Julie Reyer is an Associate Professor and Interim Chair of the Department of Mechanical Engineering at Bradley University’s Caterpillar College of Engineering and Technology. She also serves as Associate Dean and is affiliated with the Business and Engineering Convergence Center. Her academic work spans robotics, control systems, optimal design, and engineering education. B.S., General Engineering, University of Illinois M.E., Mechanical Engineering, Carnegie Mellon University Ph.D., Mechanical Engineering, University of Michigan Her research focuses on robotics, kinematic modeling, and interdisciplinary convergence in design and control systems. She has developed innovative capstone programs integrating industry feedback and authored over two decades of publications. She actively supports student organizations as a faculty advisor for BU FIRST, SHPE, and SWE (Central Illinois Section). Her teaching includes courses like ME 560: Principles of Robotic Programming and ME 591: Advanced Computational Techniques .
Achim J. Lilienthal is a Professor of Computer Science at the Technical University of Munich (TUM) , where he leads the Chair for Perception for Intelligent Systems . He is also a Guest Professor at the University of Örebro, Sweden , where he established the Mobile Robotics and Olfaction Lab and co-founded spinoff companies Retenua and QTPIE . Additional roles include coordination of the Horizon 2020 project DARKO , management of the KI.Fabrik project at the German Museum of Technology, and participation as a Principal Investigator in the Erasmus+ project MADITA and the KI-ALF project. Research Interests : His work focuses on perception systems for dynamic environments , integrating domain knowledge and AI. Key areas include mobile robot olfaction , rich 3D perception , navigation of autonomous transport robots , human-robot interaction , eye-tracking support systems , and mathematics education research . His publications span over 300 refereed conference and journal papers. Teaching & Academic Contributions : Lilienthal has taught at bachelor’s, master’s, and postgraduate levels across computer science, robotics, and physics. He completed 300+ hours of pedagogical training in Sweden, co-developed the international master’s program AI and Robotics at Örebro University, and delivered guest lectures at universities in Málaga, Tianjin, and Barcelona. Labs & Teams : He leads the Perception for Intelligent Systems chair at TUM and previously established the Mobile Robotics and Olfaction Lab at Örebro University. His team includes members like Valeria Salazar, Thomas Wiedemann, and others.
Jan Allbeck is an Associate Professor in the Department of Computer Science and Associate Dean of the Honors College at George Mason University's College of Engineering and Computing. She advises honors students in Applied Computer Science and Computer Science, while teaching courses on game design, computer graphics, and special effects. PhD, Computer and Information Science, University of Pennsylvania MSE, Computer and Information Science, University of Pennsylvania BS, Computer Science, Bloomsburg University of Pennsylvania BA, Mathematics, Bloomsburg University of Pennsylvania Allbeck's research focuses on the intersection of animation, artificial intelligence, and psychology, particularly in simulating virtual humans and intelligent crowds. She develops frameworks for behavioral realism, agent decision-making, and crowd dynamics, with applications in virtual reality and cybersecurity training. As director of the Games And Intelligent Animation (GAIA) Lab, she explores advanced simulation techniques including semantic virtual environments, parameterized memory models, and high-density autonomous crowd systems. Her work emphasizes creating agents that can interact plausibly with humans and environments.
Jorge Santos is Professor of Fishery Biology at The Norwegian College of Fishery Science, UiT The Arctic University of Norway, Tromsø. His work integrates fisheries ecology, socio-ecological systems, and innovative art-science approaches to address coastal and marine challenges. Research Focus: Fisheries ecology and bio-geography, trophic networks, effects of fishing, coasts and estuaries, small-scale fisheries, fisheries management, coastal culture, futures of coasts and fisheries, Blue Economy, education and outreach, and quantitative methods. Key Trends: Recent work emphasizes climate change impacts on marine communities, rotational harvesting effects, geographic life-history variations, and interdisciplinary art-science collaborations for ocean communication. His publications reveal a strong shift toward integrating ecological science with cultural narratives and future scenario planning. Scientific Recognition: No formal awards listed in provided materials. Advising: Supervises bachelor, master, and PhD students across biological and social dimensions of marine systems. Grants & Projects: Coordinates NorLanka Blue (marine sciences/blue economy in Sri Lanka), SAMAKI (MSc/PhD school in Tanzania/Zanzibar), and Blue Route (global PhD education). Serves on MASMA Programme Committee and leads consultancies for fisheries/education development. Active in CRAFT research group (Center for Arctic Humanities) and projects AFO-JIGG (small-scale fishing welfare) and FUTURES4Fish (coastal futures), Santos pioneers transdisciplinary approaches bridging science, art, and community engagement.
