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Jiaxiang ZhangView profile

Professor

• Artificial Intelligence
• Machine Learning
• Cognitive Neuroscience
• +2 more

Jiaxiang Zhang is Professor of Artificial Intelligence in the Department of Computer Science at Swansea University's Faculty of Science and Engineering. He holds a PhD in Computational Neuroscience from the University of Bristol and previously held positions at the University of Birmingham, MRC Cognition and Brain Sciences Unit (Cambridge), and Cardiff University where he founded the Cognition and Computational Brain Lab. Zhang's research integrates computational modeling, machine learning, brain imaging (MEG/EEG/fMRI), and experimental approaches to study human cognition, aging, and neurological disorders. Key focus areas include: Neural mechanisms of decision-making and problem-solving Computational models of cognitive processes AI applications in healthcare diagnostics and neuroimaging Brain network dynamics in neurological conditions Recent publications emphasize deep learning models for neural data, multimodal brain connectivity, decision-making impairments in Parkinson's disease, and neuroinformatics tools. His work shows strong clinical translation through epilepsy biomarker development and emergency department outcome prediction. Zhang has led research grants from ERC, MRC, BBSRC, and Wellcome Trust. As primary investigator for multiple projects, he oversees significant computational neuroscience initiatives. He is available for postgraduate supervision.

• Neuroscience
• Artificial Intelligence
• Neuronal Modeling
• +5 more

Eilif B. MULLER is a Professor in the Department of Neurosciences at Université de Montréal, Principal Investigator of the Architectures of Biological Learning Lab (ABL-Lab) at CHU Sainte-Justine Research Center, and Associate Faculty at Mila (Quebec AI Institute). His work bridges neuroscience and artificial intelligence, focusing on understanding how sensory perception is learned in the neocortex through biophysical simulations and deep learning models. He holds affiliations with IVADO (Institute for Data Valorization) and contributes to strategic initiatives like the UNIQUE Québec Center. His research integrates empirical neurophysiology with computational models, exploring dendritic processing and synaptic plasticity to inform both biological understanding and AI advancements. Teaches NSC-6044 and NSC-6045 (Neuroscience Colloquia) at Université de Montréal. Leads projects on neocortical learning mechanisms and their implications for neurodevelopmental disorders. Recipient of grants from CRSNG (Natural Sciences and Engineering Research Council), FRSQ (Health Research Fund), and institutional funding. Publications span topics in computational neuroscience, neural network modeling, and interdisciplinary AI-neuroscience research. Collaborates extensively across institutions to advance large-scale brain simulations and data-driven models.

• Precision Agriculture
• Optical Engineering
• Remote Sensing
• +3 more

Dr. Jose Manuel Sánchez Peña is a Full Professor at Universidad Carlos III de Madrid (UC3M), affiliated with the Grupo Universitario de Tecnologías de Identificación (GUTI). His research focuses on precision agriculture technologies, optoelectronics, and neuroscientific interfaces. He leads projects on drone-based crop monitoring, renewable energy systems, and machine learning applications in environmental science. Key research areas include: UAV remote sensing for water stress and weed management in viticulture and maize Optical communication systems leveraging photovoltaic integration Machine learning models for precision agriculture Neuroscientific studies on multisensory emotion elicitation Publishing trends show strong focus on: Drone technology advancements (42% of recent articles) Optoelectronics and VLC systems (28% of recent articles) Neuroscience applications (15% of recent articles) Sustainable agricultural practices (12% of recent articles) Laboratory activities center around GUTI's interdisciplinary teams working at the intersection of engineering, agriculture, and neurotechnology.

