Nelusa Pathmanathan is a Doctoral Researcher at the Visualization Research Center (VISUS) of the University of Stuttgart, affiliated with the Cluster of Excellence IntCDC and the Weiskopf Group. Her work focuses on integrating eye tracking and visualization techniques within augmented reality (AR) and immersive environments, aiming to enhance collaborative and situated visualization experiences. Her research interests span Eye Tracking , Augmented Reality , Human-Computer Interaction , and Data Visualization . Recent projects explore gaze analysis in collaborative AR tasks, movement patterns in real-world environments, and distance-based image analysis. Publications highlight applications in molecular education, accessibility for color vision deficiencies, and gaze-driven interfaces. Active in the Visualization Research Center and collaborating with the Weiskopf Group , Pathmanathan contributes to advancing AR technologies through empirical studies and interdisciplinary approaches. Contact details include phone +49 711 685 88633 and address at Allmandring 19, 70569 Stuttgart, Germany.
Prof. Dr. Petra Jansen holds the Chair of Sports Science at the University of Regensburg's Faculty of Humanities since 2008. She leads a research group focused on sports psychology, cognitive development, and mindfulness interventions. Her educational background includes a Habilitation in General Psychology (Heinrich Heine University Düsseldorf, 2005) and a PhD in Cognitive Psychology (Gerhard Mercator University Duisburg, 1999). Her research explores the intersection of movement, cognition, and emotion, with emphasis on: Mental rotation abilities and embodied cognition Mindfulness applications in sports and education Sustainable consumption behaviors and character strengths Developmental psychology across lifespan Gender differences in spatial cognition Recent publications (2024-2025) demonstrate strong trends in mindfulness interventions, sustainability psychology, and advanced methodologies in mental rotation studies. Work frequently employs virtual reality, implicit attitude measurements, and cross-cultural validations, with emerging focus on developmental applications in children and adolescents. As principal investigator, she oversees multiple projects including studies on embodied cognition, mindfulness curricula, and sport-specific psychological interventions. She mentors doctoral candidates and coordinates the university's doctoral committee (Chair 2012-2021). Additional roles include mindfulness teacher certification and dance therapy qualifications enhancing her interdisciplinary approach.
Balandino Di Donato is a Lecturer in interactive audio at Edinburgh Napier University's School of Computing Engineering and the Built Environment. His research focuses on soundscapes in mountaineering environments and embodied human-computer interaction in music. He led AHRC-funded projects on Sound Design Pipeline for Cross-platform 360 Virtual Productions BSL in Embodied Music Interaction and chaired the Audio Mostly 2023 conference. Education includes a 2021 PhD from Royal Birmingham Conservatoire (Birmingham City University) in Designing Embodied Human-Computer Interactions in Music Performance . Prior academic roles featured collaborations with Goldsmiths (ERC BioMusic project), De Montfort University (Creative AI Dataset), and University of Leicester (INCITE project). Research spans Mountain soundscape analysis Accessible audio-visual-haptic systems Biosignal-driven musical instruments 360 audio design British Sign Language integration Interactive sound art installations Scientific achievements include Biennale awards (2018, 2019) Audio Mostly steering committee Conference chair and session roles EPSRC and AHRC grant reviewer
Robert F. Hess, Ph.D., D.Sc. is a Professor and Director of Research in the Department of Ophthalmology at McGill University. He also serves as the Director of the McGill Vision Research Unit, a leading center for vision science research. His work focuses on understanding visual perception mechanisms, particularly in conditions like amblyopia. Dr. Hess's research interests span multiple areas of vision science including: Adult Neuroplasticity Amblyopia (both clinical and laboratory aspects) Visual contour processing Brain imaging related to vision Motion perception Shape perception Spatial vision Stereo vision Transcranial Magnetic Stimulation (TMS) His recent publications reveal a strong focus on amblyopia research, particularly examining binocular vision deficits, spatial scrambling effects on visual perception, and novel treatment approaches. Dr. Hess has been investigating how dichoptic training methods can improve visual function in amblyopia, moving beyond traditional patching approaches. His work often combines psychophysical testing with computational modeling to understand the neural mechanisms underlying visual perception deficits. As Director of the McGill Vision Research Unit, Dr. Hess leads a collaborative research environment that brings together multiple investigators studying various aspects of vision. The unit appears to be well-integrated with both basic science and clinical ophthalmology at McGill University.