Edward Vogel is a Professor in the Psychology Department at the University of Chicago's Social Sciences Division, where he leads a prominent research program focused on visual working memory and attentional mechanisms. His work bridges cognitive psychology and neuroscience, utilizing electrophysiological methods to investigate fundamental questions about memory capacity and cognitive control. Institution: University of Chicago Department: Psychology Research Focus: Working memory mechanisms, attention, visual cognition Key Collaborator: Edward Awh Active Research Period: 1996-present Vogel's research primarily investigates the neural and cognitive mechanisms underlying visual working memory capacity, attentional control, and the relationship between working memory and long-term memory processes. His work has been instrumental in establishing the fixed-item limit theory of working memory and developing electrophysiological markers like the contralateral delay activity (CDA) to measure memory storage. His research demonstrates that individual differences in working memory capacity reflect differences in attentional control rather than simple storage limitations. Vogel's innovative approach combines behavioral experiments with EEG methodology to provide insights into the temporal dynamics of cognitive processes. Analysis of his 15 most recent publications (2021-2025) reveals a continued focus on working memory architecture, attentional mechanisms, and neural correlates of cognitive processes. His research shows evolution from establishing basic capacity limits toward understanding more complex interactions between working memory systems, long-term memory, and attentional control mechanisms. Recent work explores how attentional pointers operate in working memory, how information is spontaneously removed from working memory upon task completion, and how long-term memory can be recruited to overcome working memory limitations. Multiple NIH-funded research projects (including R01MH087214 running through 2025) Extensive publication record with over 100 articles Highly cited work, particularly on contralateral delay activity as a neural measure of working memory Vogel maintains an active research program with significant contributions to understanding the neural basis of cognitive processes. His work has established important methodological approaches for measuring working memory capacity and has shaped theoretical understanding of how attentional mechanisms constrain memory performance. Through his collaborations, particularly with Edward Awh, he has built a comprehensive research program that continues to advance our understanding of human cognitive architecture.
Professor Soo Hee Lee is a full Professor of Organisation Studies at Kent Business School, University of Kent, where he has taught and researched since July 2012. He previously held faculty positions at Birkbeck, University of London, Cass Business School and the University of Sheffield, and has been a visiting scholar at USTC, KAIST, Sungkyunkwan University, ESSEC and TiasNimbas. Education & affiliations: While explicit degrees are not listed, his long-standing faculty roles and editorial board memberships ( Technological Forecasting & Social Change , Global Transitions ) confirm senior academic standing. Research interests: Lee interrogates the institutional and behavioural foundations of strategy, innovation, knowledge, trust and power. Early work centred on emerging-economy MNCs; recent projects examine digital convergence and creativity across architecture, fashion, food, museums and dance. Publication trends: Across 60+ outputs the corpus blends organisation theory with creative-industry empirics, tracing how platforms, museums and art fairs legitimise new actors, how blockchain reconfigures inter-organisational trust, and how policy shapes innovation in small economies. Doctoral supervision: He has supervised twelve PhD researchers to completion or in progress, exploring ethical leadership in Vietnamese MNCs, hybrid logics in UK/French art museums, branding of visual artists, social capital of expatriates, and radical innovation in coordinated market economies. Teaching & service: Modules taught include Creativity & Innovation in Organisations, Leadership & Management, Research Methods for HRM, and Generating Theory & Presenting Research. He serves on the scientific committee of the International Conference on Social Theory, Politics & the Arts.
John Tsotsos is Distinguished Research Professor of Vision Science at York University, holding the NSERC Tier I Canada Research Chair in Computational Vision. He is affiliated with the Lassonde School of Engineering, Department of Electrical Engineering and Computer Science, and serves as Adjunct Professor in Ophthalmology and Vision Sciences at the Temerty Faculty of Medicine, University of Toronto. His research focuses span computer vision, visual attention, active vision systems, human vision, and visually guided robotics. Post-Doctoral Fellow – Ontario Heart Foundation, Toronto General Hospital (1979-81) Ph.D. in Computer Science, University of Toronto (1980) M.Sc. in Computer Science, University of Toronto (1976) B.A.Sc. (Honours) in Engineering Science (Computer Science Option), University of Toronto (1974) His research integrates computer vision with robotics and human perception, emphasizing active vision and computational models of attention. Notable contributions include the Selective Tuning theory of visual attention, formal theorems on visual complexity, and implementations in autonomous robotic systems. Recent publications highlight advancements in task-driven gaze prediction, saliency mapping, domain adaptation, stereo vision tracking, and gait analysis. These works bridge computer science, neuroscience, and biomedical engineering. Fellow, Canadian Academy of Engineering (2024) Fellow, Asia-Pacific Artificial Intelligence Association (2022) CS-Can|Info-Can Lifetime Achievement in Computer Science (2020) IEEE Life Fellow (2024) Sir John William Dawson Medal, Royal Society of Canada (2015) Geoffrey J. Burton Memorial Lecture (2011) NSERC Tier I Canada Research Chair in Computational Vision (2003-2024) Royal Society of Canada Fellow (2010) With 200+ trainees and a long-standing directorship at York University’s Centre for Vision Research, Tsotsos has mentored numerous researchers who have become influential in academia and industry. His leadership extends to the Centre for Innovation in Computing @ Lassonde and collaborations with institutions including MIT, University of Toronto, and University of Pittsburgh. He pioneered the Laboratory for Active and Attentive Vision, contributing to fields like medical image analysis, autonomous robotics, and cognitive architectures. His work includes patents in touch-sensitive displays and face recognition systems.
