جست‌وجوی استاد و پژوهشگر

Julia Huyckمشاهده پروفایل

دانشیار

• Auditory Perception
• Speech Processing
• Developmental Auditory Sciences
• +۳ مورد دیگر

Dr. Julia Huyck is an Associate Professor in the Speech Pathology and Audiology Program at Kent State University’s School of Health Sciences (College of Education, Health, and Human Services). She concurrently holds an Adjunct Assistant Professor role at Northeast Ohio Medical University (NEOMED), Department of Anatomy and Neurobiology, and is a member of NEOMED’s Hearing Research Group. She directs the Perception, Learning, and Individual Differences (PLAID) lab, focusing on auditory perception and cognitive development in adolescents. Her research explores speech comprehension immaturity in youth and mechanisms underlying perceptual learning. Dr. Huyck earned a B.S. in Communication Sciences and Disorders, M.A. in Learning Disabilities, and Ph.D. in Communications Sciences and Disorders from Northwestern University. Her work bridges clinical audiology, developmental neuroscience, and cognitive psychology. Her research portfolio includes over 15 peer-reviewed articles examining perceptual learning, speech processing in noise, and neurodevelopmental auditory functions. She collaborates across institutions on projects exploring cross-accent speech perception, sex differences in auditory tasks, and neuroplasticity in aging. No formal awards are listed, though her publications reflect sustained scholarly impact. Advising and grant details are not explicitly stated in available texts. She maintains affiliations with Kent State’s Center for Performing Arts and NEOMED’s Hearing Research Group. The PLAID lab actively investigates individual differences in perceptual abilities using behavioral and neuroimaging techniques.

Asli Ozgun-Kocaمشاهده پروفایل

استاد

• Mathematics Education
• Teacher Education
• Secondary Education
• +۷ مورد دیگر

Asli Ozgun-Koca is a Professor of Mathematics Education in the College of Education at Wayne State University. Her work spans teaching, research, and leadership in mathematics teacher education, with a focus on secondary and elementary levels. She is actively involved in national and state-funded initiatives to improve mathematics instruction and equity. B.S. in Mathematics Education, Hacettepe University, Turkiye (1993) M.S. in Mathematics, Middle East Technical University, Turkiye (1996) Ph.D. in Mathematics Education, The Ohio State University (2001) Dr. Ozgun-Koca's research centers on mathematics education, particularly the integration of technology in teaching, professional development for teachers, lesson study, and fostering mathematical knowledge for teaching. She emphasizes equitable practices and the use of real-world, interdisciplinary contexts to enhance learning. Her work explores how teachers analyze tasks and student work to improve instruction, especially in proportional reasoning and statistics. The recent publications and presentations reflect a strong trend in using technology (e.g., GeoGebra) to deepen conceptual understanding, designing integrated STEM and literature-based tasks, and improving feedback and task selection in teacher education. Her scholarship consistently addresses equity, teacher learning, and innovative pedagogies. President's Awards for Excellence in Teaching (2015) COE Faculty Research Award (2014) Career Development Chair Award (2013) Dr. Ozgun-Koca has secured major grants from the NSF and Michigan Department of Education, including SSTEPs, TeachDETROIT, and REALM projects, focusing on evidence-based pedagogies, teacher fellowships, and equity in mathematics education. She advises graduate students and collaborates widely on research. She teaches courses such as Methods and Materials of Instruction, Advanced Studies in Teaching Algebra and Statistics, and Detroit by the Numbers, reflecting her commitment to practical, context-rich teacher preparation. She is a key figure in lesson study adaptations for preservice teachers and leads professional development initiatives that connect theory and practice. Her work is disseminated through national conferences and leading journals in mathematics education.

