Huub M.M. van de Wetering is an Assistant Professor at the Mathematics and Computer Science school of Eindhoven University of Technology (TU/e) , with affiliations to the Visualization and Visual Analytics departments, and the EAISI Health research institute. His research focuses on Interactive Visualization , Visual Analytics , and Medical Imaging applications, particularly in Dynamic Graphs and Neuroimaging . Recent work includes Pangenomic Variant Analysis and Streamline Transparency Techniques for brain structure visualization. Dr. van de Wetering has received Scientific Awards including: Best Demo Award (2022) Best Poster Award (2022) He teaches courses in Computer Graphics , Visualization Seminars , and Visual Computing Projects .
Derek Lomas is a researcher at Delft University of Technology’s Faculty of Industrial Design Engineering, specializing in Human-Centered Design and Human Technology Relations. He holds a PhD in Human-Computer Interaction from Carnegie Mellon University, an MFA in Social Design from UC San Diego, and a BA in Cognitive Science from Yale University. His research focuses on AI-driven wellbeing solutions, neurodesign, and educational technology. He leads projects like NeuroUX (mobile cognitive assessment software) and Zensus (patient wellness tracking), and has developed over 40 learning/assessment games. Key areas include music perception via EEG, AI alignment with human emotions, and design methodologies for positive AI. Education: B.A. Cognitive Science, Yale University, 2003 MFA Social Design, UC San Diego, 2009 PhD Human-Computer Interaction, Carnegie Mellon University, 2014 Research Interests: AI for wellbeing and mental health Neuroscience-driven design (EEG, brain-computer interfaces) AI ethics and human-AI interaction Game-based learning and assessment Key Projects: NeuroUX : Cognitive assessment software used in psychiatric research Zensus : AI-driven patient wellness monitoring system FactFlow : AI math fluency tool for children Vibe Research Labs : Exploring AI and positive human experiences Awards: Social Innovation Fellowship (PopTech) MacArthur Foundation Digital Media Learning Grant White House National STEM Game Competition McGinnis Business Plan Competition Winner Grants & Collaborations: Consultancy: Playpower Labs (UX, data science, software) Partnerships with UC San Diego, Brown University, and UT Austin
Dr. John Stins is an Assistant Professor at Vrije Universiteit Amsterdam, affiliated with the Faculty of Behavioural and Movement Sciences, specializing in Prevention and Rehabilitation, IBBA, and AMS departments. His research focuses on the intersection of cognition, emotion, psychopathology, and movement regulation, particularly postural control and balance. He investigates how affective states influence gait and static balance, and how cognitive factors like mental fatigue impact postural stability. Research Interests Influences of emotion on balance, including freeze and avoidance behaviors triggered by affective stimuli. Cognitive regulation of balance, exploring the role of working memory, attentional load, and mental fatigue. Applications of augmented reality in improving balance and gait for patients with Parkinson’s disease. Recent Contributions Recent work includes developing low-cost balance platforms, analyzing auditory and visual cue effects on movement, and studying the efficacy of AR interventions. His studies highlight marginal effects of perceived cognitive fatigue on balance in healthy adults and demonstrate how social cues modulate approach-avoidance behaviors. Awards & Grants Recipient of the HORIZON-CL2-2023-HERITAGE-01 Grant for neuroscientific research on cultural heritage. Research Fellowship of the Jena Excellence Programme (2024). Grants & Projects Current projects include 'Moving Emotions' exploring cultural heritage through neuroscience and 'Taking Approach Avoidance Research a Step Further.' Past projects focused on emotional exposure duration and gait initiation in Parkinson’s patients. Labs & Collaborations Collaborations span institutions like Université de Picardie Jules Verne and University of Pecs, with a focus on motor control, embodied cognition, and neurorehabilitation.
