جستجوی استاد راهنمای دانشگاهی

Eva Kaslikمشاهده پروفایل

استاد

• Fractional Calculus
• Dynamical Systems
• Neural Networks
• +۴ مورد دیگر

Eva Kaslik is a Professor at the Faculty of Mathematics and Computer Science, West University of Timisoara, Romania, with active research contributions in fractional-order dynamical systems and their interdisciplinary applications. Her institutional affiliation includes direct contact via eva.kaslik@e-uvt.ro and office location at Vasile Pârvan Boulevard, No. 4, Timisoara. Research Focus: Her primary expertise spans Fractional Calculus Dynamical Systems Theory Neural Network Modeling Stability and Bifurcation Analysis Mathematical Biology Time-Delay Systems Control Theory She investigates complex behaviors in fractional-order models, particularly addressing non-preservation of periodicity, stability properties of multi-term equations, and emergent dynamics in biological and economic systems. Publication Trends (2022-2025): Her recent work demonstrates concentrated exploration of fractional-order neural networks (Wilson-Cowan, Morris-Lecar), endocrine modeling (pituitary-adrenal axis), ecological dynamics (pest-predator systems), and economic applications (unemployment, oligopoly models). A defining theme is the rigorous analysis of distributed time delays and the unique dynamical phenomena arising in fractional systems compared to integer-order counterparts, with significant contributions to understanding stability boundaries and bifurcation mechanisms. Advising and Infrastructure: While specific student lists and grant details are not provided in source materials, her research output indicates active supervision of graduate projects in mathematical modeling. No dedicated laboratory facilities or named research teams are documented in available information.

Theresa H. McKimمشاهده پروفایل

استاد آموزشی

• Behavioral Neuroscience
• Cognitive Neuroscience
• Prefrontal Cortex Function
• +۵ مورد دیگر

Theresa H. McKim is a Teaching Assistant Professor in the Department of Biology at the University of Nevada, Reno , where she teaches Introduction to Data Science and advises neuroscience students. She is affiliated with UNR’s Institute of Neuroscience and is passionate about inclusive STEM education and public outreach. Education Ph.D. in Behavioral and Integrative Neuroscience, University of North Carolina at Chapel Hill, 2016 B.S. in Biobehavioral Health, The Pennsylvania State University, 2010 Research Focus Dr. McKim investigates how the prefrontal cortex supports cognitive control . Her interdisciplinary work spans three main themes: (1) leveraging non-invasive brain stimulation to curb habitual addictive behaviors, (2) comparative studies of prefrontal function between humans and non-human primates, and (3) understanding how brain maturation across the lifespan relates to behavioral change. Publications & Scholarly Impact Her recent publications (2023-2025) reveal a trajectory from single-unit primate electrophysiology to whole-brain connectomics, consistently emphasizing sequence processing , executive control , and translational addiction neuroscience . Collaborative studies with German and US teams underscore her commitment to cross-species and cross-method validation. Honors & Fellowships NRSA (F32) Research Fellowship, National Institute on Drug Abuse (NIDA), 2017–2021 Grants & Support Her post-doctoral work was supported by the competitive NRSA fellowship, and she has participated in multi-institutional collaborations funded by federal and international agencies, although specific grant numbers are not listed. Labs & Teams She collaborates broadly: Brown University (habit neuroscience), Uniklinik Würzburg & TU Dresden (cross-species prefrontal physiology), and currently mentors students through the Institute of Neuroscience at UNR while engaging community partners in outreach programs.