Timothy McMahanمشاهده پروفایل

استادیار

• Adaptive Virtual Environments
• Neurogaming
• Virtual Reality
• +۷ مورد دیگر

Dr. Timothy McMahan is an Assistant Professor in the Department of Computer Science at the University of North Texas. His research focuses on adaptive virtual environments, neurogaming, and applying VR/AR technologies to neuropsychological assessment and training. He holds a Ph.D. in Computer Science (2016) and multiple advanced degrees from UNT. Education: Ph.D. Computer Science, University of North Texas (2014–2016) M.S. Computer Science, University of North Texas (2007–2013) B.S. Computer Science, University of North Texas (2003–2007) Postdoctorate in Computational Neuropsychology, University of North Texas (2016–2017) Research Interests: Adaptive VR environments for personalized user experiences Neurogaming applications in healthcare and education Machine learning for cognitive assessment and environmental adaptation EEG-based analysis of user engagement and cognitive workload VR tools for neuropsychological disorder diagnosis and treatment Recent work emphasizes VR applications in memory research, adaptive systems leveraging real-time ML predictions, and EEG-driven analyses of subjective experiences. Articles focus on bridging virtual and real-world interactions through computational neuroscience methods. No scientific awards or grants are explicitly listed in the provided materials. No advisees or lab affiliations are documented here.

Shenghua Gaoمشاهده پروفایل

دانشیار

• Spatio-temporal Data Analysis
• Machine Learning
• Database Systems
• +۴ مورد دیگر

Professor Shenghua Gao is an Associate Professor at the School of Computing and Data Science of the University of Hong Kong (HKU), concurrently serving as Assistant Director for Shanghai Initiatives. He holds a PhD from Nanyang Technological University. His research focuses on integrating machine learning, spatio-temporal data analysis, and database systems to address challenges in mobility prediction, traffic management, and geospatial representation learning. He has contributed significantly to trajectory modeling, indexing frameworks for multi-dimensional data, and the application of large language models (LLMs) in spatio-temporal contexts. Key research interests include: Spatio-Temporal Data Science: Developing frameworks for efficient processing and analysis of point cloud, trajectory, and traffic data. Machine Learning for Databases: Innovating indexing algorithms (e.g., BMTree, MAST) and query optimization techniques leveraging ML. Trajectory and Mobility Prediction: Creating personalized models for next-location prediction and transfer learning across regions. Geographic AI (GeoAI): Enhancing road network representation and urban function inference using physics-guided and foundation models. Recent work highlights include the ST-LLM+ framework for traffic prediction, the MAST system for point cloud analytics, and the exploration of City Foundation Models for urban challenges. His publications span top venues in databases (SIGMOD, VLDB) and AI/data science (ICML, NeurIPS). While no awards are explicitly mentioned, his prolific output and leadership roles indicate significant academic contributions. He is actively involved in teaching and supervising research in the School’s undergraduate and postgraduate programs, including MSc(AI) and MPhil/PhD tracks.

Elizabeth Byrneمشاهده پروفایل

مدرس

• Developmental Psychology
• Cognitive Development
• Working Memory
• +۶ مورد دیگر

Elizabeth Byrne is a Lecturer in Psychology at the University of East Anglia, affiliated with the School of Psychology and the Developmental Science research group. She is actively involved in research and supervises PhD students. PhD in Psychology, University of Cambridge (2014–2018) MRes Psychology (Distinction), University of Manchester (2012–2013) BSc (Hons) Psychology (First Class), University of Manchester (2008–2011) Her research focuses on cognitive and behavioral development in early childhood, particularly working memory, self-regulation, and the role of guided play in learning. She investigates how educational interventions and adult-child interactions shape developmental outcomes. Her recent publications highlight a strong trend in developmental and educational psychology, with an emphasis on psychometric validation, cognitive architecture, and evidence-based interventions. Key themes include guided play, behavioral assessment tools, and the use of physical manipulatives in learning. Elizabeth Byrne has contributed to impactful research widely covered in media and policy discussions, particularly her meta-analysis on guided play. Her work has been referenced in policy sources and highlighted across news outlets, blogs, and social media platforms. She collaborates with leading researchers such as Joni Holmes and Paul Ramchandani and leads an active British Academy-funded project on cognitive segmentation in problem solving. No formal grants beyond this are detailed, but her research output suggests sustained funding and collaboration. She has contributed to open datasets and engages in public outreach through press and media contributions, promoting evidence-based early education practices.

