جستجوی استاد راهنمای دانشگاهی

Tae-Ho Lee is an Associate Professor in the Department of Psychology at Virginia Tech, with affiliated appointments in the School of Neuroscience and Translational Biology, Medicine, and Health. His research focuses on affective and cognitive neural development across the lifespan, neurodegeneration, and family-based neural dynamics. PhD in Brain and Cognitive Science, University of Southern California M.A. in Clinical Psychology, Korea University B.A. in Psychology, Korea University Dr. Lee’s work explores brain connectome dynamics, dyadic neural concordance in families, and age-related attentional control. He employs neuroimaging techniques to study how familial and environmental factors shape emotional and cognitive outcomes in adolescents and older adults. Recent publications highlight trends in longitudinal studies , parent-child neural similarity , and functional connectivity in emotion regulation . Key areas include autism spectrum disorder, substance misuse risk, and the role of socioeconomic factors in brain development. Rising Star , Association for Psychological Science (2020) Dr. Lee is not currently accepting students and leads the Affective Neurodynamics and Development (AND) Lab at Virginia Tech.

• Affective Neuroscience
• Cognitive Development
• Neuroimaging
• +۷ مورد دیگر

Giorgio Ascoli is a University Professor in the Department of Bioengineering at George Mason University, where he has been since 1997. He is the Founding Director of the Center for Neural Informatics, Structures, & Plasticity (CN3) and Founding Editor-in-Chief of the journal Neuroinformatics . His affiliations span computational neuroanatomy, neuroinformatics, and hippocampal modeling. Education : PhD in Biochemistry and Neuroscience (1996), Scuola Normale Superiore; MS in Chemistry and Biochemistry (1993), Pisa University; BS in Chemistry and Physics (1991), Scuola Normale Superiore. Dr. Ascoli investigates the relationship between brain structure, activity, and function from cellular to circuit levels. His research focuses on anatomically plausible neural networks to model mammalian brains, particularly the hippocampus, with implications for understanding human memory and consciousness . He pioneered computational neuroanatomy, developing tools like L-Neuron for neuronal shape modeling and curating NeuroMorpho.Org , a central repository for digitally reconstructed neurons. His recent publications emphasize neuronal classification , connectome analysis , and biologically informed machine learning . Awards include the 2012 Outstanding Faculty Award (Virginia), 2022 AIMBE fellowship , and 2023 Presidential Faculty Excellence Awards . He has mentored over 20 graduate students and postdoctoral fellows, with funding from NIH, NSF, DARPA, and private foundations. Scientific Contributions : Over 137 peer-reviewed articles, 4 patents, 2 authored/edited books, and leadership in NeuroMorpho.Org and Hippocampome. Grants : $20M+ in cumulative funding, including NIH R01s, NSF BRAIN EAGERs, and Burroughs-Wellcome Trust support. Labs : Leads the Computational Neuroanatomy Group within CN3, focusing on hippocampal modeling, neuronal morphology, and consciousness theories.

• Computational Neuroanatomy
• Neuroinformatics
• Neuronal Morphology
• +۵ مورد دیگر

Patrick Desrosiers serves as an Adjunct Professor in the Department of Physics, Physical Engineering and Optics within Université Laval's Faculty of Science and Engineering, while conducting neuroscience research at the CERVO Brain Research Center. He co-directs Dynamica, a multidisciplinary complex systems research group, and participates in UNIQUE (neuroscience-AI integration) and CIMMUL (mathematical modeling applications). His academic training spans physics and mathematics at Université Laval, the University of Melbourne, and CEA-Saclay. Dr. Desrosiers' research centers on mathematical and computational neuroscience , with signature contributions in dimensionality reduction and network resilience analysis . His work bridges biological and artificial neural networks , zebrafish brain mapping , and neurovascular coupling using advanced techniques from spectral graph theory , random matrix theory , and dynamical systems . Current investigations focus on neural decoding under chronic stress and structural-functional relationships in brain networks. Analysis of his 2023-2025 publications reveals three dominant trajectories: (1) Low-dimensional representations for predicting cognitive decline and neural dynamics, (2) Network reconstruction methodologies applied to neuroscience and biodiversity, and (3) Development of computational tools like NeuroTorch for neural data analysis. His work consistently integrates mathematical rigor with biological relevance across species and scales. His recognition includes: Professeur étoile prize for exceptional teaching (Faculty of Science and Engineering, Université Laval, 2018) As Dynamica co-director, he mentors a research team comprising Antoine Légaré, Arthur Légaré, Benjamin Claveau, Jordan Charest, Marziyeh Pourmousavi, Pierre-Luc Larouche, Vincent Savard, Vincent Thibeault, and Zahra Yazdani. His collaborative framework connects physics, mathematics, and neuroscience to address fundamental questions in neural network organization, with funding evident through sustained publication output and lab operations. Dynamica Lab ( https://dynamicalab.github.io/ ) serves as the operational hub for his interdisciplinary research, maintaining active collaboration with CERVO Brain Research Center and international institutions.

