Markus Safar is a Researcher at the University of Applied Sciences Wiener Neustadt, specifically within the Institute of Computer Science in the Faculty of Technology. His work focuses on developing technology solutions for elderly care and wellbeing through innovative virtual coaching systems. His research interests include: Artificial Intelligence applications for elderly populations Human-Computer Interaction design for aging users Health Informatics systems Assistive Technology development Wellbeing promotion through digital solutions Physical activity monitoring systems Dr. Safar's work demonstrates a strong interdisciplinary approach that bridges computer science with gerontology and healthcare needs. His research emphasizes creating meaningful technological interventions that support healthy lifestyles for seniors during and beyond their working years. He has contributed to significant European research initiatives focused on improving quality of life for older adults through technology-enabled support systems. Contact information: Email: markus.safar@fhwn.ac.at Phone: +43/5/0421 1248 Location: Campus 1 Wiener Neustadt, Johannes Gutenberg-Straße 3, 2700 Wiener Neustadt
Moritz Grosse-Wentrup is a Professor at the Faculty of Computer Science, University of Vienna , where he leads the Neuroinformatics research group. His work spans neuroscience, machine learning, and brain-computer interfaces , focusing on causal modeling and neurotechnology. Location: Kolingasse 14-16, Room 02.49, 1090 Wien Email: moritz.grosse-wentrup@univie.ac.at Phone: +43-1-4277-79610 Research interests include: Developing causal frameworks to bridge neuronal activity and cognition Designing interpretable machine learning algorithms for BCI applications Neurorehabilitation using virtual reality and EMG-BCI systems Advancing causal inference and feature importance in AI models Open-source tools like PyTES for neurostimulation research Recent publications highlight trends in auditory BCI, causal recourse, and Riemannian geometry-based classification . His work integrates neuroscience, computer science, and clinical applications to improve communication for impaired patients and motor rehabilitation. Students mentored include Alex Markham (2021), Gunnar König (2023), and Jiachen Xu (2023). He teaches foundational courses in data analysis, signal processing, and neuroinformatics at the University of Vienna.
Ulrike Bechtold is a researcher at the Faculty of Life Sciences, Department of Evolutionary Anthropology. Her work spans human ecology, stressors, institutional care, and anthropogenic effects on biodiversity. Current Research: Focuses on Active Assisted Living (AAL) adoption barriers and modeling human-biodiversity interactions. Collaborations: Works with colleagues like M. Fieder, N. Stauder, and H. Wilfing on interdisciplinary projects. Her publications highlight trends in: Gerontechnology (2022-2024) Ecological modeling (2012-2024) Human-environment interactions (2006-2024)
Maria Teresa Guasti is a Professor of Linguistics and Psycholinguistics at the University of Milano-Bicocca since 2005. Her academic journey includes roles as Researcher at the University of Siena and San Raffaele Hospital, and Research Assistant at the University of Geneva. She holds a PhD from the University of Geneva, focusing on causatives and perception verbs, which remains influential in theoretical linguistics. Her research spans language acquisition , developmental language impairments , dyslexia , and cognitive aspects of language disorders . Notable contributions include discovering timing anticipation deficits in dyslexia and developing interactive technologies (VR/AR) for language applications. She has held visiting positions at MIT, Cambridge University, and Macquarie University. Guasti has authored/co-authored 160+ publications (80+ peer-reviewed articles, 6 books) with a Google Scholar H-index of 42. Major grants include an ERC Synergy Grant (€10.2M) and H2020 funding. She serves on editorial boards for Language Acquisition , Journal of Child Language , and others. Her advisory work includes supervising 14 PhD students, 12 postdocs, and ~100 Master's students. Awards include Foreign Expert status in Beijing and roles in EU-funded initiatives like COST A33 and Multimind. Current research integrates human-computer interaction with linguistic principles.
Maath Musleh is a Researcher and PhD candidate at the Vienna University of Technology (TU Wien), affiliated with the Faculty of Informatics and the Department of Computer Graphics. His academic roles include serving as a University Assistant and teaching courses such as Methods for Data Generation and Analytics in Medicine and Information Visualization . He holds a BSc and MSc, with his Master’s thesis focusing on industrial multivariate time series analysis. Research interests center on Visual Analytics , Medical Visualization , and Uncertainty Visualization , with applications in healthcare, manufacturing, and agriculture. His work emphasizes explainable AI, user confidence measurement, and decision-support systems. Notable contributions include the TrustME model for explainable guidance and the ConAn framework for quantifying user confidence in uncertain analysis scenarios. Key achievements include the Best Short Paper Award at VINCI 2021 for industrial time-series visualization research. His ongoing PhD, supervised by Prof. Renata Raidou, explores Guided Visual Analytics for Decision-Making under Uncertainty . He collaborates on projects like Agritology , a multilingual decision-support system for farmers, and has developed dashboards for industrial and medical data analysis. Maath’s interdisciplinary approach integrates visualization, machine learning, and human-centered design to address challenges in complex decision-making environments.