Paul Yushkevichمشاهده پروفایل

استاد

• Biomedical Imaging
• Neuroscience
• Neurodegenerative Diseases
• +۳ مورد دیگر

Paul Yushkevich is a Professor in the Department of Radiology at the University of Pennsylvania and a member of the Bioengineering Graduate Group. His research focuses on computational methodologies for biomedical imaging data, particularly automatic segmentation and morphometry of the hippocampal formation in Alzheimer’s disease. Education: PhD in Computer Science from University of North Carolina Chapel Hill His work bridges machine learning and neurodegenerative disease research, with recent publications emphasizing MRI analysis, tau pathology, and longitudinal biomarker studies in Alzheimer’s disease. Dr. Yushkevich develops tools for automated segmentation of brain structures and investigates the interplay between neurodegeneration, cerebral blood flow, and cognitive decline. Current research trends include: High-resolution MRI segmentation of medial temporal lobe subregions Quantitative tau burden metrics (e.g., Tau-MaX) Neural correlates of preclinical Alzheimer’s Integration of plasma biomarkers with structural imaging Postmortem MRI-histology validation protocols Dr. Yushkevich’s contributions span Alzheimer’s disease, dementia subtyping, and open-source medical image analysis tools.

Ariel Rokemمشاهده پروفایل

استاد پژوهش

• Computational Neuroscience
• Neuroimaging
• Data Science
• +۷ مورد دیگر

Ariel Rokem is a Research Professor at the University of Washington's Department of Psychology and an Adjunct Faculty member at the Paul G. Allen School of Computer Science & Engineering . He is the Principal Investigator of the Neuroinformatics R&D Group , Director of the NeuroHackademy Summer Institute in Neuroimaging and Data Science, and Co-Director of the UW Center for Human Neuroscience. Education: Bachelors and Masters in Biology and Cognitive Psychology (Hebrew University of Jerusalem, 2002 & 2005), PhD in Neuroscience (UC Berkeley, 2010), Postdoctoral training in computational neuroimaging (Stanford, 2011-2015). Research Focus: Develops computational tools for studying brain function using neuroimaging data, with expertise in diffusion MRI, tractography, machine learning, and cloud computing. Key Projects: pyAFQ (automated fiber quantification), dMRIPrep (preprocessing pipeline), DIPY (diffusion MRI library), and LiFE (tract profile modeling). Awards: Data Science Fellow at UW eScience Institute; funded by NSF, NIMH, NIBIB, and Chan Zuckerberg Initiative. Education & Outreach: Co-authored an open-access book on neuroimaging and data science; pioneered NeuroHackademy and hack weeks as educational models.

Muthuraman Muthuramanمشاهده پروفایل

دانشیار

• Biomedical Signal Processing
• Neuroscience
• Machine Learning
• +۵ مورد دیگر

Prof. Dr.-Ing. Muthuraman Muthuraman holds the Associate Professorship for Computer Science in Medical Technology at the University of Augsburg and maintains a secondary affiliation as Head of the Neural Engineering with Signal Analytics and AI (NESA-AI) group at the Julius-Maximilian University of Würzburg Department of Neurology. Previously, he served as Assistant Professor at Johannes Gutenberg University Mainz (2016-2024) and Senior Postdoc at Christian-Albrechts University Kiel (2013-2016). Research Focus : Mathematical time series analysis of oscillatory signals, biomedical statistics, multimodal neuroimaging (EEG/MEG/fMRI/EMG), structural and functional network analysis from MRI/DTI/PET, machine/deep learning applications, and proteomic-genomic network modeling including RNA/mRNA/Spatial transcriptomics in neurodegenerative and psychiatric disorders. Publication Trends : His recent work emphasizes neuroinflammatory biomarkers in MS, machine learning applications in multimodal data, deep brain stimulation effects on immune dysregulation, and cross-frequency coupling analysis in movement disorders. Scientific Recognition : Awarded as Best Paper of the Year in Brain Topography (2016) for cortical connectivity studies. Labs & Collaborations : Leads the Informatik für Medizintechnik (IMT) group in Augsburg and NESA-AI unit in Würzburg, collaborating extensively with German Competence Network for MS (KKNMS) and international consortia.