Funda Yildirim is an Assistant Professor at the Digital Society Institute and the Cognition, Data and Education department, focusing on interdisciplinary research at the intersection of technology, cognition, and societal impact. With an ORCID ID of 0000-0003-4310-809X and an h-index of 41, her work spans virtual reality, cognitive neuroscience, and machine learning. She actively contributes to global initiatives like the UN Sustainable Development Goals (SDGs) through expertise in environmental resilience and human-AI interaction. Co-founder of the Open Behavioral Architecture network Chair in the European Innovation Council (2022) Chair in European Cooperation in Science and Technology (COST) (2021–2025) Her research explores how virtual reality and AI can address misinformation, sensory perception anomalies, and neurological diagnostics. Recent publications highlight her work on: VR-based climate change education Emotion-specific attention patterns Sensory integration in auditory perception AI-driven epilepsy diagnosis Human-robot interaction dynamics
Syed Muhammad Anwar serves as an Associate Professor in Software Engineering at the University of Engineering and Technology (UET) Taxila, Pakistan. He maintains a significant dual affiliation with the Sheikh Zayed Institute at Children's National Hospital in Washington, DC, USA. Additionally, he holds leadership roles as Co-founder and CTO of Sense Digital PVT. Ltd. and Director of both the Virtual Reality and Machine Learning Lab and the Signal Image Multimedia Processing and Learning (SIMPLE) Group at UET Taxila. Dr. Anwar's research spans multiple cutting-edge domains at the intersection of signal processing, machine learning, and medical applications. His primary research interests include: Multimedia Communication and Signal Processing Image and Video Coding and Quality Assessment Biomedical Signal Processing and Brain-Computer Interfaces Medical Imaging including Segmentation, Detection, and Diagnosis Deep Learning applications in healthcare diagnostics Emotion Classification and Human Behavior Modeling His recent scholarly output demonstrates a strong emphasis on applying deep learning techniques to medical image analysis challenges, particularly in brain tumor segmentation, liver tumor detection, and Alzheimer's disease classification. There's also significant work in EEG-based applications including emotion recognition, stress quantification, and game expertise classification. His research effectively bridges theoretical machine learning advances with practical healthcare applications, showing particular strength in adapting deep learning architectures to medical imaging challenges across multiple organ systems. Dr. Anwar actively mentors the next generation of researchers through his leadership of the SIMPLE research group. His current advisees include: PhD Students: Sanay Muhammad Umar Saeed (Quantification of human stress), Romana Farhan (Security in body area networks), Nosheen Sohail (Medical Image Analysis), Amin Ullah (Knowledge extraction), and Saqib Mehboob (Structural health monitoring) MS Students: Haseeb Iftikhar (Doctor recommender system), Faizah Malik (Sentiment analysis), Samreena Aslam (Fashion image retrieval), Huma Shabbir (Fashion image tagging), Khola Rafiq (Ischemic stroke detection), and Saba Naseem (Blood vessel segmentation) As Director of the Virtual Reality and Machine Learning Lab and the SIMPLE research group, Dr. Anwar oversees a dynamic research environment focused on advancing signal processing, multimedia analysis, and machine learning applications, particularly in healthcare contexts. His lab maintains strong collaborations between UET Taxila and international institutions, including Children's National Hospital in Washington DC, facilitating technology transfer between academic research and clinical practice.
Pan Wang is an Assistant Professor at the Faculty of Industrial Design Engineering (IDE) at TU Delft. Her research focuses on AI for design, particularly Human-machine (AI) co-creativity, integrating human-computer interaction, brain-computer interfaces, and AI-driven creative processes. She developed the 'symbiotic creativity' framework, an interactive system enabling human-AI collaboration throughout creative workflows. Education: PhD from the Dyson School of Design Engineering and Data Science Institute at Imperial College London. Research emphases include generative AI, brain-computer interfaces, and AI-generated artworks. She explores innovative methods for human-AI interaction in design contexts. Publications (2024–2025) highlight advancements in AI-co-creation tools, generative models for typography, and evaluation frameworks for AI art. Current work addresses interdisciplinary applications of AI in creative industries. No secondary employment declared (2023–2026). Teaches research modules (3 & 5 ECTS) at IDE, contributing to both academic and applied design education.
Bruno Ehrler is a Professor at the University of Groningen (honorary) and Group Leader of the Hybrid Solar Cells Group at AMOLF in Amsterdam since 2014. His research focuses on perovskite materials science, including fundamental studies and device applications like solar cells. He holds significant grants (ERC Starting, NWO Vidi) and is a WIN Rising Star award recipient. He previously worked at the University of Cambridge, where he earned his PhD in Physics under Prof. Neil Greenham. His expertise spans optoelectronics, quantum dots, and singlet fission photovoltaics. Ehrler contributes to national energy initiatives and serves on advisory boards for the Dutch Chemistry Council and nanoGe conferences. Education: PhD in Physics, University of Cambridge (2009–2012) MSci in Physics, University of London (Queen Mary College, 2005–2009) Studies at RWTH Aachen and University of London Research Interests: Perovskite materials, solar cell efficiency, ion migration dynamics, photonic materials, and sustainable energy technologies. His work bridges fundamental material science with applied device engineering, addressing challenges in scalability, stability, and energy conversion efficiency. Grants & Awards: ERC Starting Grant (2020): Artificial synapses from halide perovskites NWO Vidi Grant (2017): Metal halide perovskites WIN Rising Star Award (2018) Advising & Labs: Leads the Hybrid Solar Cells Group at AMOLF, focusing on perovskite innovation. Collaborates on national energy projects like the Netherlands Energy Research Alliance (NERA). Active in mentoring early-career researchers through advisory roles and grant programs.
