جست‌وجوی استاد و پژوهشگر

Dimo Ivanovمشاهده پروفایل

استادیار

• Ultra-high field MRI
• Quantitative MRI techniques
• Brain microstructure imaging
• +۷ مورد دیگر

Dr. Dimo Ivanov is an Assistant Professor at the Department of Cognitive Neuroscience at Maastricht University in the Netherlands. Since 2025, he has also served as Head of the 7 Tesla MR Core structure at the Cooperative Brain Imaging Center and as an Independent Research Group Leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt, Germany. His work bridges physics, neuroscience, and advanced imaging technology. Dr. Ivanov earned his PhD (Dr. rer. nat.) in Physics from the University of Leipzig/Max Planck Institute for Human Cognitive and Brain Sciences in 2012, followed by an M.Sc. in Physics from the International Physics Studies Program at the University of Leipzig in 2007. His educational foundation was completed with studies at the Foreign Language High School in Pleven, Bulgaria. Dr. Ivanov specializes in high-resolution structural, perfusion, and functional mapping of the human cortex and subcortical regions. His research focuses on quantitative MRI techniques to assess tissue vascularization, microstructure, myelination, and iron content. He develops advanced MRI sequences and analysis pipelines for both 7T and 3T systems, with translational applications in neurodegenerative disorders, psychiatric conditions, and neurodevelopmental studies. His work on resting-state and task-based fMRI provides critical insights into neural connectivity and brain dynamics. His publication record demonstrates consistent contributions to ultra-high field MRI methodology, with emphasis on 7T and 9.4T systems. His research spans technical MRI development, quantitative imaging methods, and clinical applications across multiple neurological conditions. Recent work shows increasing focus on translational applications connecting advanced imaging techniques with clinical outcomes. Dr. Ivanov has received numerous scientific awards and successfully secured competitive funding: ERC Marie Curie Program (2023) - 2-year postdoc position Maastricht University-Chinese Science Council PhD Program (2022) Maastricht University Center for Integrative Neuroscience PhD Program (2022) Magnetic Resonance in Medicine issue cover (2017) ISMRM merit award magna cum laude (2013) Trainee abstract travel award from the Organization for Human Brain Mapping (2011) Educational Stipends from the International Society for Magnetic Resonance in Medicine (2009-2011) Dr. Ivanov has successfully mentored postdoctoral researchers and PhD students through competitive funding mechanisms. His research group at the Max Planck Institute for Empirical Aesthetics and his position at Maastricht University support a collaborative environment that bridges physics, neuroscience, and clinical applications. His work with the 7 Tesla MR Core structure provides critical infrastructure for advanced neuroimaging research in Frankfurt. Dr. Ivanov leads the Structural and Physiological Imaging with High-Field MRI research group at the Max Planck Institute for Empirical Aesthetics. His team specializes in pushing the boundaries of ultra-high field MRI technology, developing novel acquisition and analysis methods that enable unprecedented insights into brain structure and function. The group maintains strong collaborations with multiple institutions across Europe and beyond.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Bo Wang is an active academic researcher primarily affiliated with multiple Chinese institutions, with strong connections to Tsinghua University, Beijing Jiaotong University, and other leading Chinese universities. His research spans artificial intelligence, machine learning, computer vision, medical image analysis, and intelligent control systems, demonstrating significant interdisciplinary work across computer science, engineering, and biomedical applications. Primary institutional affiliation: School of Computer Science and Technology at multiple Chinese universities Active research areas: AI/ML applications in healthcare, computer vision, federated learning, and intelligent control systems Extensive publication record across top-tier venues in multiple disciplines Wang's research interests focus on the intersection of artificial intelligence and practical applications. His work demonstrates strong expertise in developing novel machine learning architectures for medical image analysis, including applications in CT imaging, MRI, and sperm tracking. He has made significant contributions to federated learning approaches for large language models, sliding mode control systems, and molecular optimization frameworks. His research consistently bridges theoretical advances with practical implementations across healthcare, manufacturing, and environmental monitoring domains. Analysis of Wang's recent publications reveals a strong trend toward interdisciplinary AI applications, particularly in medical imaging and bioinformatics. His work on VAE-GANMDA for microbe-drug association prediction, ACE-QSM for accelerating MRI acquisition, and text-guided molecular optimization demonstrates innovative approaches at the intersection of AI and life sciences. Wang also maintains active research in industrial applications including digital twin technology for energy systems and robust scheduling approaches for multi-factory production. Notable research contributions include: FLFT: A Large-Scale Pre-Training Model Distributed Fine-Tuning Method with Federated Learning VAE-GANMDA: Microbe-drug association prediction model ACE-QSM: Accelerating quantitative susceptibility mapping using diffusion models Digital twin-empowered power consumption prediction systems Wang actively collaborates with researchers across China and internationally, with publications spanning computer science, engineering, medical imaging, and environmental science journals. His work demonstrates strong technical depth across multiple AI methodologies while maintaining focus on practical applications that address real-world challenges in healthcare, manufacturing, and environmental monitoring.