• Dimensionality Reduction
• Dynamical Systems
• Mathematical and Computational Neuroscience
• +۸ مورد دیگر

Jan G. Bjaalie is Professor of Neuroinformatics and Dean of Research and Innovation at the University of Oslo Faculty of Medicine . Since 2023 he heads the faculty’s research and innovation strategy, while directing the Neural Systems and Graphics Computing Laboratory at the Institute of Basic Medical Sciences. Education: 1990 Ph.D. in Neuroanatomy, University of Oslo 1986 M.D., University of Oslo Research interests revolve around collaborative and open neuroscience, digital brain atlasing, and the cyber-infrastructures that enable data sharing. He leads efforts to build next-generation atlases that integrate multi-scale brain architecture and connectivity data, and to develop ontologies and FAIR-compliant platforms for global neuroscience. Recent work emphasizes in silico integration of rodent and human imaging datasets, leveraging machine-learning registration tools and cloud-based services such as EBRAINS. The goal is to transform how brain data are stored, visualised and reused across laboratories worldwide. Scientific output & impact: A scan of publications from 2023-2025 reveals a strong focus on digital atlas frameworks, automated image registration (DeepSlice, DeMBA), open data standards (AtOM ontology), and large-scale analyses of genetic influences on brain structure in Alzheimer’s models. These works collectively advance reproducible, high-throughput neuroanatomy and cross-species translation. Grants & leadership roles: Coordinator/Partner in EU Flagships EBRAINS 2.0, BRAIN Health, Human Brain Project (2013-2026) Infrastructure Director, Human Brain Project (2018-2023) Leader of Neuroinformatics Platform & EBRAINS Data Services (2017-2023) Head of Institute of Basic Medical Sciences (2009-2016) Executive Director, International Neuroinformatics Coordinating Facility (INCF) (2006-2008) Chair, International Brain Initiative (2021-) Editorial & governance service: Founding Chief Editor Frontiers in Neuroinformatics (2007-), Section Editor Brain Structure and Function (2002-2020), member of the INCF Governing Board and EBRAINS AISBL Management Board, and numerous international advisory panels on data governance and ethics. His laboratory hosts the Norwegian Neuroinformatics Node and collaborates closely with global consortia to deliver open-access atlases, software pipelines and FAIR data standards that underpin modern neuroscience.

• Neuroinformatics
• Digital brain atlasing
• Brain architecture and connectivity
• +۴ مورد دیگر

Dr. Daniel Tward is an Assistant Professor at the University of California, Los Angeles (UCLA), holding joint appointments in the Department of Neurology and the Department of Computational Medicine. He earned his Ph.D. in Biomedical Engineering from Johns Hopkins University and completed postdoctoral training at the Kavli Neuroscience Discovery Institute. His research integrates neuroimaging, machine learning, and differential geometry to analyze brain structure changes in neurodegenerative diseases like Alzheimer's, with a focus on bridging molecular pathology and clinical imaging. Research Interests: Dr. Tward's work addresses challenges in neuroimaging data complexity, developing computational tools to map brain anatomy across scales (from centimeters to microns). Key areas include neurodegeneration in the medial temporal lobe, multi-modal image registration, and spatial transcriptomics. His lab emphasizes high-dimensional statistics and geometry-driven analysis to improve diagnostic accuracy and clinical trial design. Grants & Projects: Secured NIH funding for: A 3D multimodal human brain atlas integrating MRI and histology. CloudReg—a distributed framework for massive neuroimage registration. Contributions to the BRAIN Initiative Cell Census Network (BICCN) for mouse/rat brain atlases. Students & Training: Mentors undergraduate researchers via the BIG Summer program, with projects on neural networks, spatial transcriptomics, and MRI analysis. No PhD/Master's advisees listed.

