Thursday, February 5^th, 2026, 4pm CET

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Speaker: Ginevra Castellano

Full Professor in Intelligent Interactive Systems, Department of Information Technology, Uppsala University, Sweden

Title: From Human-Like to Human-Centric Robots: What Type of Alignment to Humans Do We Need?

Abstract:

Today we are witnessing an increased robotisation in all areas of society, from manufacturing to assistive technology, from healthcare to education. These application areas require robots to be able to interact with humans in an efficient and socially acceptable manner. At the same time, like all technologies, robots may not only bring benefits, but also change how we think and behave. This calls for human-robot interaction researchers to design and develop more human-centric and trustworthy artificial intelligence and robotics, which put humans at the center and preserve human agency and autonomy. In this talk I will present examples of creating trustworthy human-robot interaction in education, healthcare and transportation systems from my research at the Uppsala Social Robotics Lab, investigating dimensions of human agency, autonomy, trust, transparency, and fairness, in the quest for more human-centric robots for the societal good.

Bio:

Ginevra Castellano is a Full Professor in Intelligent Interactive Systems at the Department of Information Technology of Uppsala University, Sweden, where she is the Founder and Director of the Uppsala Social Robotics Lab. Her research is in the area of social robotics and human-robot interaction, addressing questions on how we can build human-robot interactions that are ethical and trustworthy, including robot ethics, robot autonomy and human oversight, gender fairness, robot transparency and trust, human-robot relationship formation, both from the perspective of developing computational skills for robotic systems, and their evaluation with human users to study acceptance and social consequences. She has been the Principal Investigator of several national and EU-funded projects on ethical and trustworthy human-robot interaction, in application areas spanning education, healthcare, and transportation systems. She is currently the coordinator of the CHANSE-NORFACE MICRO (Measuring children’s wellbeing and mental health with social robots) project (2025-2028), and the WASP-HS Research Group on Child Development in the Age of AI and Social Robots (2025-2030, funded by WASP-HS Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society. Castellano was an invited speaker at the UN AI for Good Global Summit 2024 and a keynote speaker the World Summit AI 2024. She was recently awarded the Thuréus prize 2025 from the Royal Society of Sciences in Uppsala.

Friday, December 5^th, 2025, 5pm CET

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Speaker: Jonathan Gratch

Research Full Professor of Computer Science and Psychology at the University of Southern California (USC), USA

Title: A social-functional view on the recognition and analysis of emotional expressions

Abstract:

Despite consensus among emotion researchers that the social meaning of emotional expressions is contextual, other-directed, co-constructed and culturally dependent, computational methods largely rest on the assumption that expressions denote some internal state (e.g., emotion or pain) which can be recovered by an expression’s morphology or timing alone. For example, many papers at the FG conference adopt a classic detection perspective, in which observers annotate the presumed internal states revealed by an expression, then algorithms are trained to predict this mapping without access to the original context in which the expression was produced. This assumption is also implicit in government regulations, such as the EU’s AI Act which bans emotion recognition across many practical. Though social psychology theirs point to a broader perspective on expressions, they fail to offer detailed of what constitutes “context” or “co-construction” to a level that can be exploited by computational methods. In this talk, I will highlight the use of automatic expression analysis in social domains, highlighting the interpersonal processes that shape their production and analysis. I hope this talk can encourage future work that formalizes the computational implications of this social perspective, including clarifying the communicative function of expressions, how are they shaped and co-constructed via context and culture, and how socially interactive agents might adapt and engage in meaning creation?

Bio:

Jonathan Gratch is a Research Full Professor of Computer Science and Psychology at the University of Southern California (USC) and Director for Virtual Human Research at USC’s Institute for Creative Technologies. He completed his Ph.D. in Computer Science at the University of Illinois in Urbana-Champaign in 1995. Dr. Gratch’s research focuses on computational models of human cognitive and social processes, especially emotion, and explores these models’ potential to advance psychological theory and shape human-machine interaction. He is the founding Editor-in-Chief (retired) of IEEE’s Transactions on Affective Computing, Associate Editor for Affective Science, Emotion Review, and former President of the Association for the Advancement of Affective Computing (AAAC). He is a Fellow of AAAI, AAAC, and the Cognitive Science Society.

Thursday, November 6^th, 2025, 4pm CET

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Speaker: Jeffrey L. Krichmar

Full Professor, Department of Cognitive Sciences and the Department of Computer Science, University of California, Irvine, USA

Title: Neurorobotics and Neuromodulation: Affect, Learning, and Behavior in the Brain-Body-Environment Loop

Abstract:

Neurorobots are robots whose control systems follow structural and dynamical aspects of the nervous system.  Their artificial brains can be thoroughly probed and recorded as the robot interacts with the world. Neurorobotic design principles fall into three categories that follow natural organisms: First, they must react decisively to sensory events. Second, they must have the ability to adapt, learn and remember over their lifetime. Third, they must weigh the different and sometimes conflicting options that are crucial for completing tasks. Following these principles can not only increase our understanding of how brain responses lead to flexible behavior, but they may also lead to more intelligent systems. In this talk, I will describe the field of neurorobotics and then present neurorobot interaction case studies that focus on how neuromodulation and neurohormones can influence affect, learning, and behavior.

Bio:

Jeffrey L. Krichmar received a B.S. in Computer Science in 1983 from the University of Massachusetts at Amherst, a M.S. in Computer Science from The George Washington University in 1991, and a Ph.D. in Computational Sciences and Informatics from George Mason University in 1997. He spent 15 years as a software engineer on projects ranging from the PATRIOT Missile System at the Raytheon Corporation to Air Traffic Control for the Federal Systems Division of IBM. From 1999 to 2007, he was a Senior Fellow in Theoretical Neurobiology at The Neurosciences Institute. Since 2008, he has been a Professor in the Department of Cognitive Sciences and the Department of Computer Science at the University of California, Irvine. Krichmar has over 20 years of experience designing adaptive algorithms, creating neurobiologically plausible neural networks, and constructing brain-based robots whose behavior is guided by neurobiologically inspired models. He has over 150 publications and holds 9 patents. His work has been funded by the Defense Advanced Research Projects Agency (DARPA), Intelligence Advanced Research Projects Activity