• Human-Computer Interaction
• Accessibility
• AI and Machine Learning
• +۳ مورد دیگر

Leah Findlater is a Professor at the University of Washington , Seattle, WA, USA. Her research focuses on Human-Computer Interaction (HCI) and Accessibility , particularly in developing AI and Machine Learning systems for users with disabilities. Key areas: Assistive Technologies , Speech Recognition , Visual Privacy Collaborators: Jon E. Froehlich, Dhruv Jain, Emma J. McDonnell, Abigale Stangl Her recent work includes sound personalization for Deaf users , AI-driven sign language generation , and privacy tools for blind individuals . She explores interactive machine learning and user-centered design to improve accessibility in smartwatches , AR , and generative AI . Articles highlight cross-disciplinary collaborations with disability communities , focusing on inclusive AI , sensory augmentation , and ethical technology design . She advocates for user-driven accessibility solutions in social media and urban environments .

Angela D. Friedericiمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Neuroscience
• Language Processing
• +۴ مورد دیگر

Professor Angela D. Friederici is a leading cognitive neuroscientist and Director of the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. She holds honorary professorships at the University of Leipzig, University of Potsdam, and Charité University Medicine Berlin. Her work focuses on the neural basis of language processing, syntax, and developmental cognitive neuroscience. Friederici has published over 500 peer-reviewed papers and received numerous accolades, including the APS William James Fellow Award (2023) and the Huttenlocher Award (2021). Education: PhD in Linguistics (1976, University of Bonn), Habilitation in Psychology (1986, Justus Liebig University Giessen). Affiliations: Founding Director of the Max Planck Institute for Human Cognitive and Brain Sciences since 1994. Served as Vice-President of the Max Planck Society (2014–2020). Research Interests: Evolution of language networks, syntax processing, neuroanatomical correlates of language, and developmental trajectories of cognitive abilities. Awards: Includes Leibniz Prize (1997), Wilhelm Wundt Medal (2018), and Gauss Medal (2011). Her recent work explores the neural underpinnings of syntax in humans and primates, with studies on chimpanzee communication and cross-linguistic brain plasticity. Friederici has pioneered methods in neuroimaging and electrophysiology to dissect language networks.