Arvin Agah is a Professor in the Department of Electrical Engineering and Computer Science at the University of Kansas. His research spans biomedical robots, applied artificial intelligence, and interdisciplinary applications in behavior navigation systems, human-robot interaction, and computational creativity. Research interests include: Biomedical Robotics for rehabilitation and diagnostics Augmented/Virtual/Mixed Reality in remote assistance Deep Learning for image processing and healthcare Multi-agent communication strategies Evolutionary approaches to digital art and navigation His publications from 2016-2023 reveal a trajectory from foundational work in skin/face detection to advanced VR/AR systems and sociorobotics. Key trends: AI-driven healthcare solutions, immersive interface design, and agent-based collaboration models. Professional activities include: Teaching Agile software development Leadership in robotics competitions for education Development of polar exploration robotics Contact: agah@eecs.ku.edu
Ioannis Havoutis is an Associate Professor in Engineering Science at the Oxford Robotics Institute , University of Oxford. His research integrates dynamic whole-body motion planning , control systems , and machine learning for robotics with arms and legs . He holds a PhD (2011) and MSc with distinction (2007) from the University of Edinburgh, focusing on machine learning for motion planning of articulated robots. University of Edinburgh: PhD in Robotics (2011), MSc in Machine Learning (2007) His work spans dynamic legged locomotion , learning from demonstration , and terrain-adaptive control , with applications in quadruped robots and teleoperation . Key contributions include symplectic meta-learning , skill switching criteria , and flow-based trajectory optimization . Recent publications focus on 2025 advancements in adaptive manipulation , generalist parkour policies , and diffusion models for locomotion. He has received awards such as the Frontiers in Robotics & AI Best Paper Award (2019) and CLAWAR 2015 Best Technical Paper Award . Teaching roles include B16 Operating Systems courses at Oxford and Advanced Robotics lectures at IIT. Contact: havoutis@robots.ox.ac.uk | ioannis@robots.ox.ac.uk | Address: Oxford Robotics Institute, 17 Parks Road, Oxford, OX1 3PJ, UK
Dr Dominic Edsall serves as an Honorary Senior Research Fellow in the Department of Curriculum, Pedagogy and Assessment at the UCL Institute of Education. His current research investigates the impact of artificial intelligence on higher education and English as a Foreign Language (EFL) instruction, conducted in collaboration with Professor Sandra Leaton Gray. Appointed from September 2024 to September 2026, he maintains active scholarly output despite the non-salaried nature of his honorary position. His research centers on Learner Autonomy, TESOL, and Higher Education pedagogy, with specialized focus on Japanese university contexts. Key themes include the negotiation of learner autonomy by EFL teachers, transitions from dependent test-taking to autonomous learning, and critical challenges posed by AI in academic integrity. His work bridges theoretical frameworks like game theory and legitimation code theory with practical classroom applications, emphasizing sociocultural dimensions of education. Analysis of his 2023-2025 publications reveals a strategic pivot toward AI ethics in education, while maintaining core expertise in learner autonomy. The 2025 article on AI-based digital cheating exemplifies his timely intervention in emerging academic integrity crises, proposing ethical pedagogical responses rather than technical fixes. Earlier works establish foundational contributions to autonomy theory through Japanese EFL case studies and complexity-aware research methodologies. Dr Edsall explicitly states he cannot accept or supervise doctoral students in his current role. He is available for collaborative projects, conference speaking, consultancy, and journal reviewing. His professional background includes secondary science teaching in the UK and extensive EFL instruction in Japanese higher education, providing unique cross-disciplinary and cross-cultural perspectives.