• Neurorehabilitation
• Clinical Biomechanics
• Parkinson's Disease
• +۷ مورد دیگر

Constanza Isabel San Martín Valenzuela is a researcher at the Universitat de València, affiliated with the Faculty of Physiotherapy and the Department of Physiotherapy, as well as the Department of Medicine. She is a member of the UBIC Research Unit in Clinical Biomechanics, focusing on clinical and biomechanical aspects of movement disorders. Her primary research interests lie in neurorehabilitation, particularly gait rehabilitation using dual-task training in patients with Parkinson’s disease. Her work integrates principles from physiotherapy, psychiatry, and clinical biomechanics to improve motor and cognitive function in neurodegenerative conditions. The available information does not include recent publications, preventing analysis of article trends. However, her doctoral research indicates a strong focus on evidence-based rehabilitation interventions and randomized controlled trials in movement disorders. There are no listed scientific awards or honors in the provided data. She completed her PhD under the supervision of Dr. María Pilar Serra Añó and Dr. Jose Manuel Tomás Miguel. There is no information available about students she may have supervised or grants she has led. Her research is conducted within the UBIC Research Unit in Clinical Biomechanics, which likely involves interdisciplinary collaboration in assessing and improving clinical outcomes through biomechanical analysis.

Máté Gyurkovicsمشاهده پروفایل

مدرس

• Cognitive Neuroscience
• Neural Oscillations
• Attention
• +۷ مورد دیگر

Máté Gyurkovics is a Lecturer in Psychology at the University of East Anglia's School of Psychology, appointed in August 2024. His academic background includes a PhD in Cognitive Psychology from the University of Sheffield (2020), followed by postdoctoral research at the University of Illinois at Urbana-Champaign and the University of Glasgow. Education: BSc/MSc in Psychology at Eötvös Loránd University, Hungary; PhD in Cognitive Psychology at University of Sheffield, UK Research Interests: Máté focuses on the neural oscillatory mechanisms of attention , combining EEG , MEG , and brain stimulation techniques like TMS. His work spans cognitive development (adolescence) and age-related cognitive changes in attentional control. Publication Trends: Recent work examines task difficulty effects on cognitive control, EEG aperiodic activity in attention, and genetic links between neural oscillations and neurodevelopmental disorders. Techniques include computational EEG analysis , longitudinal twin studies , and multimodal neuroimaging . Professional Roles: He serves on UEA's Ethics Committee and acts as a peer reviewer for the Psychophysiology journal. His expertise spans brain imaging , cognitive neuroscience , and perception/action research .

Joana Braga Pereiraمشاهده پروفایل

دانشیار

• Brain Connectivity
• Neurodegenerative Disorders
• Alzheimer's Disease
• +۱۱ مورد دیگر