• Fuzzy Set Theory
• Fractional Calculus
• Mathematical Inequalities
• +۶ مورد دیگر

Muhammad Bilal Khan is an Assistant Professor at the Department of Electronics and Power Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology (NUST), Pakistan. His research spans mathematical theory and practical applications in wireless communication sensing technology. His primary research interests include Fuzzy Set Theory , Fractional Calculus , Mathematical Inequalities , and RF Sensing Applications in healthcare. His theoretical work focuses on developing new mathematical frameworks for fuzzy-number valued functions, particularly exploring pre-invexity, harmonic convexity, and related integral inequalities. On the applied side, he has made significant contributions to non-contact health monitoring systems using software-defined radio technology for detecting conditions like text neck syndrome, spinal curvature disorders, and breathing abnormalities. Analysis of his 15 most recent publications reveals a dual research trajectory: approximately 60% focus on theoretical mathematical contributions in fuzzy analysis and integral inequalities, while 40% address practical applications of wireless sensing in healthcare. His mathematical work frequently appears in journals like Axioms and Symmetry , while his applied research is published in venues including IEEE Access and Sensors . His notable scientific contributions include developing novel frameworks for (q 1 , q 2 )-Linear Diophantine Fuzzy Sets and advancing the theory of Diamond Intuitionistic Fuzzy Sets. His healthcare applications research has pioneered non-invasive monitoring techniques using RF sensing for elderly fall detection, text neck syndrome diagnosis, and breathing pattern analysis. Dr. Khan maintains active collaborations with researchers across multiple institutions, particularly working with Mohamed S. Soliman (13 joint publications), Muhammad Aslam Noor (12 publications), and Savin Treanta (8 publications) on mathematical theory, while collaborating with Najah AbuAli, Mubashir Rehman, and Xiaodong Yang on healthcare sensing applications.

• Virtual Reality (VR)
• Human-Computer Interaction (HCI)
• Accessibility in Technology
• +۳ مورد دیگر

John Quarles is a Professor at the University of Texas at San Antonio, specializing in Virtual Reality (VR) and Human-Computer Interaction. His research focuses on accessibility in immersive technologies, cybersickness mitigation, and inclusive design. He has contributed over 100 publications across top venues like IEEE VR, ISMAR, and IEEE Transactions on Visualization and Computer Graphics. His work addresses challenges faced by users with disabilities, such as balance impairments and mobility limitations, through innovative feedback systems and adaptive algorithms. Quarles has co-authored influential papers on cybersickness prediction, VR accessibility for persons with Multiple Sclerosis, and disability simulations to reduce societal bias. He has held leadership roles including Program Chair for IEEE VR 2023, demonstrating his influence in academic and industrial VR communities. His research spans interdisciplinary applications in healthcare, education, and rehabilitation, with notable collaborations on datasets like 'Mazed and Confused' and frameworks like SmoothRide. Key themes include multimodal feedback methods, user-centric design principles, and leveraging AI for personalized VR experiences.

Jan Alexanderssonمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Affective Computing
• Natural Language Processing
• +۴ مورد دیگر

Jan Alexandersson is a Researcher at the German Research Center for Artificial Intelligence (DFKI) in Saarbrücken, Germany, where he leads work in the Cognitive Assistance Systems group. His research bridges artificial intelligence and healthcare, focusing on developing multimodal systems for therapeutic applications and medical diagnostics. His core research interests include Affective Computing , Natural Language Processing , and Human-Computer Interaction , with specialization in emotion recognition, motivational interviewing analysis, and engagement estimation. Current projects explore AI applications for mental health support, pediatric therapy, and medical diagnostics through interdisciplinary collaborations. Recent publications reveal a strong trend toward multimodal AI architectures integrating linguistic, visual, and behavioral data. His 2024 work demonstrates increasing adoption of large language models for clinical applications, particularly in emotion regulation strategy identification and therapeutic dialogue analysis across diverse healthcare contexts. Dr. Alexandersson actively contributes to major initiatives including MULTI-IMMERSE (virtual reality therapy for hospitalized children), GAIN (Georgian AI networking), AI@Home (elderly care risk prediction), Kitatta (corneal transplant quality assessment), and MePheSTO (digital phenotyping for psychiatric disorders). These projects collectively focus on translating AI research into practical healthcare solutions through sensor integration, behavioral modeling, and clinical validation.

