Professor Jari Hietanen, affiliated with Welfare Sciences, is a leading researcher in social neuroscience and psychophysiology. His work focuses on eye contact, affective responses, and human-robot interaction, with significant contributions to understanding autism spectrum disorder and developmental psychology. Research Interests: Social Neuroscience Psychophysiology Human-Robot Interaction Developmental Psychology Autism Spectrum Disorder Attentional Processing Publication Trends: Recent articles examine eye contact dynamics, emotional self-regulation, and neurodevelopmental differences. Studies integrate physiological measures (EMG, skin conductance, heart rate) with behavioral and cognitive analyses. Scientific Activities: Reviewer for journals like Social Cognitive and Affective Neuroscience , International Journal of Human-Computer Studies , and Cognition and Emotion Examiner for docentship and funding applications Contributor to datasets on eye contact and psychophysiological responses
Roberto Vezzani is an Associate Professor at the University of Modena and Reggio Emilia's Enzo Ferrari Department of Engineering, specializing in information processing systems (ING-INF/05). Previously Director of the Artificial Intelligence Research and Innovation Center (2018-2021), he holds a PhD in Information Engineering from the same institution. As senior member of AimageLab, he coordinates research on human-computer interaction using multi-sensor systems. His research spans: Computer vision for IoT and video surveillance Motion detection and action classification 3D vision with depth/thermal/event cameras Sensor fusion and automatic video annotation He leads competitive projects funded by Toyota, Ferrari, and EU programs, focusing on industrial applications of computer vision. Recent publications (2024-2025) demonstrate strong focus on 3D pose estimation, robot perception, and efficient embedded vision systems, with applications in automotive, robotics, and UAVs. Awards include: Best Paper - ICPR 2020 (IAPR) Best Paper - VISAPP 2020 Best Paper - THEMIS'2008 Industrial collaborations feature multi-year projects with Ferrari (RedVision lab), Toyota Europe, and Tetra Pak. Teaching includes courses on Computer Architecture, IoT systems, and industrial AI.
Lisbeth Fagerström is a Professor at the University of Southeast Norway, affiliated with the Faculty of Health and Social Sciences and the Department of Nursing and Health Sciences. With over 213 publications spanning more than 15 years, she has established herself as a leading researcher in nursing science with particular expertise in geriatric care, preventive home visits, and clinical competence assessment methodologies. Professor Fagerström's research program demonstrates remarkable thematic continuity and development. Her foundational work on preventive home visits (2009) examined whether these services truly adopt an individual health resource perspective, revealing that while most studies implemented PHVs based on individual perspectives, many lacked proper health resource orientation. This early work evolved into detailed investigations of elderly perspectives on home care services, identifying key benefit categories including safety, everyday management, quality of life, and personal identity maintenance. Analysis of her publication trajectory (2009-2024) reveals a strategic expansion from national to Nordic-wide research initiatives, particularly evident in her recent work on the Professional Nurse Self-Assessment Scale II, which has been translated and culturally adapted across Nordic countries. Her research consistently bridges theoretical frameworks with practical healthcare applications, addressing critical issues like pandemic response in elderly care facilities while maintaining focus on person-centered approaches. Professor Fagerström has secured funding for multiple significant projects including: 'An investigation how the elderly person's physical and mental wellbeing can be supported by a humanoid robot' (completed) 'Providing person-centred healthcare - by new models of advanced nursing practice' (completed) 'Nordic Nurse Competency Study' (active) 'How do preventive home visits affect older people's health and possibility for a good life in their own home?' (completed) Her collaborative approach is evident through extensive partnerships across Nordic institutions, with recent publications featuring co-authors from multiple universities. Professor Fagerström has supervised numerous students in nursing research, particularly in clinical competence development and geriatric care interventions, contributing significantly to the next generation of nursing scholars and practitioners.
Francesco Rea is a Senior Technician at Istituto Italiano di Tecnologia (IIT) and holds adjunct/teaching positions at University of Lethbridge and University of Genova. He leads the Cognitive Architecture for Interactive Technology (CONTACT) lab, focusing on humanoid perception, cognitive skills, and industrial applications. Education: B.Sc. Information Engineering, Università di Bergamo (2004) Specialization in Computer Engineering, Università di Bergamo (2007) M.Sc. Robotics and Automation, University of Salford (2008) Ph.D. Robotics, University of Genoa (2012) Research: His work bridges cognitive neuroscience and robotics, developing systems for auditory awareness, adaptive tutoring, and human-robot collaboration in manufacturing/healthcare. Key projects include VOJEXT, APRIL, and PROMEN-AID, funded by EU H2020 and Human Brain Project. Publications: Recent works (2025) explore LLM-based tutoring architectures, visuo-motor learning, and social robotics, demonstrating consistent focus on AI-driven human interaction and cognitive modeling. Awards: Canada-Italy Innovation Award (2017, 2021) Best Paper Award at ROMAN2020 Mitacs Globalink Research Award (2018) AI for Robotics Award (2020) Grants & Teams: Secured €multi-million funding for 5+ EU projects. Leads a 10+ member team at CONTACT lab developing cognitive architectures for industrial robots and healthcare applications.
Beomjoon Kim is an Associate Professor at the Graduate School of AI at Korea Advanced Institute of Science and Technology (KAIST). He directs the Humanoid Generalization (HuGe) lab, which focuses on creating general-purpose humanoids capable of efficient decision-making in complex environments. Education: Ph.D. in Computer Science from MIT CSAIL M.Sc. in Computer Science from McGill University B.Math in Computer Science and Statistics from University of Waterloo Professor Kim's research spans multiple areas of robotics and artificial intelligence, with a particular focus on humanoid robotics, task and motion planning, and robot learning. His work aims to bridge the gap between high-level task planning and low-level motion control, enabling robots to operate effectively in complex, real-world environments. He has made significant contributions to the field of geometric task and motion planning, developing novel algorithms that improve the efficiency and effectiveness of robot decision-making processes. Analysis of Professor Kim's recent publications reveals a strong focus on humanoid robotics, with particular emphasis on motion planning, object manipulation, and learning-based approaches. His work increasingly integrates deep learning techniques with traditional robotics algorithms, demonstrating a trend toward more data-driven approaches in robotics research. Many of his papers address the challenge of generalization in robotics, seeking to develop systems that can handle novel objects and environments without extensive retraining. Scientific Awards: Best Cognitive Robotics Paper award at ICRA 2017 Oral presentation (top 6% of accepted papers) at AAAI 2020 Oral presentation (top 6% of accepted papers) at AAAI 2019 Oral presentation (top 6% of accepted papers) at AAAI 2018 Spotlight presentation (top 3.5% of accepted papers) at NeurIPS 2018 Spotlight presentation (top 4% of accepted papers) at NeurIPS 2013 Plenary talk (top 12% of accepted papers) at CoRL 2020 Professor Kim actively mentors students at various levels, currently advising multiple Ph.D. and Master's students in the HuGe lab. His research is supported by grants that enable his team to pursue ambitious projects in humanoid robotics and AI. Through collaborations with institutions like MIT and industry partners, his work has significant impact on both academic research and practical applications of robotics technology. The HuGe lab, under Professor Kim's direction, has established itself as a leading research group in humanoid robotics. The lab maintains strong connections with other research institutions and regularly publishes in top-tier robotics and AI conferences. Current research directions include developing more efficient motion planning algorithms, improving robot manipulation capabilities, and exploring the integration of large language models with robotic systems.