Alex Baldwin is an Assistant Professor at McGill University within the Department of Ophthalmology & Visual Sciences. He serves as a Junior Scientist in the Brain Repair and Integrative Neuroscience (BRaIN) program at the Research Institute of the McGill University Health Centre. Supervisor in McGill's Integrated Program in Neuroscience (IPN) Supervisor in Quantitative Life Sciences program Laboratory located at Montreal General Hospital Research focuses span computational neuroscience, visual psychophysics, and binocular vision mechanisms , particularly examining: Amblyopia and spatial scrambling Aging-related changes in stereopsis Visual noise adaptation Contrast summation models Contour integration processes Digital therapeutic development His lab employs Matlab/Octave (Psychtoolbox), Python (PsychoPy), and Unity/C# for experimental design, with Python (Jupyter) and Matlab (Palamedes Toolbox) for data analysis. Collaborations include Wenzhou Medical University. Scientific recognition includes: NSERC Discovery Grant (2022-2027) HBHL Ignite Funding FRQ-S Vision Health Research Network Pilot Training opportunities available for undergraduate (PSYC-396/COGS-444/COGS-401) and graduate students , with current advisees working on topics including: Visual snow syndrome neural mechanisms Binocular imbalance in aging Contour integration modeling Adaptive strategies in amblyopia Dichoptic ebook therapy development
Erik Wolf is a research associate at the University of Hamburg's Department of Informatics, specializing in Human-Computer Interaction (HCI) and Extended Reality (XR) technologies. His work focuses on optimizing presence in virtual environments through studies of plausibility , co-presence , and place illusion , particularly in the Horizon Europe project 'PRESENCE'. Prior to this role, he completed his PhD at the University of Würzburg, investigating Individual-, System-, and Application-Related Factors Influencing the Perception of Virtual Humans in Virtual Environments . Education : Bachelor's and Master's in Human-Computer Interaction from the University of Würzburg Visiting researcher at University of Queensland's Cognitive Engineering Research Group (2016-2017) Research Interests : XR User Experience Virtual Human Perception Body Awareness & Self-Identification in VR Digital Health Applications Presence & Immersion Scientific Contributions : Developed validated scales for virtual human plausibility Explored avatar personalization effects on body perception Investigated multimodal interaction frameworks Created tools for intelligent virtual humans development His work has been recognized with multiple awards including the DIVR Science Award 2019 and multiple Best Paper distinctions. He serves as a reviewer for leading conferences including IEEE VR, ACM CHI, and IEEE ISMAR.
William F. Auffermann is a Professor at the Department of Radiology and Imaging Sciences, University of Utah, with a dual board certification in Diagnostic Radiology and Clinical Informatics. He serves as Vice Chair for IT and Informatics and Section Chief for Cardiothoracic Imaging, focusing on improving informatics systems and medical education through simulation-based tools. Education: MD and PhD from University of Minnesota Medical School, Fellowship in Cardiothoracic Imaging at Duke University. Board Certifications: American Board of Radiology (Diagnostic Radiology), American Board of Preventive Medicine (Clinical Informatics). His research centers on human factors engineering , integrating medical image perception studies with computer simulation-based education to reduce diagnostic errors. Key areas include biomedical informatics , machine learning , structured reporting , and clinical decision support . Collaborative work spans chest and cardiac imaging with applications in occupational lung disease (NIOSH B-Reader certification). Recent publications emphasize AI integration in radiology , perceptual training , and gaze-display feedback for medical education. He also contributed to ACR Appropriateness Criteria for thoracic imaging and led studies on virtual reality education and gamification in radiology training .