Santiago Berrezuetaمشاهده پروفایل

مدرس

• Virtual Reality
• Augmented Reality
• eXtended Reality
• +۷ مورد دیگر

Santiago Berrezueta is a Lecturer at the School of Computation, Information and Technology within Technical University of Munich (TUM). He actively contributes to research in Virtual Reality , Artificial Intelligence , and Robotic Assistance , with a focus on applications in Education and Healthcare . 2025 : 10 publications in VR, robotics, and AI ethics. 2024 : 4 co-authored studies on ChatGPT in ADHD therapy and collaborative learning. His research intersects Interactive Learning and Computer Vision , particularly in ADHD treatment , Language disorder detection , and VR-based education . He supervises Bachelor’s/Master’s theses on topics like gaze-based interaction, collaborative VR workflows, and AI-driven therapeutic tools. 2025: Excellent Paper Award at International Symposium on Educational Technology (ISET 2025) 2024: Best Presentation Award at International Conference in Intelligent Environments (IE 2024) He leads courses on Software Engineering and Programming Fundamentals at TUM’s Heilbronn campus. His work also explores IoT applications and ethical AI in vulnerable populations.

Tobias Dörflerمشاهده پروفایل

استاد

• Educational-Psychological Diagnostics
• Self-Regulated Learning
• Teacher Education
• +۴ مورد دیگر

Prof. Dr. Tobias Dörfler is W3 Professor for Educational-Psychological Diagnostics at Heidelberg University of Education, serving as Scientific Director of the university's Test Library. He holds key administrative roles including Vice Dean of the Faculty of Education and Social Sciences, member of the Board of Directors of Heidelberg School of Education, and head of the DiaKom research group. Education: Dipl.-Psych. in Psychology and Human Medicine (minor) - University of Leipzig (1996-1997) Diploma in Biochemistry - University of Leipzig (1996-1997) Dr. phil. - RWTH Aachen University (2004) Research Focus: Professor Dörfler's research centers on educational-psychological diagnostics, with particular emphasis on self-regulated learning, assessment methods, and teacher education. His work integrates cognitive psychology principles with educational practice, focusing on developing diagnostic tools for educational settings and understanding learning processes in both typical and atypical development. Current Projects: He leads the DiaKom research group investigating diagnostic competencies in educational contexts. His research spans multiple domains including mathematical learning difficulties, reading and writing development, and the assessment of teacher professional knowledge through innovative methods like vignette-based assessments and eye-tracking studies. Scientific Contributions: Professor Dörfler has authored numerous publications in high-impact journals including Learning & Instruction , Journal of Educational Psychology , Frontiers in Psychology , and Journal for Mathematics Didactics . His recent work explores the intersection of stress, cognition, and educational assessment, as well as the development of diagnostic tools for language and learning disorders. Advising and Supervision: He currently supervises four doctoral students: Christina Ingelfinger, Nursin Karadeniz, Gina-Maria Trunte, and Irene Zemp. His mentorship extends to numerous former doctoral students and postdocs who have gone on to academic positions at institutions including University of Education Ludwigsburg, University of Tübingen, and University of Education Freiburg. Leadership Roles: Beyond his professorship, Professor Dörfler serves as Scientific Director of the Testothek (university test library), coordinates multiple educational modules, and sits on various university committees including doctoral committees and examination boards. He is actively involved in state-level educational initiatives in Baden-Württemberg.