Joana Braga Pereira is an Associate Professor (Docent in Neurosciences) and Principal Researcher at the Department of Clinical Neuroscience, Karolinska Institutet, where she leads the Brain Connectomics research group. Her work focuses on brain connectivity measures derived from structural MRI, functional MRI, diffusion tensor imaging, and other neuroimaging modalities in patients with neurodegenerative disorders. Education: Docent in Neurosciences, Karolinska Institutet, 2021 PhD in Biomedicine, University of Barcelona, 2012 Master in Neurosciences, University of Barcelona, 2008 Postdoctoral Fellow in Neuroimaging, Karolinska Institute, 2017 Dr. Pereira's research focuses on understanding brain connectivity and network topology in neurodegenerative disorders, particularly Alzheimer's and Parkinson's diseases. Her work integrates multiple neuroimaging modalities with biomarker analysis to identify early signs of disease and track progression. She specializes in applying graph theory, deep learning, and novel imaging sequences to analyze complex brain networks and develop precision medicine approaches. Her research spans multimodal brain connectivity, dynamic brain connectivity, functional gradients, and proteomics to understand disease mechanisms. Her recent publications demonstrate a strong focus on computational approaches to understanding neurodegenerative diseases, with particular emphasis on the relationship between brain connectivity patterns, biomarkers, and clinical outcomes across aging and various neurological conditions. She has pioneered methods like delayed correlation-based approaches for dynamic connectivity analysis and developed BRAPH 2.0 software for brain connectivity analysis. Scientific Awards and Grants: Marie Curie Intra-European Fellowship Swedish Research Council Alzheimerfonden Hjärnfonden StratNeuro New Technologies Grant 2025 Swedish Foundation for Strategic Research Senior Research Faculty Position Dr. Pereira actively mentors the next generation of neuroscientists, currently supervising 3 PhD students and 3 postdoctoral researchers, with additional co-supervision of 4 PhD students from other institutions. She has successfully guided 4 PhD students to completion of their theses. She also organizes the yearly conference 'Emerging Topics in Artificial Intelligence' since 2020. She leads the Brain Connectomics research group, which is part of the Department of Clinical Neuroscience at Karolinska Institutet. The group is highly interdisciplinary, combining expertise from medicine, engineering, physics, and computer science to tackle complex questions in neuroscience. The group has developed BRAPH 2.0, a comprehensive software for brain connectivity analysis using graph theory and deep learning.

Uwe Kerstingمشاهده پروفایل

استاد

• Biomechanics
• Orthopaedics
• Sports Injury Prevention
• +۷ مورد دیگر

Uwe Kersting is a full Professor at the Institute of Biomechanics and Orthopaedics, German Sport University Cologne. He is actively engaged in research, teaching, and supervision within the fields of sports biomechanics, orthopaedics, and injury prevention. His work spans multiple projects, collaborations, and publications, focusing on athlete safety and biomechanical analysis. Academic Rank: Professor Institution: German Sport University Cologne Department: Institute of Biomechanics and Orthopaedics Email: u.kersting@dshs-koeln.de Research Interests: Uwe Kersting's research is centered on biomechanics and orthopaedics, with a strong emphasis on injury mechanisms in athletes. His work investigates knee joint vulnerability, lower limb loading, muscle activity during dynamic tasks, and the development of wearable technologies for long-term monitoring. He applies 3D biomechanical analysis to understand unplanned movements in sports such as handball and snowboarding. Publication Trends: His recent publications (2023–2025) show a consistent focus on ACL injury prevention, joint loading in change-of-direction tasks, and the use of advanced modeling and measurement systems. Themes include EMG analysis, statistical shape modeling, shear force measurement, and real-time feedback in training. The research bridges clinical orthopaedics, sports science, and engineering. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: Prof. Kersting actively supervises PhD and master’s students, including Kevin Bill, Patrick May, and Jan-Peter Goldmann. He is the primary advisor on multiple doctoral theses. He leads and participates in externally funded and self-financed research projects such as LoStInCrowds and FeeTISH, which focus on injury risk in crowded environments and snowboarding technique, respectively. Labs and Teams: He is a core member of the Institute of Biomechanics and Orthopaedics, collaborating with researchers like Steffen Willwacher (formerly), Cynthia Fantini Pagani, and Jasper Kwasny. His team conducts lab-based and field biomechanical studies involving motion capture, force plates, and wearable sensors.