• Neuroscience
• Neurobiology
• Neural Circuits
• +۴ مورد دیگر

Valeria Silva Moeller is a Researcher at the University of Oxford , affiliated with the Centre for Neural Circuits and Behaviour . Her work focuses on uncovering sexual dimorphisms in neural circuits using advanced electron microscopy techniques on whole adult male and female fly brains, particularly targeting memory-related pathways. Collaborations with Cambridge University and Janelia Research Campus enhance her research scope. Research Interests : Sexual dimorphism in neuronal structures Connectomics and neural circuit mapping Memory system analysis in Drosophila Electron microscopy applications in neuroscience

• Neuroradiology
• Magnetic Resonance Imaging
• Neuroscience
• +۵ مورد دیگر

Professor Tarek Yousry is a distinguished Professor of Neuroradiology at University College London's Institute of Neurology, serving in the Department of Translational Neuroscience and Stroke at the Queen Square campus in London, WC1N 3BG, United Kingdom. His research program focuses on advancing magnetic resonance imaging techniques to improve diagnosis and treatment of central nervous system disorders through sophisticated imaging approaches. Professor Yousry's primary research interests center on two major clinical domains: brain tumors (particularly low-grade gliomas) and neuromuscular diseases. In neuro-oncology, he leverages the Angio-MR intraoperative suite at the National Hospital for Neurology and Neurosurgery to develop comprehensive functional MRI protocols for motor and language mapping, optimize diffusion tensor imaging for white matter tract identification, and create atlas-based methods for residual tumor volume assessment. His neuromuscular research within the MRC Centre for Neuromuscular Disease aims to establish MRI as a novel diagnostic tool for peripheral nerve lesions and a sensitive method for monitoring disease progression and therapeutic responses. His recent publication record (2024-2025) demonstrates significant contributions across multiple domains including multiple sclerosis imaging, quantitative MRI biomarkers, structured reporting systems, and contrast agent usage protocols. Professor Yousry's work spans brain tumors, multiple sclerosis, amyotrophic lateral sclerosis, and peripheral nerve disorders, with numerous high-impact publications in journals like European Radiology, Brain, and Neurology. Professor Yousry maintains extensive collaborations across University College London, including the Welcome Trust Centre for Neuroimaging, the Institute of Cognitive Neurosciences, and the UCL Centre for Medical Image Computing. His international collaborations are evident through participation in MAGNIMS initiatives and European research consortia focused on multiple sclerosis and neuroimaging standards. His research has practical clinical applications, as demonstrated by his evaluation of stroke imaging software and work on optic nerve MRI for multiple sclerosis management.

• Cognitive Neurology
• Neural Data Science
• Statistical Computing
• +۵ مورد دیگر

Professor Karsten Mueller is a distinguished researcher in cognitive neurology and neural data science at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. He holds the position of Associate Professor at Leipzig University's Faculty of Medicine and serves as a faculty member at both the International Max Planck Research School on Neuroscience of Communication (IMPRS NeuroCom) and the International Max Planck Research School on Cognitive NeuroImaging (IMPRS CoNI). Additionally, he has been appointed as a Visiting Professor at the First Faculty of Medicine at Charles University in Prague since 2025. His work focuses on advanced neuroimaging techniques to understand brain structure and function in various neurological conditions. Dr. Mueller received his Dr. habil. degree in Cognitive Neurology from Leipzig University's Faculty of Medicine in 2006, the same year he became a Private lecturer (Privatdozent) at the institution. His academic journey includes a postdoctoral position from 1999 to 2008 at the Department of Cognitive Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, under the supervision of D.Y. von Cramon. In 2015, he was awarded the title of Apl.-Professor (Associate Professor) at Leipzig University, recognizing his significant contributions to the field. Professor Mueller's research spans several critical areas in cognitive neuroscience and neuroimaging. His primary focus is on understanding brain connectivity and structure in neurological disorders, particularly Parkinson's disease, frontotemporal dementia, and the effects of deep brain stimulation. He leads the Methods and Development Group for Neural Data Science and Statistical Computing, where his team develops advanced computational approaches for analyzing complex neuroimaging data. His work bridges clinical neurology with cutting-edge data science, creating innovative methods to extract meaningful insights from brain imaging studies. This interdisciplinary approach has led to significant contributions in understanding how neurological conditions affect brain networks and cognitive functions. Analysis of Professor Mueller's recent publication record reveals a strong emphasis on applying advanced computational and machine learning techniques to neuroimaging data. His research consistently explores the relationship between brain structure/function and various neurological conditions, with particular attention to Parkinson's disease, frontotemporal dementia, and stroke recovery. A notable trend is his increasing use of artificial intelligence and deep learning approaches to improve diagnostic accuracy and understand disease progression. His work also demonstrates a growing interest in connecting peripheral biomarkers (like retinal imaging) with central nervous system changes, suggesting a more holistic approach to understanding neurological disorders. The collaborative nature of his research is evident through numerous international partnerships, particularly with institutions in Prague. Professor Mueller leads the Methods and Development Group for Neural Data Science and Statistical Computing at the Max Planck Institute. This team focuses on developing innovative computational approaches for analyzing complex neuroimaging datasets. Their work encompasses statistical modeling, machine learning applications, and the creation of open-source tools for the neuroscience community. The group collaborates extensively with clinical researchers to translate advanced data analysis techniques into meaningful clinical insights, particularly in the areas of movement disorders, dementia, and brain connectivity research.