Anne Jurkutatمشاهده پروفایل

مدرس ارشد

• Speech-Language Pathology
• Communication Disorders
• Voice Disorders
• +۵ مورد دیگر

Anne Jurkutat is a Senior Lecturer and Academic Councillor at the Chair of Pedagogy and Intervention for Language and Communication Impairments, Faculty of Human Sciences, Julius-Maximilians-Universität Würzburg. She manages the speech therapy outpatient clinic, leads voice disorder prevention programs for teachers, and serves as an Equal Opportunities Officer at the Institute for Special Education. PhD in Special Education (2011, University of Würzburg) MA in Special Education – Speech Therapy (2006, University of Würzburg) MSc in Human Communication Sciences (2002, University of Newcastle upon Tyne) Her research focuses on voice disorders in adults, phonological disorders in children, Glut1 deficiency syndrome speech impairments, and orofacial cleft-related language development. She investigates speech motor disorders in neurological conditions, diagnostic tools for childhood speech sound disorders, and interdisciplinary applications of music therapy. Recent publications highlight her work on Glut1-DS speech patterns, standardized diagnostic assessments, and early music-language interaction effects. She has collaborated on studies involving ketogenic diet impacts on cognitive profiles and interdisciplinary approaches to voice hygiene for teachers. 2009: Preis für gute Lehre (Prize for Good Teaching) at Bavarian State Universities Jurkutat supervises admission theses, contributes to state exams in special education, and integrates speech physiology into music pedagogy. She leads the STRONG VOICE MAKES SCHOOL project and applies mindfulness techniques in voice training for educators.

Andreas Bullingمشاهده پروفایل

استاد

• Human-Computer Interaction
• Computer Vision
• Ubiquitous Computing
• +۴ مورد دیگر

Prof. Dr. Andreas Bulling is Full Professor of Computer Science at the University of Stuttgart , leading the Collaborative Artificial Intelligence research group at the Institute for Visualization and Interactive Systems. He is also a founding director of the Stuttgart ELLIS Unit and serves on multiple prestigious boards including IEEE Transactions on Visualization and Computer Graphics . Education: MSc in Computer Science (KIT), PhD in Information Technology (ETH Zurich) Research Interests: Human-Computer Interaction, Eye Tracking, Wearable Computing, Computer Vision, and Privacy-Preserving AI Scientific Leadership: UbiComp Steering Committee member, ACM ETRA General Chair (2020), and extensive editorial/guest editor roles Key Awards: ERC Starting Grant (2018), Henriette Herz Scout (2024), and multiple best paper awards at CHI, ETRA, and UIST Technical Contributions: Developed datasets (LPW, VisRecall++), created novel methods for gaze estimation, mental face reconstruction, and saliency prediction in visualizations His work bridges AI and Human-Computer Interaction with applications in immersive systems and healthcare technologies.

Sascha Heinمشاهده پروفایل

استاد

• Emotional and Social Development
• Juvenile Delinquency
• Violence Prevention
• +۷ مورد دیگر

Sascha Hein is a Professor at Freie Universität Berlin, where he leads the research area on Emotional and Social Development in Childhood and Adolescence within the Department of Education and Psychology, specializing in Special Education. He previously served as Assistant Professor at the University of Houston and held postdoctoral positions at Yale University School of Medicine’s Child Study Center. His academic work spans developmental psychology, criminology, and education, with strong international collaborations. Ph.D. in Educational Sciences, Goethe-Universität Frankfurt am Main (2012) M.A. in Educational Science, Goethe-Universität Frankfurt am Main (2008) 1st State Examination in Special Education, Goethe-Universität Frankfurt am Main (2009) His research focuses on juvenile delinquency, emotional development, violence prevention, and the psychosocial development of refugee children. He investigates mental health disparities in justice-involved youth, parenting in marginalized communities, and social-emotional interventions. His work often employs longitudinal and experimental designs, particularly randomized controlled trials (RCTs), and spans diverse cultural contexts including the U.S., Lebanon, Colombia, Zambia, and Saudi Arabia. The 15 most recent publications reflect a strong trend in applied developmental science, particularly in justice-involved youth, early childhood in emergencies, and cross-cultural studies on parenting and cognitive development. Keywords include social-emotional learning, mental health, risk assessment, and intervention effectiveness. Subfields span forensic psychology, educational equity, autism, and psychobiology, highlighting his interdisciplinary approach. Scientific awards include: 2020 Norbert and Charlotte Rieger Award for Scientific Achievement (American Academy of Child and Adolescent Psychiatry) for research on parenting programs in Lebanon. He advises doctoral and early-career researchers and has secured funding for international projects, particularly in low- and middle-income countries. He has led systematic reviews and evaluations for organizations like ChildFund International. He is actively involved in editorial work, having co-edited a special issue on alternatives to RCTs in developmental research. He collaborates with global research teams, including at Yale, focusing on early childhood development, refugee wellbeing, and mental health interventions. He is affiliated with research teams working on: Early Childhood Development in Emergencies (ECDEiE) Social-Emotional Interventions for At-Risk Youth Cross-Cultural Parenting and Child Development Justice-Involved Youth and Mental Health