Wolfgang Hürst is an Associate Professor at Utrecht University's Department of Information and Computing Sciences, where he also serves as program leader for the MSc in Game & Media Technology. Previously, he was Education Director of the department from 2020-2024. His research focuses on immersive technologies including augmented/virtual reality, human-computer interaction, and multimedia systems, with applications in gaming, healthcare, and neuroscience. Education includes: PhD in Computer Science from University of Freiburg, Germany Master's in Computer Science from University of Karlsruhe/KIT Visiting researcher at Carnegie Mellon University (1996-1997) Postdoctoral work at University of Freiburg (2005-2007) Research interests span virtual/augmented reality systems, mobile interaction design, multimedia methods, and gaming technology. His work explores how immersive technologies can enhance human perception, information visualization, and accessibility in domains ranging from neuroscience research to cultural heritage preservation. Publications demonstrate strong focus on AR/VR interface innovation, particularly in 360° video interaction, lifelog visualization, and neuroscience applications. Recent work emphasizes ethical AI integration in extended reality and inclusive design for diverse user populations. Research consistently combines technical development with rigorous human-centered evaluation methodologies. Scientific awards: No major awards reported in provided materials. Research involves collaborations through the Game Research group and Applied Data Science initiatives. Current projects include immersive literature exploration tools for neuroscientists and accessible VR museum experiences. Extramural funding sources not detailed in available documentation.
Maria Carla Piastra is an Assistant Professor in Clinical Neurophysiology, specializing in neuroimaging and computational neuroscience. Her work focuses on advancing EEG and MEG methodologies, particularly in validating volume conduction models and analyzing neurological disorders like absence seizures. She explores how CSF-filled cavities impact EEG accuracy and develops automated quality control protocols for neuroimaging data. Her research aligns with UN Sustainable Development Goals, contributing to innovations in healthcare diagnostics. She collaborates internationally on neurophysiological studies, with notable contributions to understanding visual attention dynamics during seizures and improving clinical neurophysiology practices.
Dr. Giulio Mecacci is an Associate Professor at the Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen. His research focuses on ethical, legal, and societal implications of AI and neurotechnologies, particularly operationalizing the concept of Meaningful Human Control to address responsibility gaps in human-AI interaction. He holds academic appointments at the Donders Centre for Cognition and the Donders Institute. Teaching responsibilities include courses on AI ethics, societal impacts of AI, and Neurophilosophy within the CNS master’s programme. He actively promotes dialogue between science, technology, and society through education. Recipient of the 2021 Education Award from the Faculty of Social Sciences, his work bridges applied ethics with technological development. His research outputs span AI governance frameworks, neurotechnology ethics, and responsibility gaps in autonomous systems.
Clemens Dirven is a Full Professor at Erasmus MC, Department of Neurosurgery, where he leads significant research and clinical work in neuro-oncology and brain surgery. His academic and clinical roles place him at the forefront of translational neuroscience and surgical innovation. His research interests include glioblastoma , ganglioglioma , craniotomy , brain surgery , and oncolytic virotherapy . He is particularly active in studies involving tumor immunology, functional brain imaging, and improving patient outcomes through innovative interventions such as music therapy for delirium prevention. His work bridges clinical neurosurgery with molecular and immunological research. The recent articles highlight a strong trend toward integrating advanced technologies like functional ultrasound for brain imaging, evaluating immunological responses in glioblastoma, and assessing healthcare quality and cost-effectiveness in neurosurgical care. His publications span high-impact journals in neurosurgery, oncology, and molecular medicine, reflecting a multidisciplinary approach to treating brain tumors. While no specific scientific awards are mentioned in the provided text, his extensive publication record and leadership in major clinical and translational studies suggest significant recognition in the field. Prof. Dirven has supervised at least 19 research projects, indicating a strong commitment to mentoring and academic training. Although no grants are explicitly listed, his involvement in multi-center trials and advanced research implies ongoing funding support. His collaborations span diverse institutions and disciplines, particularly in neuro-oncology and biomedical engineering. He is actively involved in research networks focusing on brain tumor biology, neuroimaging, and surgical outcomes. His team collaborates with experts in virology, immunology, and biomedical engineering, contributing to a robust interdisciplinary research environment at Erasmus MC.