Nele Wild-Wallمشاهده پروفایل

استاد

• Cognitive Psychology
• Neuropsychology
• Geropsychology
• +۱۸ مورد دیگر

Prof. Dr. Nele Wild-Wall is a Professor of Research Methods and Diagnostics in Psychology at the Faculty of Communication and Environment, Rhine-Waal University of Applied Sciences. She holds a dual academic background as a graduate psychologist and a graduate social gerontologist, with a strong research focus on cognitive aging, neurophysiological methods, and applications in work and organizational psychology. She is responsible for organizing psychology laboratories and the Psychology Test Library within her department. Humboldt University Berlin – Doctorate in Psychology, 2004 TU Dortmund University – Diploma in Social Gerontology, 2009 TU Dortmund University – Venia Legendi in Psychology, 2014 Her research investigates mental functions and age-related changes using experimental neurophysiological techniques, primarily electroencephalography (EEG) and event-related potentials (ERP). Her work spans cognitive aging, dual-task performance, executive functions, attention, and cognitive training in seniors. She also explores applications in human factors, driving safety, and workplace performance of older adults. Her most recent publications reflect a consistent focus on aging, cognition, and neurophysiological assessment, with research on dual-task performance, working memory, feedback processing, and cognitive flexibility. These studies often compare young and older adults, examining neural correlates of performance differences and compensatory mechanisms. While no scientific awards are explicitly mentioned in the provided text, her sustained publication record in high-impact journals and participation in national and international conferences indicate active scholarly engagement. Prof. Wild-Wall has collaborated extensively with researchers at the Leibniz Institute for Working Environment (IfADo) in Dortmund, particularly with Prof. Dr. Michael Falkenstein. Her work includes both empirical studies and contributions to edited volumes on aging, cognition, and workplace systems. She has also contributed to public discourse through interviews on lifelong learning and aging. She leads research involving cognitive and physical activity training in elderly adults, investigates neural control processes in driving contexts, and examines cognitive performance in occupational settings. Her interdisciplinary approach integrates psychology, neuroscience, and ergonomics to support healthy aging and optimal human-system interaction.

• New Product Development
• Service Innovation
• Project Management
• +۳ مورد دیگر

Tian Heong Chan is an Associate Professor at Emory University's Goizueta Business School in the Information Systems & Operations Management department. His research and teaching focus on new product/service development, team collaboration, and technology operations. Education: PhD in Technology and Operations Management, INSEAD MS in Management Science and Engineering, Stanford University BS in Mechanical Engineering, UC Berkeley His work investigates: Collaboration dynamics in diverse settings (product design, problem-solving, customer-supplier co-production) Novelty emergence in design processes (exaptation, computer vision similarity metrics) Team composition effects on invention value (expertise similarity, gender diversity, cohesion) Recent publications analyze: Exaptation in IKEA hacks Voting protocols in FDA advisory committees Style evolution in product design Free-rider problems in medical equipment maintenance

Hans van Dijkمشاهده پروفایل

پژوهشگر

• Biomedical Engineering
• Clinical Neurophysiology
• Electrophysiology
• +۷ مورد دیگر

Hans van Dijk serves as a Senior Researcher in the Signal Processing Systems group within the Department of Electrical Engineering at Eindhoven University of Technology. He simultaneously holds leadership and research positions at multiple institutions, heading the Clinical Physics department at Kempenhaeghe (an institute specializing in Epileptology and Sleep medicine) and working as a Senior Researcher at the University Hospital in Ulm, Germany. His multidisciplinary career bridges engineering, clinical neurophysiology, and sleep medicine. Dr. van Dijk's research focuses on biomedical engineering applications in Clinical Neurophysiology, with particular expertise in electrophysiological techniques including EEG, EMG, and ECG. His work centers on developing and applying signal processing methods to diagnose neurological disorders, with specific emphasis on seizure detection using EEG , High-Density EMG for facial and masticatory muscles , and alternative diagnostic methods for sleep disorders . His recent publications demonstrate a strong focus on applying machine learning techniques to sleep medicine and epilepsy monitoring. Analysis of Dr. van Dijk's recent publications (2021-2025) reveals a consistent research trajectory in developing advanced signal processing methods for clinical neurophysiology. His work spans three main domains: epilepsy monitoring and seizure detection (particularly in children), sleep disorder diagnostics (using multimodal approaches beyond traditional polysomnography), and advanced EMG techniques for motor unit analysis. His research increasingly incorporates deep learning and multi-modal sensor fusion approaches to improve diagnostic accuracy while reducing the invasiveness of monitoring procedures. 2699 citations according to Scopus metrics 101 research outputs documented in institutional repository Active research collaboration with Philips Research and Kempenhaeghe Contributions to UN Sustainable Development Goals through medical diagnostics research Dr. van Dijk supervises research activities with 8 documented supervised works, collaborating extensively with clinical and engineering researchers across multiple institutions. His research program integrates signal processing expertise with clinical needs in neurology and sleep medicine, developing practical solutions for monitoring and diagnosing neurological disorders. His work at Kempenhaeghe focuses on translating engineering innovations into clinical practice for epilepsy and sleep disorder patients.