Rupert Lanzenberger is a Clinical Professor in Neurosciences at the Medical University of Vienna, where he has served as Director of the NeuroImaging Labs since 2021. He previously held roles as Associate Professor (2012-2021), Assistant Professor with habilitation (2010-2021), and Head of Neuroimaging Labs (2005-present). He chairs the WFSBP Task Force on NeuroImaging and serves on scientific committees including the ERC and Austrian Neuroscience Association. MD in Medicine (1998, Medical University of Vienna) Habilitation in Neurosciences (2010) His research focuses on translational molecular neuroimaging using PET/fMRI to study treatment effects in psychiatric and neurological disorders, particularly depression and ADHD. He develops predictive biomarkers and investigates serotonin/norepinephrine transporter dynamics. His work combines functional imaging with psychopharmacology to understand brain plasticity in mental health. Recent publications show expertise in multimodal imaging techniques (PET, fMRI, ultra-high field MRI) applied to psychiatric disorders, receptor dynamics (5-HT1A, NET, GluN2B), and treatment response modeling. His team's work appears in top journals like Molecular Psychiatry and JAMA Psychiatry. Worldwide top 1% Serotonin researcher (2021) European Academy of Sciences and Arts member (2019) ERC Consolidator Grant panel service Editorial board of NeuroImage and International Journal of Neuropsychopharmacology He supervises research teams and has established an international neuroimaging network with collaborations across >20 countries. The NeuroImaging Labs under his leadership conduct cutting-edge research in psychiatric biomarkers, with expertise in PET, MRI, EEG/TMS, and chemical imaging techniques.
Prof. Dr. Nassir Navab is a full professor and director of the Chair for Computer Aided Medical Procedures (CAMP) at the Technical University of Munich (TUM), Germany. He also serves as an adjunct professor of computer science at Johns Hopkins University (USA) and holds secondary appointments at TUM’s Medical School. He is internationally recognized for his pioneering work in computer-assisted interventions, augmented reality, medical imaging, computer vision, and machine learning. Education: PhD from INRIA and University of Paris XI, France Postdoctoral Fellowship at MIT Media Laboratory Research Interests: Prof. Navab's research bridges the gap between computer science and medicine. His core interests include: Robotic Imaging Systems : Developing robotic platforms for intraoperative imaging Augmented Reality in Surgery : Creating AR systems for surgical navigation Medical Image Computing : Advanced algorithms for medical image analysis Machine Learning in Healthcare : Deep learning applications in medical imaging Computer Vision : 3D reconstruction and scene understanding Research Trends: His recent publications demonstrate a strong focus on deep learning applications in medical imaging, particularly in 3D volumetric analysis, real-time surgical guidance systems, and automated diagnostic tools. The work spans from fundamental algorithm development to clinical translation, with significant contributions in areas like neural network architectures for medical image segmentation, pose estimation for robotic surgery, and augmented reality systems for intraoperative navigation. Scientific Awards: IEEE Fellow (2022) MICCAI Society Enduring Impact Award (2021) IEEE ISMAR 10 Year Lasting Impact Award (2015) Fellow of MICCAI Society (2012) SMIT Technology Award (2010) Siemens Inventor of the Year (2001) Over 50 best paper awards at international conferences Leadership & Service: General Chair: MICCAI 2015, ISMAR 2001/2005/2014 Founding Board Member: IPCAI (2010-2021) Editorial Board Member: IEEE TMI, MedIA Steering Committee Member: IEEE ISMAR (since 2001) Board of Directors: MICCAI Society (2007-2012, 2014-2017) Laboratories & Teams: Prof. Navab leads the Laboratories for Computer Aided Medical Procedures (CAMP) at TUM, a world-renowned research group focused on developing cutting-edge technologies for computer-assisted surgery and medical interventions. The lab has produced numerous award-winning PhD students who have gone on to become leaders in the field. He also directs the biannual Medical Augmented Reality school series at Balgrist Hospital in Zurich, Switzerland, which has become a premier educational event in the field.