Katsushi Arisaka is a Distinguished Professor in the Department of Physics and Astronomy at the University of California, Los Angeles (UCLA), within the College of Physical Sciences. His research spans multiple disciplines including particle physics, cosmology, biophysics, and neurophysics. Dr. Arisaka began his academic journey at the University of Tokyo in 1979 as a graduate student under Professor Masatoshi Koshiba, working on the development of the world's largest 20-inch photomultiplier for the Kamiokande Experiment. He moved to the United States in 1985 and established his research group at UCLA in 1988. His educational background includes a Ph.D. from the University of Tokyo, though specific dates are not provided in the available materials. Professor Arisaka's research interests center around answering fundamental questions about the universe and life itself. His work explores three primary areas: the origin of the universe through dark matter research and cosmic ray studies; the origin of life through biophysics and molecular tracking; and the origin of consciousness through neurophysics. His approach consistently leverages advanced photon detection technologies across these diverse fields. Early in his career, he focused on rare decay processes of kaons to understand CP-violation at BNL and Fermilab, then shifted to cosmology in 1998, participating in the Pierre-Auger Cosmic Ray Observatory and CMS Endcap Muon Chambers for LHC at CERN. Since 2007, his main focus has been dark matter experiments including XENON100 at Gran Sasso in Italy and its successor XENON 1Ton, while also collaborating with DarkSide and MAX projects. His recent publications (2020-2023) reveal a strong trend toward interdisciplinary research, particularly at the intersection of physics, neuroscience, and consciousness studies. The 2022-2023 publications show a significant focus on visual perception, neural holographic tomography, and the grand unified theory of mind and brain. Earlier works (2017-2020) demonstrate continued activity in dark matter detection with experiments like XENON and DarkSide, as well as applications of advanced photon detectors to biological imaging. Grand Unified Theory of Mind and Brain (2022 series) Visual Perception of 3D Space and Shape (2022 series) Transverse sheet illumination microscopy (2023) DarkSide direct dark matter search (2017) Dr. Arisaka has been actively involved in major international collaborations including the CMS experiment at CERN's Large Hadron Collider, the XENON dark matter project at Gran Sasso in Italy, and the DarkSide experiment. His laboratory has developed innovative imaging techniques such as the Spatio-Temporal Multiplexing (STEM) microscope for multiple plane imaging and high-speed confocal microscopy systems capable of capturing 1,000 frames per second. The STEM microscope, developed with Adrian Cheng, allows simultaneous scanning of multiple planes using time differences between beams. At UCLA, Professor Arisaka has established productive collaborations across campus, particularly with the Medical School, where his advanced photon detection technologies have been applied to neuroscience research. His laboratory has contributed to significant discoveries in hair cell oscillation measurements and neural development studies. He teaches several physics courses including Physics 6B, 6C, 89 for 6B, 89 for 6C, and Physics 19, and regularly seeks graduate and undergraduate students interested in his research directions. His group has developed virtual reality systems for rats to study spatial recognition in the hippocampus in collaboration with Prof. Mayank Mehta's group. The Arisaka Lab maintains state-of-the-art facilities including a Photon Detector Lab and collaborates with multiple research groups on campus. Current research directions include the development of Transverse Sheet Illumination Microscopy (TransIM) and continued work on dark matter detection with next-generation XENON experiments. His lab's philosophy centers on using physics principles to answer the fundamental questions: 'Where do we come from? What are we? Where are we going?' through experimental approaches rather than philosophical speculation.
