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Yiannis Aloimonos
University of Maryland, College Park

Yiannis Aloimonos is Professor of Computational Vision and Intelligence at the Department of Computer Science, University of Maryland, College Park, and the Director of the Computer Vision Laboratory at the Institute for Advanced Computer Studies (UMIACS). He is also affiliated with the Institute for Systems Research and the Neural and Cognitive Science Program. He was born in Sparta, Greece and studied Mathematics in Athens and Computer Science at the University of Rochester, NY (PhD 1990). He is interested in Active Perception and the modeling of vision as an active, dynamic process for real time robotic systems. For the past five years he has been working on bridging signals and symbols, specifically on the relationship of vision to reasoning, action and language.

Yiannis Aloimonos | 4-09-25 from 14:00

TITLE: Minimal Active Perception for embodied AI design in nano UAV autonomy

ABSTRACT

State-of-the-art in aerial robot autonomy utilizes sensors that directly perceive the world in 3D and require a massive amount of computation. This is in stark contrast to the methods used by small living beings such as birds and bees: they use exploratory and active movements to gather more information to simplify the perception task. Using this active vision-based philosophy, we achieve state-of-the-art autonomy on nano-quadrotors using minimal on-board sensing and computation. Specifically, I will describe several methods of achieving activeness on an aerial robot: 1. By moving the agent itself, 2. By employing an active sensor, 3. By moving a part of the agent’s body, 4. By hallucinating active movements. Next, to make this work practically applicable I show how hardware and software co-design can be performed to optimize the form of active perception to be used. Finally, I present the world’s first prototype of a RoboBeeHive that shows how to integrate multiple competencies centered around active vision in all its glory. Joint work with my prior PhD students Nitin Sanket and Chahat Singh.

Gordon Cheng
Technical University of Munich

Gordon Cheng has made pioneering contributions in Humanoid Robotics, Neuroengineering, and Artificial Intelligence for over 20 years. Since 2010, he has held the Chair Professor for Cognitive Systems and the Director of the Institute for Cognitive Systems at the Technical University of Munich, Germany. Prof. Cheng is the Program Director of the Elite Master of Science in Neuroengineering of the Elite Network of Bavaria, a highly selective and unique study program in Germany. He is also the coordinator of the Center of Competence Neuro-Engineering. Gordon Cheng is the co-inventor of 20 patents and has co-authored over 450 technical publications, proceedings, editorials, books, and book chapters. The IEEE acknowledged this interdisciplinarity when he was named IEEE Fellow in 2017 for his “contributions in humanoid robotic systems and neurorobotics.” His research interests include NeuroRobotics, Humanoid Robotics, Imitation Learning, Cognitive Systems, Artificial Intelligence and NeuroEngineering.

Keynote Gordon Cheng | 03-09-25 from 14:00

TITLE: Cognitive Physical Intelligence

ABSTRACT
In this talk, I will explore various aspects of robot intelligence. We will examine physical intelligence through touch, showcasing whole-body interactions with robots, including how these interactions can enhance mobility. Additionally, we will discuss purposive learning and how robots can learn from humans. My presentation will include several real-world examples to illustrate these concepts.

Silvia Rossi
University of Naples Federico II

Silvia Rossi is a full professor of Computer Science at the Department of Electrical Engineering and Information Technologies, University of Naples Federico II. She serves as the scientific director of the PRISCA Lab (Projects of Intelligent Robotics and Advanced Cognitive Systems – https://www.prisca.unina.it). Prof. Rossi holds an M.Sc. in Physics from the University of Naples Federico II (2001) and a Ph.D. in Information and Communication Technologies from the University of Trento (2006). She has played a key role in numerous EU and international research projects and is currently the principal investigator and coordinator of several major initiatives, including the MSCA-ITN-2020 PERSEO (European Training Network on Personalized Robotics as Service Oriented applications), HORIZON-MSCA-2023-DN SWEET (Social aWareness for sErvicE roboTs), and HORIZON-TMA-MSCA-DN TRAIL (TRAnsparent, InterpretabLe Robots). She also coordinates the national PRIN project ADVISOR (ADaptiVe legIble robotS for trustwORthy health coaching). Prof. Rossi chaired the RO-MAN conferences in 2020 and 2022 and is an active member of program committees for leading conferences in human-robot interaction and artificial intelligence. Her research focuses on Socially Assistive Robotics, Human-Robot Interaction, Cognitive Architectures, and User Profiling and Recommender Systems. Her work explores computational methods for designing autonomous agents that can adapt their behavior to effectively interact with and support users. Prof. Rossi has authored over 190 publications in international journals, books, and conference proceedings, advancing the fields of robotics and AI.

Silvia Rossi | 5-09-25 from 9:00

TITLE: Understanding and Being Understood: A Human-Centered Approach to Mobile Robotics

ABSTRACT
Mobile robots operating in human-populated environments must go beyond treating people as dynamic obstacles. Even in non-interactive tasks, effective and socially acceptable deployment requires perceiving and responding to human states, intentions, and emotions, and integrating these cues into the robot’s decision-making processes. At the same time, their own actions must be designed to “speak” clearly: movements that are legible, predictable, and easy for people to interpret. This talk will explore these two complementary dimensions—human-aware perception and human-understandable action—highlighting their role in fostering safe, efficient, and widely accepted mobile robotic systems.