Catherine Sibert is a faculty member at the University of Groningen, affiliated with the Faculty of Science and Engineering in the Department of Artificial Intelligence. She holds the academic rank of Assistant Professor and is actively engaged in interdisciplinary research bridging cognitive science, neuroscience, and artificial intelligence. Her research interests include cognitive architecture, decision-making, neuroimaging, causal modeling, and brain activity, with a strong emphasis on data-driven approaches. She applies methods such as Granger causality and dynamic causal modeling to analyze multitask neuroimaging data and understand the neural underpinnings of cognition. The recent publications of Catherine Sibert demonstrate a consistent focus on modeling cognitive processes, particularly in decision-making and motor control, using computational and neuroimaging techniques. Her work often explores individual differences and the interaction between episodic and procedural memory systems. She collaborates with researchers such as Andrea Stocco and Hake H.S., contributing to high-impact journals like Topics in Cognitive Science and Frontiers in Neuroscience . Her research output is peer-reviewed, open access, and widely shared in academic networks. Decision Making Cognitive Architecture Neuroimaging Resting-State Networks Speech Motor Control Data-driven Modeling Catherine Sibert has no listed scientific awards in the provided text. She does not appear to have formal advisees listed, and there is no mention of grants or teaching responsibilities. However, her active publication record suggests ongoing research and collaboration within cognitive neuroscience and AI. She is associated with a research lab or team focused on cognitive modeling and neuroimaging, likely collaborating within the Artificial Intelligence department on projects involving brain-computer interfaces, cognitive systems, and computational modeling of human behavior.
Maryam Alimardani is a researcher at Tilburg University's School of Humanities and Digital Sciences, Department of Cognitive Science and AI. She holds a Hospitality Contract position focusing on cutting-edge neurotechnology research. Her work contributes to UN Sustainable Development Goals related to innovation and infrastructure. Research Interests: Brain-Computer Interfaces (BCI) for human-machine interaction Virtual Reality (VR) applications in training and neurocognitive assessment EEG-based neural pattern analysis Passive BCI systems for workload prediction Gender differences in neurophysiological responses Recent Work Trends: Recent publications (2021-2024) emphasize BCI integration with VR environments, particularly in aviation training contexts. She explores gamification principles for optimizing BCI training protocols and investigates neurophysiological markers like mu rhythm suppression to improve BCI performance. Grant/Project Leadership: Principal Investigator on the Assessment and Enhancement of Pilot Training in VR using Neuro-cognitive Indicators of Learning project. Labs/Teams: Collaborates with multidisciplinary teams in aviation human factors and neuroergonomics, contributing to datasets like Psychological and Cognitive Factors in Motor Imagery BCI and Neural responses with EEG to climate change images .
Elena Nuñez Castellar is an Assistant Professor in the Human-Technology Interaction group at Eindhoven University of Technology. Her research focuses on human factors in AI-driven systems, examining cognitive abilities, attention dynamics, and ethical considerations for responsible AI design. She bridges disciplines including psychology, neuroscience, and engineering to address challenges in human oversight of AI systems. Education : Ph.D. in Psychology from Ghent University (2011), graduate degree from National University of Colombia. Affiliations : Imec (former postdoctoral researcher), European Research Council (AI mapping projects), Belgian ethical committee for AI tools. Her work integrates three pillars: (1) EEG and AI-driven technologies like BCIs, (2) network-neuroscience analysis of attentional demands in AI interactions, and (3) ethical frameworks for AI regulation under the EU-AI Act. She emphasizes real-world AI applications that balance innovation with human wellbeing.
Prof. Jelmer Borst is an Associate Professor in Computational Cognitive Neuroscience at the University of Groningen's Faculty of Science and Engineering, affiliated with the Artificial Intelligence department within the Bernoulli Institute. His research focuses on integrating computational models with neuroimaging data to understand cognitive processes like multitasking, working memory, and decision-making. He advises three PhD candidates and collaborates internationally on projects involving EEG/fMRI analysis and cognitive modeling frameworks such as ACT-R and Nengo. Research Interests: Neuroimaging analysis methods, cognitive bottlenecks in multitasking, memory retrieval localization, and adaptive learning systems. Key Projects: Developed the PREDICTOR tool for semi-automated driving response timing, and advanced models linking symbolic process stages to brain activity via MEG/EEG. Recent work includes large-scale evaluations of adaptive learning systems and interventions to mitigate mind-wandering in driving scenarios. He has received the Allen Newell Best Student-led Paper Award (2021) for contributions to cold-start adaptive learning research. His research group maintains active collaborations on datasets involving working memory, decision-making, and cognitive architecture validation through neuroimaging experiments. He also contributes to open-source tools for cognitive modeling and neuroimaging analysis.