Anton BergView profile

Research Fellow

• Cognitive Science
• Computer Vision
• Religious Studies
• +7 more

Anton Berg is a Postdoctoral Researcher at the University of Helsinki, affiliated with the Department of Digital Humanities within the Faculty of Arts and the Helsinki Institute for Social Sciences and Humanities (HSSH). He is also a member of the methodological unit at HSSH, focusing on interdisciplinary research at the intersection of cognitive science, religious studies, and artificial intelligence. His educational background spans computer science, cognitive science, and religious studies, enabling him to bridge technical and humanistic approaches to AI. His research primarily investigates how commercial image recognition systems interpret and categorize religious content, exploring issues of bias, representation, and the datafication of religion. Berg's research interests include computer vision systems, automatic image recognition, machine and deep learning, large language models, and the relationship between religions, worldviews, and values related to AI technologies. He particularly focuses on inequality issues, the datafication of religion, the datafication of societies, the social scientific study of religion, and the cognitive science of religion. His work combines technical analysis of AI systems with social scientific perspectives on religion and technology. His recent publications demonstrate a strong focus on examining biases in commercial image recognition services, particularly regarding religious content, with significant contributions to understanding representational silence and racial biases in these systems. He has also conducted important work on pandemic psychology, contributing to large-scale international studies on COVID-19 responses across 69 countries. Berg has been actively involved in numerous academic activities, including presentations at international conferences on topics such as computer vision in religious studies, mediatized religious populism, and biases in image recognition services. His research has been presented at venues including the International Association for the Cognitive Science of Religion. His teaching areas include religious studies, cognitive science, data science, and religion and technologies, reflecting his interdisciplinary approach to understanding the relationship between digital technologies and religious phenomena.

Alan A. StockerView profile

Professor

• Computational Neuroscience
• Bayesian Inference
• Sensory Adaptation
• +4 more

Alan A. Stocker is a Professor in the Department of Psychology at the University of Pennsylvania, with affiliations in the Neuroscience Graduate Group, Bioengineering Graduate Group, and Computational Neuroscience Initiative. He leads the Computational Perception and Cognition (CPC) Laboratory, focusing on how prior beliefs and expectations shape sensory perception through Bayesian inference and efficient coding principles.

Cyriel DielsView profile

Researcher

• Human Factors in Automotive Design
• Transport Psychology
• Human-Machine Interaction
• +4 more

Cyriel Diels is a researcher at the Royal College of Art's Intelligent Mobility Design Centre (IMDC) , focusing on automotive and transport design at the intersection of human factors, technology, and sustainable mobility. His career spans academia (Coventry University, RCA) and industry (Jaguar Land Rover, Transport Research Laboratory). Expertise : Human-machine interaction in automated vehicles, motion sickness mitigation, passenger experience design Key Projects : DOMUS (EU), SIMUSAFE (EU), UK CITE (Innovate-UK) Recent research explores motion discomfort alleviation through design interventions and adaptive HMI solutions in autonomous vehicles. Funded by European Commission, Innovate-UK, and automotive industry partners, his work combines cognitive psychology with applied transport design . Publications analyze: Simulator sickness management Visual-motion cue conflicts Seating appearance effects on comfort Warning sign design for vehicle interfaces Multi-axis motion sickness mechanisms Automated driving trust compatibility Current students include Yi Li, Pooya Sareh, Robin Severs, and Selin Zileli. Collaborative projects span future cities , intelligent mobility , and human-centered vehicle design .

Nicholas CumminsView profile

Lecturer

• Artificial Intelligence
• Machine Learning
• Affective Computing
• +6 more

Dr. Nicholas Cummins is a Lecturer in AI for Speech Analysis at King’s College London, specializing in applying machine learning to health conditions, particularly mental health disorders. He holds roles in the Department of Biostatistics & Health Informatics and is affiliated with the NIHR Maudsley Biomedical Research Centre. His research focuses on speech processing, affective computing, and digital phenotyping, with projects like RADAR-CNS and DE-ENIGMA. He earned his PhD from UNSW Australia (2016) and conducted postdoctoral work in Germany before becoming habilitation candidate at the University of Augsburg. Education: PhD in Electrical Engineering, UNSW Australia (2016) Habilitation Candidate, Chair of Embedded Intelligence for Healthcare, University of Augsburg Research Interests: Machine learning for mental health monitoring Speech-based biomarkers for depression and psychosis Wearable device integration for health tracking Multilingual speech analysis Key Projects: RADAR-CNS: Data analysis for neurological conditions DE-ENIGMA, TAPAS, sustAGE (Horizon 2020) National Science Foundation of China project on speech-based depression diagnosis Grants & Awards: Over 100 peer-reviewed publications (h-index: 23) NSFC-funded project on speech analysis for depression Reviewer for IEEE, ACM, ISCA journals Labs & Teams: Involved in the NIHR HealthTech Research Centre in Brain Health and the EMBRACE initiative for maternal/child health with AI.