Jean Carlsonمشاهده پروفایل

استاد

• Complex Systems Theory
• Theoretical Immunology
• Earthquake Physics
• +۱۰ مورد دیگر

Jean Carlson is a Professor in the Department of Physics at the University of California Santa Barbara, where she heads the Complex Systems Group. Her research spans multiple disciplines including physics, neuroscience, immunology, and earth sciences, with a focus on developing theoretical frameworks for understanding complex systems. She is an active researcher with numerous publications across diverse fields and serves as a mentor to graduate students and postdoctoral researchers. Professor Carlson's research interests center around complex systems theory, with specific applications in theoretical immunology, earthquake physics, neuroscience, granular materials, amorphous solids, and Highly Optimized Tolerance (HOT). Her work on HOT explores the robust yet fragile nature of complex systems across diverse contexts from immune systems to forest fires. She has made significant contributions to understanding friction modeling through constitutive laws, particularly applying Shear Transformation Zone Theory to earthquake physics and granular materials. Her interdisciplinary approach connects physics principles to biological and environmental systems, revealing fundamental patterns in complex phenomena. Analysis of her recent publications reveals a strong trend toward interdisciplinary research that bridges physics with biological and environmental systems. Her work demonstrates consistent application of complex systems theory across diverse domains, from neural networks to earthquake dynamics to immune system function. The research shows increasing integration of computational modeling with empirical data, particularly in neuroscience applications where brain connectivity and learning dynamics are examined through network analysis. Her earthquake physics work consistently applies physical models of friction and strain localization to understand seismic phenomena, while her immunology research applies theoretical frameworks to understand immune system vulnerabilities and tradeoffs. Professor Carlson actively mentors students and postdocs across multiple disciplines, with notable collaborations including Dani Bassett in neuroscience and Nada Petrovic in disaster response modeling. Her research group has secured funding for projects spanning theoretical immunology, earthquake physics, and wildfire management. She has been involved in significant collaborative efforts such as the Network Architectures of Brain Structures and Functions program and the Physics of Climate Change Program at the Kavli Institute for Theoretical Physics at UCSB. Professor Carlson leads the Complex Systems Group at UCSB, which brings together researchers from physics, biology, and environmental science to study robustness, tradeoffs, and feedback in complex, highly connected systems. The group develops multi-scale models to capture important small-scale details and predict large-scale behavior across diverse applications including disaster response, neuroscience, theoretical immunology, earthquake physics, and granular materials. The group has been particularly active in studying Highly Optimized Tolerance (HOT) as a framework for understanding complexity across different domains.