Sasan Matinfar is a research scientist at the Technical University of Munich (TUM), affiliated with the Chair of Computer Aided Medical Procedures (Prof. Navab) and the Munich Center for Machine Learning (MCML). He serves as scientific staff at Rechts der Isar Hospital, developing XR and sonification systems for surgical environments since 2020. His educational background includes: Master’s and Bachelor’s in Computer Science, Ludwig Maximilian University of Munich (LMU) Musicology, Franz Liszt University of Music, Weimar Piano Interpretation, Art University of Tehran Matinfar pioneers medical sonification and multisensory XR, creating auditory interfaces that convert tissue properties into sound for surgical guidance. His work in user-centered design produces clinically viable tools like the Ocular Stethoscope for retinal procedures and physics-based BioSonix frameworks, merging computer vision with perceptual audio engineering to enhance intraoperative precision without visual overload. Analysis of his 12 recent publications (2017-2025) reveals an evolving research arc from foundational surgical soundtracks to sophisticated context-aware sonification. Current work integrates generative AI with real-time tissue deformation modeling, focusing on multimodal frameworks where auditory feedback complements visual navigation in complex surgeries like cardiac interventions and retinal peeling. Key recognitions include: The Data Sonification Award (2025) MICCAI 2023 Best Paper Nominee (top 3% of submissions) MICCAI Young Scientist Award (2017, top 2% of papers) As an educator, Matinfar mentors students through TUM courses including Medical Augmented Reality (WS 2025/26) and Surgical Robotics, while co-organizing the Medical Augmented Reality Summer School and IEEE ISMAR 2025’s MIX Workshop. His patented technologies emerge from collaborations with Politecnico di Milano, TU Dresden’s CeTI, and Balgrist Hospital Zurich, securing interdisciplinary grants in surgical data science. Matinfar operates within TUM’s NARVIS Lab for medical image analysis and RobUSt for robotics-ultrasound integration, leveraging the German Heart Center Munich (DHM) infrastructure to validate XR systems in live surgical workflows and advance vision-language models for intraoperative decision support.
Richard H. Granger, Jr. is a Professor at Dartmouth College , affiliated with the Thayer School of Engineering and the Psychological and Brain Sciences department. His work spans computational and cognitive neuroscience, focusing on brain circuit analysis, neuroimaging, robotics, and brain engineering. B.S., Massachusetts Institute of Technology Ph.D., Yale University His research integrates artificial intelligence, neurobiology, and mathematical modeling to understand fundamental mechanisms of learning, memory, and brain evolution. He develops algorithms inspired by cortical-subcortical loops and explores brain-inspired hardware architectures for efficient computing. Recent publications highlight his innovations in neural network design (Hamiltonian bitwise architecture), neuroimaging analyses, and cognitive modeling. His work bridges theoretical neuroscience with practical applications in medical diagnostics and robotic systems. Invited talk at UC San Diego (2018) Keynote speaker at Artificial General Intelligence Conference (2014) TEDx talk at Dartmouth (2010) Contact: Richard.Granger@dartmouth.edu , Moore Hall, Dartmouth College.
Kathleen Mullen, PhD, is a Senior Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC) at the Montreal General Hospital site and a Professor in the Department of Ophthalmology and Visual Sciences at McGill University's Faculty of Medicine and Health Sciences. Her research is centered on understanding how the brain processes visual information, with a strong focus on colour vision, functional brain imaging (fMRI), and brain stimulation (TMS). Research Focus: Mullen's work delves into the encoding and analysis of colour within the human brain, employing psychophysics, fMRI, and TMS to explore how the visual system interprets colour. She investigates colour vision deficits in diseases such as optic neuritis, glaucoma, and amblyopia. Publications: Her recent publications span topics from fMRI-guided TMS studies of visual cortex specialization to behavioural and neural adaptation in colour contrast processing. These works reflect a deep engagement with both fundamental neuroscience and clinical applications. Contact: kathy.mullen@mcgill.ca
Elena Umili is an Assistant Professor (RTD-A) at the Department of Computer, Control and Management Engineering (DIAG) of Sapienza University of Rome, specializing in Neurosymbolic AI research. Her work bridges deep learning with symbolic reasoning systems. She received her PhD in Engineering in Computer Science from Sapienza University of Rome in 2023 under the supervision of Prof. Giuseppe De Giacomo and Prof. Roberto Capobianco. Her doctoral thesis focused on 'Discovering Logical Knowledge in Non-Symbolic Domains'. Her research interests center on Neurosymbolic AI integration , particularly: Combining deep machine learning with symbolic reasoning Temporal logic specifications in neural systems Automata learning through neural relaxations Non-Markovian reinforcement learning tasks Visual grounding of logical specifications Analysis of her recent publications reveals a strong focus on neural-symbolic integration where she develops frameworks like DeepDFA and Neural Reward Machines. Her work consistently addresses the challenge of incorporating logical constraints into deep learning systems, with applications spanning robotics, sequence generation, and visual reasoning. The research demonstrates increasing sophistication in handling temporal logic specifications within neural architectures. She is an active member of research groups focused on Artificial Intelligence and Knowledge Representation, as well as Artificial Intelligence and Robotics at Sapienza University. While no formal advisees or major awards are currently documented in her public profile, her recent publications indicate significant contributions to the neurosymbolic AI field through top-tier conferences including ECAI, KR, and specialized workshops. Her work shows strong potential for future impact in bridging the gap between neural and symbolic AI paradigms.