Robert JacobView profile

Professor

• Human-Computer Interaction
• Brain-Computer Interfaces
• Implicit Interaction Techniques
• +3 more

Robert Jacob is a Professor of Computer Science at Tufts University's School of Engineering, where he leads research in human-computer interaction with particular focus on implicit brain-computer interfaces. His work bridges computer science, cognitive science, and interface design to create adaptive systems that respond to users' cognitive states without explicit input. His educational background includes a Ph.D. from Johns Hopkins University. Professional milestones include: ACM CHI Academy membership (2007) ACM Fellow designation (2016) Leadership roles as ACM SIGCHI Vice President and conference chair for CHI, UIST, and TEI Professor Jacob's research centers on implicit interaction techniques, particularly using fNIRS brain sensing to create adaptive interfaces. His work has evolved from foundational studies in reality-based interaction and tangible programming to current neuroadaptive systems that measure cognitive workload in real-time. This research spans domains including music learning, museum education, and general user interface adaptation. His publications reveal consistent focus on brain-computer interfaces since 2012, with increasing sophistication in physiological measurement and machine learning techniques. Recent work integrates multiple physiological signals beyond brain data to create comprehensive user state models. Major recognitions include: CHI 2016 Best Paper Award for music learning research CHI 2014 and 2012 Best Paper Honorable Mentions Keynote addresses at major conferences including Neuroadaptive Technology Conference (2017) Extensive media coverage in New Scientist, IEEE Computer, and Boston Globe Professor Jacob has mentored 17 PhD students who now hold faculty positions at institutions including Worcester Polytechnic Institute, Northwestern University, and Carleton University. His HCI Lab, located in the Joyce Cummings Center, receives funding from NSF and other sources supporting neuroadaptive interface research. Current projects focus on broadening implicit interaction to include multiple physiological measurements while maintaining user privacy and system transparency.

Stephanie PosthumusView profile

Associate Professor

• Ecocriticism
• French Literature
• Animal Studies
• +3 more

Stephanie Posthumus serves as Associate Professor at McGill University, specializing in contemporary French and Québécois literature through the lens of ecocriticism, animal studies, and plant studies. Her research interrogates representations of the non-human across European literary traditions while examining cultural specificities in environmental discourse. Professor Posthumus develops French-specific ecocritical frameworks by engaging with thinkers like Guattari ( écosophie ), Latour ( nature-culture ), and Serres ( contrat naturel ), arguing against universal ecocritical models. Her work spans three interconnected domains: constructing French ecocriticism through monographs like French Écocritique (2017); analyzing animal representations via co-edited volumes including French Thinking about Animals (2015); and pioneering plant studies in Québécois contexts through recent works like Entre les feuilles (2024). She further bridges digital and environmental humanities through SSHRC-funded platform development. Her publication trajectory (2016-2024) reveals intensifying focus on vegetal agency and digital methodologies within ecocritical practice. Articles consistently address cultural differences in environmental representation, with increasing attention to sensory plant studies and posthumanist reconfigurations of human/non-human boundaries across French and Québécois literary landscapes. Professor Posthumus leads the Digital Environmental Humanities initiative, which functions as a research hub featuring digital exhibits, analytical tools like topic modeling, and pedagogical resources. This SSHRC Connections grant project (2013) exemplifies her commitment to interdisciplinary knowledge mobilization through digital innovation. She currently directs collaborative research networks connecting Canadian environmental humanities scholars with digital humanities practitioners, fostering experimental approaches to ecological representation through multimodal projects examining plant intelligence and sensory environmental engagement.

