agricultural settings.

    Abstract: In this talk, we will review the basic principles of stereo vision and 3D scene reconstruction, where keypoint detection and matching play a crucial role. We will review classic methods for keypoint detection and machine and introduce contrastive learning ideas showing how they can be exploited to improve robots' autonomous navigation in agricultural settings.

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    Taihú Pire

    CIFASIS, Rosario, Argentina

    Taihú Pire received the licentiate degree in Computer Science (2010) at the National University of Rosario and the PhD in Computer Science (2017) at the University of Buenos Aires. Currently, he is a ...

    Taihú Pire received the licentiate degree in Computer Science (2010) at the National University of Rosario and the PhD in Computer Science (2017) at the University of Buenos Aires. Currently, he is a research scientist and Head of the Robotics Laboratory belonging to the Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas (CIFASIS, CONICET-UNR). In addition, he is an Adjunct Professor at the National University of Rosario. His research interests focus on the development of new SLAM algorithms and autonomous navigation systems for mobile robots.

    Talk Title: SLAM for Agricultural Robots

    Abstract: In order for a mobile robot to navigate an unknown environment, it must be able to build a map, estimate its location, and plan a safe path. Localization and mapping tasks are often addressed together, giving rise to the problem of SLAM (Simultaneous Localization and Mapping), which consists of the robot reconstructing the environment (map) at the same time as it estimates its location. This talk covers the Simultaneous Localization and Mapping (SLAM) theoretical concepts and application challenges in Agriculture Environments.

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    Miguel Torres Torriti

    Departamento de Ingeniería Eléctrica, Pontificia Universidad Católica de Chile, Chile

    Miguel Torres-Torriti is Associate Professor at Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, teaching control systems, sensors, actuators and robotics. He received t...

    Miguel Torres-Torriti is Associate Professor at Department of Electrical Engineering, Pontificia Universidad Catolica de Chile, teaching control systems, sensors, actuators and robotics. He received the B.Sc. and M.Sc. degrees in electrical engineering from the Pontificia Universidad Católica de Chile in 1996 and 1998, respectively, and the Ph.D. degree in systems and control from McGill University, Montreal, Canada, in 2003. Between 1998-2003 his research at McGill’s Center for Intelligent Machines focused on the stabilization of strongly nonlinear underactuated systems. During 2000-2001 he was also a research assistant for Lockheed Martin Canada in SAR imagery classification. From 2004 to 2005, he was Senior Applications Engineer with General Electric Chile in the implementation of the multivariable process controllers for the ENAP Bío Bío and Magallanes refineries. In 2005 he joined the Department of Electrical Engineering of the School of Engineering of PUC Chile, where he is currently Associate Professor. Dr. Torres-Torriti has been the Director of the undergraduate program in Robotics Engineering (2013-2022), Associate Dean of Social Responsibility (2014-2016), Associate Dean of Technology (2016-2022), and is currently the Vice-Dean of the Faculty of Engineering of the Pontificia Universidad Católica de Chile. His fields of experience comprise systems modeling and control, estimation, machine learning, robot dynamics, mechatronic design, sensors and perception. His current research projects include the development of sensing, motion planning and control strategies for mobile manipulators

    Talk Title: Advancing Robotics Systems Modeling, Simulation and Control: From Block Diagram Modeling with DiaBloS to RL-based Control of Dual Arm-Mobile Manipulators for Agriculture

    Abstract: Dual arm-mobile manipulators represent a versatile class of robotic systems, combining mobility with dexterous manipulation capabilities. This talk provides an overview of the entire development process, from the initial modeling of complex dynamics to real-world implementation. Mathematical models of dual-arm coordination, motion planning, and control strategies are used to overcome challenges such as handling payloads and ensuring synchronization between arms. On the other hand, the talk examines emerging tools like MuJoCo for physically accurate modeling and the development of visual diagrammatic programming open-source tool for Python called DiaBloS for the graphical modeling and simulation of dynamic systems based on block diagrams. The synergy between modeling, algorithms and simulation tools highlights the growing relevance of proper physically accurate simulation in advanced robotic systems and the deployment of AI-based algorithms for control of complex real-world systems.

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    Yinoussa Adagolodjo

    Defrost team, Institut National de Recherche en Informatique et Automatique (INRIA)

    As an Assistant Professor at the University of Lille and a full member of the DEFROST team since 2019, He has actively contributed to advancing research in robotics and augmented reality applications ...

    As an Assistant Professor at the University of Lille and a full member of the DEFROST team since 2019, He has actively contributed to advancing research in robotics and augmented reality applications in healthcare. Throughout his academic career, he has been deeply involved in pioneering projects that reflect a commitment to cutting-edge exploration and impactful innovation. Among these, the CONECT project—his doctoral thesis—stands out as a cornerstone of his work. In this project, he focused on integrating robotic technology within the operating room to enhance precision in needle insertion procedures. His contributions included developing methodologies that leverage finite element simulations to assist surgeons during complex operations and using augmented reality to provide intuitive, real-time guidance. In addition to CONECT, he has collaborated on several interdisciplinary projects to bridge the gap between technology and healthcare. He continually seeks ways to improve surgical outcomes and optimize medical workflows through advanced simulation and robotic solutions. Notably, the ROBOCOP project focuses on the fascinating field of cochlear implant robotization, exploring new avenues to improve hearing technologies. In parallel, his involvement in the COSSEROOTS project focused on applying Cosserat's theory to advance the control of slender deformation robots, contributing to advances in the field.

    Talk Title: From biomechanical simulation to deformable robot control

    Abstract: Advances in medical technology are increasingly bridging the gap between virtual simulation and robotic intervention, paving the way for more precise and minimally invasive surgeries. This presentation, titled 'From Biomechanical Simulation to Deformable Robot Control,' explores my journey from biomechanical modeling and medical simulations to the latest in soft robotic surgical tools.

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    Josie Hughes (Online)

    Institute of Mechanical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland

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    Robert Guamán-Rivera

    Instituto de Ciencias de la Ingeniería, Universidad de O'Higgins, Chile