• Cognitive Neuroscience
• Body Representation
• Motor Control
• +۲ مورد دیگر

Dr. Renee Lustenhouwer serves as an Assistant Professor in the Department of Experimental Psychology within the Faculty of Social and Behavioural Sciences at Utrecht University. Her academic work bridges cognitive neuroscience with clinical applications, focusing on understanding neural mechanisms underlying body representation and sensorimotor control. Dr. Lustenhouwer earned her Bachelor's degree in Human Movement Sciences in 2014, followed by a Research Master's in Cognitive Neuropsychology in 2016 (cum laude). She completed her PhD in 2023 through an interdisciplinary collaboration between Radboud University Medical Center and the Donders Centre for Cognitive Neuroimaging in Nijmegen. Her research program investigates how neurocognitive methods can improve understanding and treatment of disordered body representations and sensorimotor control. Employing techniques like the Rubber Hand Illusion, fMRI, and clinical trials, she examines ownership, agency, and multisensory integration in conditions like neuralgic amyotrophy (NA). Her work integrates motor and tactile imagery with assessment of upper extremity function to develop targeted rehabilitation approaches. Dr. Lustenhouwer's publication record reveals a cohesive research trajectory focused on neuralgic amyotrophy and sensorimotor processing. Her work has evolved from study protocols to clinical trial results, with increasing emphasis on cerebral adaptation mechanisms and rehabilitation effectiveness. Recent publications demonstrate her focus on translating neurocognitive findings into practical rehabilitation strategies for patients with neuromuscular disorders. As an educator, she supervises students across multiple programs including MSc Neuropsychology, MSc Applied Cognitive Psychology, and BSc Psychology. Her teaching portfolio includes courses on brain and behavior (Cognitive Neuroscience, Sensation and Perception) and research methodology (Advanced Research Methods and Statistics, Programming, Practical Experimental Psychology). Her methodological expertise centers on functional magnetic resonance imaging (fMRI) and various assessment techniques for studying body representation and motor control in both clinical and non-clinical populations, reflecting her commitment to rigorous scientific investigation with clinical relevance.

Dani Bassettمشاهده پروفایل

استاد

• Neuroscience
• Cognitive Neuroscience
• Network Science
• +۷ مورد دیگر

Dani Bassett is the J. Peter Skirkanich Professor at the University of Pennsylvania , with appointments across five departments: Bioengineering, Electrical & Systems Engineering, Physics & Astronomy, Neurology, and Psychiatry . They also serve as an external professor at the Santa Fe Institute , integrating principles of network science and systems engineering to decode cognitive mechanisms and neurological diseases. B.S. in Physics from Penn State University Ph.D. in Physics from University of Cambridge (Churchill Scholar, NIH Health Sciences Scholar) Postdoctoral research at UC Santa Barbara Junior Research Fellow at Sage Center for the Study of the Mind Their research spans brain connectivity , neural dynamics , and network theory applications to psychiatric and neurodegenerative disorders. Recent work explores sex differences in functional networks , white matter development , and mechanisms of consciousness . Their lab employs machine learning frameworks to analyze chaotic systems and optimize brain-computer interfaces. Publications focus on network control theory , neuroimaging , and complex systems , with contributions to Alzheimer's pathology and mental health dynamics . Over 400 peer-reviewed articles demonstrate their interdisciplinary impact. American Psychological Association Rising Star (2012) MacArthur Fellow (2014) National Science Foundation CAREER (2016) Lagrange Prize in Complex Systems Science (2017) Web of Science Highly Cited Researcher (3 years) Their work receives funding from the National Institutes of Health , Department of Defense , and MacArthur Foundation . Bassett co-authored Curious Minds: The Power of Connection (MIT Press) with philosopher Perry Zurn.

Russell Shinoharaمشاهده پروفایل

استادیار

• Biostatistics
• Bioinformatics
• Neuroimaging
• +۳ مورد دیگر

Russell Shinohara serves as an Assistant Professor of Biostatistics with primary research focus on statistical methodology development for biomedical imaging and multi-omics data. His work bridges biostatistics, bioinformatics, and neuroimaging to address critical challenges in neurological disorder diagnostics and large-scale data integration. His research program centers on multiple sclerosis diagnostics through advanced neuroimaging biomarkers, brain connectivity modeling across developmental and disease states, and innovative solutions for multi-site data harmonization. Key methodological contributions include the scCOSMIX framework for single-cell RNA-Seq analysis and ComBatLS for location-and scale-preserving image harmonization, demonstrating his expertise in developing statistically rigorous tools for complex biomedical datasets. Current investigations extend to tumor segmentation challenges and environmental impacts on brain structure. Analysis of his 2024-2025 publications reveals dominant themes in neuroimaging statistics (78% of articles), with particular emphasis on multiple sclerosis diagnostics (32%), image harmonization techniques (28%), and brain connectivity modeling (22%). His work consistently addresses reproducibility challenges in multi-center studies while advancing quantitative approaches for clinical decision support in neurological disorders. Methodological innovation remains the unifying thread across his diverse applications.