Shabnam Sadeghi EsfahlaniView profile

Associate Professor

• Robotics
• Mechatronics
• Artificial Intelligence
• +3 more

Dr. Shabnam Sadeghi Esfahlani is an Associate Professor in Robotics at the School of Engineering and the Built Environment, Anglia Ruskin University , where she serves as Deputy Leader of the BORI research group and leads the Automation & Robotics MSc program. Her interdisciplinary expertise spans mechatronics, artificial intelligence, virtual reality, and serious games , with a focus on applications for rehabilitation, medical training, and autonomous systems . As a Chartered Engineer and Senior Fellow of the Higher Education Academy , she has secured significant funding from Innovate UK, Horizon 2020, and GCRF , with grants exceeding £3 million. Education PhD in Mechanical Engineering, Anglia Ruskin University BSc (First Class) in Statistics & Mathematical Science, Shahid Beheshty University Her research integrates AI with robotics for societal impact, exemplified by the open-source SROBO ground robot and projects like Rehabgame and the Assistive Feeding Robot . She has published over 45 peer-reviewed articles and contributes to academic communities as a journal guest editor and conference organizer . Key collaborations include IET, IMechE, and the Nuffield Foundation as a mentor for young students. Scientific Awards & Recognitions: Chartered Engineer (CEng), Engineering Council UK Senior Fellow (SFHEA), Higher Education Academy Student-Voted 'Made a Difference Award' (2018) Post-Graduate Certificate in Higher Education

Hao ZhangView profile

Associate Professor

• Robotics
• Artificial Intelligence
• Computer Vision
• +6 more

Hao Zhang is an Associate Professor in the Department of Computer Science at the Manning College of Information and Computer Sciences (CICS), University of Massachusetts Amherst. He directs the Human-Centered Robotics Laboratory (HCRLab), focusing on lifelong collaborative autonomy, robot adaptation, and human-robot teaming. His research integrates robotics, AI, and machine learning to develop algorithms for real-world applications like manufacturing, autonomous driving, and environmental monitoring. He holds an NSF CAREER Award and DARPA Young Faculty Award, among other recognitions. Dr. Zhang earned a PhD from the University of Tennessee, Knoxville (2014) and an MS from the Chinese Academy of Sciences (2009). His work addresses challenges in unstructured environments through innovations like self-reflective terrain adaptation and graph-based perception systems. He actively promotes equity in robotics through his PROGRESS outreach program. His research sponsors include NSF, DARPA, and industry partners such as Toyota. Publications span conferences like RSS, ICRA, and IROS, with best paper awards. He serves on editorial and program committees for top-tier journals/conferences including RA-L, NeurIPS, and AAAI.

Raymond H. CuijpersView profile

Associate Professor

• Cognitive Robotics
• Human-Robot Interaction
• Socially Assistive Robotics
• +5 more

Raymond H. Cuijpers is an Associate Professor at Eindhoven University of Technology in the Human Technology Interaction group. His research focuses on Cognitive Robotics , Human-Robot Interaction , and Artificial Intelligence for cognitive agents, with applications in healthcare robotics and aging population support. PhD in Physics of Man from Utrecht University (2000) Postdoctoral research at Erasmus MC Rotterdam and Radboud University Nijmegen Key research areas include: Developing socially intelligent robots with proper social cue interpretation Hybrid AI approaches for real-world complexity handling Visual-haptic perception integration in human motor control Service robots for COPD patient assistance (KSERA project) Rescue robotics and tele-operation applications Recent research output (2025) includes studies on: Personalization in human-robot communication Optimal lighting for elderly visual perception Human-robot bonding mechanisms Interactive sensorized platforms for homecare (GUARDIAN) Audiovisual temporal integration in virtual environments He coordinates large-scale European projects like GUARDIAN and previously KSERA, contributes to sustainable development goals through healthcare robotics, and serves on editorial boards of leading journals including International Journal of Social Robotics . His work spans both technical robotics development and human-centric interaction studies.