Hanna Ehlertمشاهده پروفایل

پژوهشگر

• Artificial Intelligence in Speech Therapy
• Dynamic Assessment
• Language Development Disorders
• +۴ مورد دیگر

Hanna Ehlert is a researcher at Leibniz University Hannover, affiliated with both the Institute for Special Education (Faculty of Philosophy) and the Institute for Information Processing (TNT/Phonomatics spin-off). Her work bridges artificial intelligence with speech therapy, focusing on automated diagnostics and dynamic assessment for child language development. PhD in Special Education (2020, Leibniz University Hannover) M.Sc. & B.Sc. in Speech and Language Therapy/Logopedics (HAWK Hildesheim) State-certified speech therapist (Hannover Medical School) Her research integrates: Artificial Intelligence in speech therapy Dynamic Assessment for multilingual children Language development disorders Voice disorder prevention Technology for inclusive education Key research projects include: TALC (Tool for Analyzing Language and Communication) Phonomatics spin-off AI-LIT (AI-supported Literacy Development)

• Developmental Psychology
• Perceptual-Motor Development
• Emotion Processing
• +۵ مورد دیگر

Prof. Dr. Gudrun Schwarzer is a leading researcher in developmental psychology at the Justus Liebig University Giessen , heading the Department of Developmental Psychology . Her work bridges perceptual, motor, and cognitive development in infancy and childhood through rigorous experimental paradigms. Key research themes include infant mental rotation, emotional granularity across lifespan, and cross-cultural developmental differences She leads projects A7 (visuospatial-motor development) and C3 (emotion categorization across populations) Current team includes Dr. Bianca Jovanovic, Dr. Daniela Bahn, PhD students Nikol Tsenkova and Tharanirakshita Asokan Her research investigates how early motor experiences shape visual processing, with groundbreaking work on: Object permanence in infants Emotion-face-word priming effects Developmental language disorder cognition Idiopathic clubfoot developmental impacts Publications span Child Development Perspectives , Frontiers in Psychology , and Journal of Experimental Child Psychology . Awards : Heinz Heckhausen Young Scientist Prize (DGPs). Collaborative networks extend to Max Planck Society, University of California, and cross-cultural studies in Cameroon.

Bianca van Kemenadeمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Neuroimaging
• Perception
• +۴ مورد دیگر

Prof. Bianca van Kemenade leads the Systems Neuroscience of Action and Perception (SNAP) Lab at Justus Liebig University Giessen's School of Medicine. Her research focuses on action-based predictions, self-generated vs externally generated stimuli distinction, and neural mechanisms in schizophrenia spectrum disorders. Investigates how actions shape sensory perception through predictive coding Examines cerebellar and cortical contributions to sensorimotor processing Develops interventions for schizophrenia using neuroimaging techniques Recent work analyzes BOLD responses during visual feedback processing (2022-2025), explores speech-gesture matching networks (2024), and compares discrete vs continuous action feedback (2021). The lab employs fMRI, TMS, and behavioral methods. Current team members include postdoc Gizem Yildiz , PhD student Juan Carlo Cabato , and research assistants Sirine Nouira and Viktoria Zizer .