Dr. Isabelle Gagnon is a Senior Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC) and a Professor at the School of Physical and Occupational Therapy, Faculty of Medicine and Health Sciences, McGill University. She is affiliated with the Department of Pediatrics, Division of Emergency Medicine at McGill University Health Centre (MUHC), contributing to the Child Health and Human Development Program. Senior Scientist, RI-MUHC Professor, School of Physical and Occupational Therapy, McGill University Department of Pediatrics, MUHC Her research focuses on pediatric traumatic brain injury (TBI) and concussion , with emphasis on functional outcomes, rehabilitation interventions, and healthcare system impacts. Key domains include: Balanced assessment of motor and psychosocial domains Integration of imaging and virtual reality technologies Development of innovative rehabilitation approaches for slow recoverers Analysis of emergency department service organization on patient outcomes Recent publications (2024-2025) address quality indicators for trauma care , vestibulo-ocular reflex dynamics , direct-access physiotherapy models , and social determinants of health disparities . Her work spans clinical practice guidelines , EEG-based concussion biomarkers , and virtual pedestrian collision avoidance paradigms . Dr. Gagnon collaborates with interdisciplinary teams to advance pediatric concussion management , focusing on return-to-activity protocols and neurological data integration . She emphasizes patient-centered outcomes and healthcare accessibility .
Lars Hammarstrand is an Associate Professor at Chalmers University of Technology specializing in the Signal Processing research group. His work integrates model-based Bayesian statistics with deep machine learning for applications in visual localization, sensor fusion, and autonomous systems, with emphasis on robustness in real-world environments. His research focuses on bridging Bayesian inference and deep learning to solve challenges in autonomous vehicle perception. Key areas include visual localization under appearance changes, radar-camera sensor fusion, and out-of-distribution detection for safety-critical systems. Recent work explores neural radiance fields for radar, semi-supervised learning for mapping, and probabilistic hierarchical classification to address real-world uncertainties in autonomous driving. Analysis of his 2020-2025 publications reveals a trajectory toward unifying geometric and semantic understanding in autonomous systems. His work demonstrates increasing integration of neural radiance fields with traditional filtering techniques, while advancing open-set recognition capabilities. Notable contributions include road geometry estimation frameworks, extended object tracking with PHD filters, and methods to mitigate data leakage in localization benchmarks. No scientific awards were mentioned in the provided materials. Hammarstrand has contributed to academic supervision methodology through his publication on improving master's thesis supervision efficiency, though specific student names are not listed. The provided information contains no details about research grants or funding sources. He operates within Chalmers University's Signal Processing research group, which develops advanced algorithms for automotive perception systems, focusing on sensor fusion techniques that combine radar, camera, and motion data for robust environmental understanding in autonomous vehicles.
Kun Gao is an Assistant Professor at the Department of Architecture and Civil Engineering at Chalmers University, leading the Urban Mobility Systems research group. His work bridges transportation engineering and data science to develop sustainable mobility solutions through electrification, shared systems, and connected infrastructure. Research Focus: Electric vehicle integration, charging infrastructure optimization, multimodal mobility systems Funding: Supported by JPI Urban Europe, FORMAS, Swedish Innovation Agency, Swedish Energy Agency, and Chalmers AoA Transport/Energy Methods: Machine learning, big data analytics, system optimization His recent publications emphasize autonomous vehicle safety , renewable energy integration , and equity in mobility systems . Current work explores AI-driven infrastructure planning and coupled transportation-energy systems.
Katahira Kenji is an Associate Professor at the School of Humanities and Social Sciences , Osaka University, with research spanning music psychology , emotion physiology , and Kansei informatics . His work bridges Cognitive neuroscience Human-computer interaction Design psychology Key research themes include flow experiences , emotional piloerection , and nonverbal communication in musical ensembles . He developed EEG-based flow state measurement 3D shape evaluation models Emotional response frameworks for sound and design His scientific contributions include Good Design Award (2014) ICMPC10 Travel Award (2008) Multiple best paper awards from Japanese academic societies Recent projects focus on Neural basis of voluntary piloerection Physiological measurement systems for peak experiences Kansei evaluation models for textures and 3D designs with grants from the Japan Society for the Promotion of Science.
Marcela Munera is an Associate Professor in Assistive Robotics at the University of the West of England (UWE Bristol). Her research focuses on robotic devices for rehabilitation, human-robot interaction, biomechanics, and movement analysis, with a particular emphasis on user-centered design approaches. Bioengineer, Universidad de Antioquia (Colombia) MSc in Mechanics and Materials, Ecole Nationale de Metz (France) PhD in Mechanics and Biomechanics, Université de Reims Champagne Ardenne (France) Key research areas include socially assistive robotics, rehabilitation robotics, and biomechanical modeling. She has led projects involving exoskeletons, smart walkers, and wearable sensors, often integrating participatory design and multimodal feedback mechanisms. Her publications highlight interdisciplinary applications in neurological rehabilitation (e.g., stroke, Parkinson's disease), autism therapy, and occupational health. Recent work explores smart upper-limb exoskeletons for construction workers, stress classification via novel sensors, and adaptive control systems for mobility assistance. FEDER, Region Champagne Ardenne Doctoral Grant Her doctoral research focused on industrial biomechanical assessments for sports performance and injury prevention, later expanding to human-centered rehabilitation robotics. She has collaborated on projects involving brain-computer interfaces, serious games, and cloud robotics frameworks like PoundCloud.