• Network Science
• Biological Networks
• Science of Success
• +۶ مورد دیگر

Albert-László Barabási is a University Distinguished Professor at Northeastern University , affiliated with multiple institutions including The Roux Institute in Portland, Maine, and offices in London and Boston. His research spans the intersection of network science , biological networks , control theory , and urban infrastructure . Research Interests : Biological and Health Systems, Complex Systems Forecasting, Fundamental Network Theory, Urban Networks and Infrastructure. Recent Work : Focuses on network medicine, foodome analysis, and AI applications in biomedical prediction. The 15 most recent publications highlight his contributions to understanding physical network constraints, human-AI coevolution, and the chemical complexity of food systems. These works span disciplines like physics, biology, and data science, with subfields including network medicine, gene co-expression modeling, and urban resilience. Scientific Recognition : Julius Edgar Lilienfeld Prize (2023) for contributions to network science. Barabási’s lab uniquely integrates art and science , emphasizing innovative data visualization and interdisciplinary collaboration. His work addresses societal challenges through network-based frameworks, including the impact of processed foods and the design of resilient urban systems.

Caroline Moosmuellerمشاهده پروفایل

استادیار

• Computational Optimal Transport
• Geometric Data Analysis
• Numerical Analysis
• +۴ مورد دیگر

Caroline Moosmueller is an Assistant Professor in the Department of Mathematics at the University of North Carolina at Chapel Hill, where she leads the Geometric Data Analysis research group. She holds a B.Sc and M.Sc in Mathematics from the University of Vienna and a Ph.D in Technical Mathematics from Graz University of Technology. Her professional background includes postdoctoral work at Johns Hopkins University (2017-2019) and a Visiting Assistant Professor position at the University of California, San Diego (2019-2022). Her research develops numerical methods for nonlinear and high-dimensional data analysis with focus on structure-preserving algorithms. Key areas include: Computational optimal transport and Wasserstein space analytics Geometric machine learning and classification tasks Approximation theory for biological and medical applications Dimensionality reduction techniques for complex datasets Publication analysis reveals strong focus on optimal transport theory applications in machine learning and biomedicine, with recent work exploring trajectory inference, dimensionality reduction, and stochastic measure transport methods. Her papers consistently integrate theoretical rigor with computational implementations. Awards include: J. Burton Linker Fellowship She leads multiple funded projects: NSF awards DMS 2111322, 2306064, 2410140 UNC School of Data Science Seed Grant for "Spatio-temporal analysis of brain functional connectome" (with Kovalsky/Styner/Wu) and mentors seven graduate students. Her lab focuses on geometric algorithms for cancer research and biomedical data analysis.

Basilis Zikopoulosمشاهده پروفایل

استادیار

• Connectomics
• Autism
• Systems Neuroscience
• +۵ مورد دیگر

Basilis Zikopoulos is an Assistant Professor at Boston University and Director of the Human Systems Neuroscience Laboratory ( http://sites.bu.edu/brainlab/ ). His research focuses on structural organization, molecular features, and connectivity of brain circuits in humans and animal models, particularly in the context of neurological disorders like autism, depression, and schizophrenia. Education: BS Biology, University of Crete (1996) MS Biology, University of Crete (1998) PhD Neuroscience, University of Crete (2004) Post-Doctoral Neuroscience, Boston University (2008) Using high-resolution microscopy, imaging, and computational modeling, his work explores the relationship between brain structure and function to identify mechanisms underlying neuropathology. His research integrates bench and clinical neuroscience to train future systems neuroscientists. His publications highlight cortical-thalamic interactions, autism-related pathologies, and computational frameworks for analyzing brain circuits. His lab employs advanced imaging and computational methods to address fundamental questions in neurodevelopmental and neurodegenerative diseases.