Matteo Saveriano is an Assistant Professor at the University of Trento, focusing on integrating cognitive robotics into industrial and social environments through AI solutions inspired by human behavior. His research bridges robotics, AI, and human-robot interaction to enhance productivity in smart factories and assistive technologies. Research Focus His work centers on developing robotic systems capable of intuitive learning and safe interaction. Key areas include: Robotic skill acquisition via imitation learning Safe human-robot collaboration frameworks Variable impedance control systems Cognitive architectures for industrial automation Publication Trends Recent publications demonstrate interdisciplinary focus spanning clinical applications (dysphagia diagnostics, Parkinson's therapies), surgical robotics (vocal fold reconstruction), and fundamental biomechanics (tissue elasticity modeling). This reflects a translational research approach connecting engineering innovation with medical practice. Projects & Leadership He coordinates major EU initiatives including: INVERSE (Horizon Europe): Interactive robots learning tasks through reasoning MAGICIAN : Human-robot collaboration for defect detection ARIEL : Assistive robotics for elderly care
Honghai Liu is a Professor at the University of Portsmouth, UK, with a career spanning over two decades in interdisciplinary research at the intersection of physics, physiology, and biomedical engineering. His affiliations include prestigious institutions like the University of Aberdeen and King’s College London, and he is a member of the Institute of Electrical and Electronics Engineers (IEEE) and Institution of Engineering and Technology (IET). Research Interests: His work focuses on Autistic intervention Multi-modal sensing Medical devices and systems Human motion analytics Machine learning Intelligent robotics and control Stroke rehabilitation Recent publications highlight applications of biomedical engineering in stroke recovery analysis, autism screening protocols, and wearable sensor technology for muscle-computer interfaces. Scientific Awards: Fellow of IEEE (2020) Fellow of IET (2011) His research spans neuroscience, robotics, and control systems, with notable contributions to fatigue-sensitivity analysis and adaptive vehicle suspension technologies.
Donald Degraen is an Assistant Professor and Lecturer at the University of Canterbury, affiliated with the HIT Lab NZ, a leading research center in New Zealand. His work focuses on the intersection of haptics, fabrication, and virtual reality, with a particular emphasis on designing touch experiences and novel interaction methods. His research explores tools and techniques for generating tactile textures, sensory substitution for object detection, and collaborative haptic design. Donald’s research spans immersive technologies, including studies on virtual reality (VR) and augmented reality (AR) applications such as cycling exergames, wind-based haptic feedback, and eco-friendly gamification. He has contributed to frameworks for integrating smart devices into VR environments and enhancing tactile experiences through 3D-printed metamaterials. His work often bridges physical and digital realms, emphasizing sustainability and user-centered design. Key projects include TactStyle (generative AI for tactile textures), Spatial Haptics (sensory substitution methods), and Collaborative Haptic Experience Design (on-body vibrotactile patterns). Donald actively collaborates on interdisciplinary projects, leveraging his expertise in both technical and applied aspects of human-computer interaction. His research has been published in top-tier venues, with recent contributions exploring adaptive feedback systems, pseudo-force rendering in VR, and gamified eco-behavioral interventions. Donald is also involved in prototyping tools like AmbiPlant and Vrysmart, which aim to enhance real-world interactions through ambient and smart technology integration.
Essi Kujansuu is a Researcher at the University of Innsbruck, with affiliations at the University of Turku and the Institute of Replication (I4R). She holds a PhD in Economics from the European University Institute. Her work focuses on experimental economics, exploring themes like fairness, trust, moral behavior, and choice architecture. Recent research emphasizes meta-science and Open Science, particularly computational reproducibility and robustness analysis of published studies. Her experimental designs often involve real-effort tasks and real-time interaction platforms like oTree. Key contributions include analyzing wage rigidity in labor markets, the psychological impacts of wage cuts, and the effectiveness of nudges under transparency. She collaborates internationally on projects ranging from field experiments in credence goods to assessing reproducibility in quantitative social science through human-AI teams. Current projects include investigating how transparency affects nudge deployment by choice architects and comparing human vs AI-assisted methods in research reproducibility. She frequently contributes to replication efforts of high-impact studies in development and health economics. Her technical expertise spans experimental platform development (e.g., Django Channels integration) and advanced statistical methods for reproducibility analysis. Future work aims to bridge behavioral economics with modern computational tools, enhancing both theoretical understanding and practical applications of economic decision-making models.
Matthias Aulbach is a Postdoctoral Researcher at the Department of Clinical Psychology and Health Psychology at the University of Salzburg, working on the FWF project Cognitive Affective Mechanisms of Food Biases Trainings . He previously held Postdoctoral positions at the University of Helsinki and Aalto University and served as a Research Assistant at the University of Helsinki. Education: PhD in Social Psychology (University of Helsinki, 2016–2020); Diplom in Psychology (University of Würzburg, 2009–2014) His research focuses on computer- and smartphone-based interventions to modify unhealthy eating behavior and physical activity through behavioral retraining , combining Meta-Analysis , EEG , and Smartphone Data . He also explores ecological momentary assessment and applications of virtual reality in prejudice reduction . Current projects include analyzing cognitive-affective mechanisms of food biases and dietary self-regulation . His work addresses why individuals fail to act on their health intentions. He is affiliated with the Salzburg Eating Behavior Laboratory and collaborates on international research initiatives.