• Perceptually guided graphics
• Virtual characters and crowds
• Virtual reality
• +4 more

Cathy Ennis is an Assistant Professor in the Department of Computer Science at Maynooth University, Ireland, specializing in perceptually guided graphics and virtual reality. She is actively involved in research and teaching, with affiliations to the ADAPT Centre and D-REAL SFI Centre for Research Training. Education: BEng in Electronic Engineering, Maynooth University MSc in Cognitive Science, University College Dublin PhD in Computer Graphics, Trinity College Dublin PG Dip in Higher Education Teaching and Learning, DIT Research Interests: Dr. Ennis's research centers on creating realistic virtual humans and crowds, exploring multisensory perception in VR, and applying these technologies in serious games and interactive systems. Her work integrates AI, HCI, and immersive technologies to enhance user engagement and learning. Her recent publications reflect a strong focus on virtual character realism, VR-based education, and machine learning applications in animation and interaction. Notable themes include speech-animation realism, cultural VR experiences, and reinforcement learning for character control. Scientific Awards: Best Paper Award, IEEE VR 2022 Teaching and Supervision: Dr. Ennis currently teaches CS401 (Machine Learning and Neural Networks) and CS261 (Multimedia Technology). She is actively seeking PhD students and collaborators interested in VR, games, and virtual characters, particularly using machine learning for gesture generation and engagement. Labs and Teams: She is a Funded Investigator with the ADAPT Centre and D-REAL SFI Centre for Research Training, contributing to interdisciplinary research in AI, HCI, and immersive technologies.

• Cognitive Neuroscience
• Developmental Neuroscience
• Multisensory Perception
• +5 more

Ambra Ferrari is a Research Fellow at the Interdepartmental Center for Mind/Brain Sciences (CIMEC) within the University of Trento. Her work focuses on cognitive development, multisensory perception, and neuroimaging techniques. She teaches courses such as Cognitive neuroscience of infant development and contributes to the Cognitive Neuroscience program in the Department of Psychology and Cognitive Sciences. Her research integrates methodologies from neuroscience and psychology to study infant cognition, social development, and sensory integration. She develops computational tools like the WTools MATLAB toolbox for analyzing infant neural data. Ferrari's work bridges developmental psychology, psycholinguistics, and sensory neuroscience, emphasizing how prior expectations guide perception during communication. In teaching, she employs journal clubs and seminars to foster critical analysis of empirical studies and contemporary theories in cognitive development. Her courses aim to equip students with skills to evaluate experimental research and understand neurobiological foundations of cognition. Her laboratory (CIMEC) focuses on adaptive behavior, cross-modal plasticity, and embodied communication. Current projects explore statistical learning mechanisms, attention modulation in multisensory perception, and the role of gesture-prosody interactions in language comprehension.

• Human-Computer Interaction
• Virtual Reality
• Tabletop Displays
• +7 more

Mark Hancock is a Professor and Chair of the Department of Management Science and Engineering at the University of Waterloo's Faculty of Engineering. He directs the Touchlab research group and holds cross-appointments in Systems Design Engineering and the David R. Cheriton School of Computer Science. His research focuses on designing interactive technologies that leverage human movement and perception to create novel interaction paradigms. Education: 2010: PhD in Computer Science, University of Calgary 2004: MSc in Computer Science, University of British Columbia 2002: BSc in Mathematics & Computer Science, Simon Fraser University Research Interests: Hancock's work centers on human-computer interaction, particularly technologies enabling richer physical interaction through hands, fingers, and body movements. His lab explores tabletop displays, large-screen interfaces, VR/AR systems, multi-touch interaction, 3D interfaces, and collaborative systems. Recent work examines VR applications for productivity, stress reduction through gaming, and gender-inclusive maker spaces. Publication Trends: Recent articles show strong emphasis on virtual reality applications (productivity tools, health considerations), tangible interfaces (card-based systems, physical props), and social computing (collaborative systems, community studies). Methodologies include phenomenological analysis, systematic reviews, and comparative evaluations of interaction techniques. Awards: NSERC Discovery Accelerator Supplement (2016) ACM CHI Golden Mouse Award (2016) ISS 2018 10-Year Impact Award Two ACM CHI Honorable Mentions (2019) Top Ontario Researcher recognition (2016) Teaching: Recent courses include Introduction to Computer Programming (MSCI 121), Algorithms and Data Structures (MSCI 240), Analytics and User Experience (MSCI 543), and Human-Computer Interaction (MSCI 630). Research Infrastructure: Directs the Touchlab, which develops novel interaction technologies. The lab's work bridges physical and digital interaction spaces, with applications in gaming, productivity tools, and collaborative systems.