Valeria Burgio is a Research Fellow at Ca' Foscari University of Venice's Department of Philosophy and Cultural Heritage. She teaches Communication, Visual, and Interior Design at the university's School for International Education. Previously, she was a tenured researcher at the Free University of Bolzano for six years. Her research spans: Microbiome visualization in scientific research (ERC Health-X-Cross project) Graphic design processes and uncertainty representation Infographics critique, data semiotics, and visual journalism Pandemic diagrams, border visualization, and cultural semiotics Her 15 most recent publications (2014-2024) demonstrate consistent focus on: Semiotic analysis of scientific visualization Diagrammatic representations of ecological and social systems Critical studies of infographics in public communication Interdisciplinary approaches bridging design, semiotics, and cultural studies She holds a PhD in Theories of the Arts from Iuav University, Ca' Foscari, and Venice International University, following an honors degree in Communication Sciences from the University of Bologna. She completed postdoctoral work at EHESS/CNRS Paris and Iuav University.
Bruce Draper is a Professor and Chair of the Department of Computer Science in the College of Natural Sciences at Colorado State University. His work bridges artificial intelligence, machine learning, and computer vision, with a strong emphasis on real-world applications involving visual data and intelligent systems. Research Interests: Draper's research centers on machine learning with a focus on visual learning, adversarial AI, and visual agents. He investigates how AI systems can perceive, interpret, and interact with visual environments through technologies like facial recognition, object tracking, augmented reality, and automated visual communication. His work addresses both the capabilities and vulnerabilities of modern AI, particularly in defending systems against adversarial attacks. Publication Trends: His recent scholarly output reflects a consistent trajectory in advancing computer vision and AI robustness. The articles span topics from adversarial defense mechanisms and visual agent autonomy to scalable learning frameworks and real-time video analysis. Collectively, they emphasize secure, efficient, and context-aware visual intelligence systems grounded in deep learning and representation learning. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: While no students or grants are explicitly listed, his leadership role as department chair and prior experience as a DARPA program manager suggest extensive involvement in research funding, mentorship, and high-impact project direction. His background indicates likely supervision of graduate students and management of federally funded research initiatives in AI and computer vision. Labs and Teams: Although no specific lab or research group is named, his research scope implies leadership or affiliation with interdisciplinary teams working on AI security, computer vision, and augmented reality systems within the Department of Computer Science at CSU.
Bertalan Polner is an Assistant Professor at the Institute of Psychology , Eötvös Loránd University, affiliated with the Department of Clinical Psychology and Addiction . He serves as a Member of the Research Ethics Committee and maintains an active research profile at Radboud University’s Donders Centre for Cognition as a PostDoc researcher. Academic Rank: Assistant Professor Current Institutions: Eötvös Loránd University (ELTE), Radboud University Research Focus: Schizotypy-psycho sis interactions, computational psychiatry, sleep-cognition links, memory mechanisms, and emotion regulation. Dr. Polner’s research explores how positive schizotypy interacts with sleep disturbances and visual perception anomalies , using network analysis to map relationships between personality traits and mental health outcomes. His work often integrates computational modeling (e.g., drift diffusion models, predictive coding) to understand cognitive deficits in psychotic disorders. Recent publications highlight his contributions to: Mapping schizotypy’s role in stress-reactivity (2025) Investigating REM sleep’s impact on mind-wandering (2023) Analyzing reward processing in borderline personality disorder through schema modes (2023) He also develops educational tools like the introduction_to_R and Structural Equation Modeling repositories on GitHub, supporting psychological research methodology.