• Neurophysiology
• Schizophrenia
• Addictiology
• +۶ مورد دیگر

Stéphane Potvin is a Full Professor at the Department of Psychiatry and Addictionology, Faculty of Medicine, University of Montreal. He is affiliated with the Institute Universitaire en Santé Mentale de Montréal (CIUSSS de l'Est-de-l'Île-de-Montréal) and holds the Eli Lilly Canada Research Chair in Schizophrenia. His research focuses on neurophysiology , cannabis/alcohol effects on schizophrenia , and virtual reality therapy for psychiatric disorders. Key Research Themes Neuroimaging of reward and pain systems Cannabis and violence in mental illness Virtue-based interventions for substance use Forensic psychiatry applications Scientific Recognition Multiple CIHR and FRQS funding Winner of the 2013 Emmanuel Stip Prize Lead on 10+ research projects Academic Leadership Supervised 15+ graduate students Coordinated Neurobiology and Cognition research axis Contributed to 200+ peer-reviewed publications

Milica Todorovicمشاهده پروفایل

استاد مهمان

• Machine Learning
• Materials Science
• Quantum Mechanics
• +۶ مورد دیگر

Milica Todorovic is a Visiting Professor at Aalto University's Department of Applied Physics , leading machine learning research within the Computational Electronic Structure Theory (CEST) group. Her work bridges quantum mechanical simulations and machine learning algorithms to optimize material functionality, particularly for solar cell components and organic-inorganic interfaces . Research Interests include: Data-driven materials science Active learning for molecular datasets Bayesian optimization in atomic structure prediction Quantum simulations of surfaces and adsorbates Thermodynamic property modeling for atmospheric molecules Article Trends (2017-2025) show focus on machine learning applied to materials science , with subfields spanning bayesian optimization , conformational analysis , and density functional theory . Key collaborations include Patrick Rinke and Hanna Vehkamäki . Activities include organizing workshops like the Young Researcher’s Workshop on Machine Learning for Materials Science (2019) and International Workshop on Machine Learning for Materials Science (2018).

• Arabic Natural Language Processing
• Machine Translation
• Dialect Identification
• +۷ مورد دیگر

Ahmed Abdelali is a prominent researcher at Hamad Bin Khalifa University's Qatar Computing Research Institute (QCRI), where he works in the Arabic Language Technologies department. With 97 publications spanning from 2004 to 2024, he has established himself as a leading figure in Arabic natural language processing research. His work has been presented at major conferences including ACL, EMNLP, EACL, and specialized Arabic NLP venues. Dr. Abdelali's research focuses on several key areas within Arabic computational linguistics, with particular emphasis on Arabic language technologies. His work spans Arabic dialect identification, diacritization, machine translation, offensive language detection, and part-of-speech tagging. In recent years, he has been at the forefront of adapting large language models for Arabic language processing, contributing significantly to benchmarking frameworks like LAraBench and LLMeBench that evaluate Arabic language models' performance. His publication record shows consistent high-impact contributions, with notable collaborations with researchers including Hamdy Mubarak (45 co-authored papers), Kareem Darwish (38 co-authored papers), and Nadir Durrani (26 co-authored papers). Recent work has focused on large language models for Arabic, cross-lingual spaces, and benchmarking frameworks to advance Arabic AI capabilities. His research bridges theoretical advances with practical applications, particularly in processing the linguistic complexities of Arabic and its dialects. Through his leadership in developing resources like the Farasa segmenter and contributions to major Arabic NLP conferences, Dr. Abdelali has played a pivotal role in establishing the infrastructure and community for Arabic language technology research.