• Neuroimaging
• Computational Neuroscience
• Machine Learning
• +۴ مورد دیگر

Mallar Chakravarty is an Associate Professor in the Department of Psychiatry at McGill University's Faculty of Medicine and an Associate Member of the Department of Biomedical Engineering. He serves as Director of the Brain Imaging Centre at the Douglas Research Centre and leads the Computational Brain Anatomy (CoBrA) Laboratory. His work bridges computational neuroscience, psychiatry, and biomedical engineering to advance understanding of brain structure and function. Dr. Chakravarty received his Bachelor's Degree in Electrical Engineering from the University of Waterloo and his PhD in Biomedical Engineering from McGill University. He completed postdoctoral fellowships in Aarhus, Denmark and jointly at the Rotman Research Institute, Mouse Imaging Centre (MICe), and Hospital Sick Children in Toronto, Canada. Between fellowships, he worked at the Allen Institute for Brain Science in Seattle, WA, USA. His research focuses on computational neuroanatomy, specifically examining how brain anatomy changes through development, aging, and in illness. The CoBrA Lab investigates brain maturation through adolescence, the normal aging process, and alterations in brain anatomy related to neurodegenerative disorders such as Alzheimer's and Parkinson's disease, as well as neurodevelopmental disorders like schizophrenia. The lab develops sophisticated computational techniques to automatically analyze the geometric complexity of brain anatomy using MRI and other imaging modalities. Analysis of Dr. Chakravarty's recent publications reveals a strong emphasis on hippocampal and striatal morphology, brain development across the lifespan, and computational methods for neuroanatomical analysis. His work consistently bridges basic neuroscience with clinical applications, particularly in psychiatric and neurodegenerative disorders. The publications demonstrate expertise in multi-atlas segmentation, high-resolution MRI atlas development, and longitudinal neuroimaging analysis. Fonds de recherche du Québec – Santé (FRQS) Research Scholar, Junior 2 Fonds de Recherche Santé Québec – Young Investigator Award Junior 1 Sertuener Award for best scientific work in pain research in Germany 2016 CCNP Young Investigator Award 2023 Member to the College of New Scholars, Artists, and Scientists Dr. Chakravarty actively mentors a diverse team of researchers including neuroscientists, computer scientists, engineers, and physicists. His lab has secured significant funding from multiple sources including FRQS, CIHR, and private foundations such as the TD Ready Commitment for Digital Mental Health research. The lab is known for its commitment to open science, publicly disseminating algorithms and atlases to promote reproducible research. The Computational Brain Anatomy (CoBrA) Laboratory operates within the Cerebral Imaging Centre at the Douglas Mental Health University Institute. The lab's multi-disciplinary approach combines expertise from neuroscience, computer science, engineering, and physics to understand brain structure-function relationships through health and illness. Their work has contributed significantly to the field of computational neuroanatomy and its applications in mental health research.

• Computational Neuroanatomy
• Brain Imaging
• MRI Analysis
• +۷ مورد دیگر

Trygve Brauns Leergaard is a Professor at the Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo. His academic work focuses on neuroanatomy, brain connectivity mapping, morphological phenotyping, and neuroinformatics, particularly in rodent models. MD, University of Leiden (1996) PhD, University of Oslo (2000) Research Interests: Leergaard specializes in digital brain atlasing, histological validation of neuroimaging, and neuroinformatics. His work bridges computational methods with neuroanatomical studies, emphasizing standardization of brain mapping techniques. Recent Publications: His 2024–2025 research includes developing spatial integration workflows, comparative brain atlas metadata models, and developmental mouse brain atlases. Earlier work (2018–2023) explored neurodegenerative disease models, brain tumor growth patterns, and Parkinson's disease mechanisms. Laboratory & Collaborations: He co-leads the Neural Systems and Graphics Computing Laboratory and collaborates internationally with institutions including UC San Diego, Duke University, and NTNU.

• Neuroanatomy
• Brain connectivity mapping
• Morphological phenotyping
• +۵ مورد دیگر

Leonard Edward White is an Associate Professor in Neurology at Duke University, with additional appointments in Psychology and Neuroscience, Orthopaedic Surgery, and Neurobiology. He serves as Associate Director of the Duke Institute for Brain Sciences and Director of Undergraduate Studies of Neuroscience. His academic career spans over three decades since earning his Ph.D. from Washington University in St. Louis in 1992. Dr. White's research focuses on the structure and function of the mammalian brain, particularly through the development of advanced magnetic resonance methods for interrogating brain structure. His work combines light sheet microscopy with MRI techniques to provide new insights into microscopic brain structure, whole-brain connectivity, and how neural tissue constrains connectivity in animal models. He maintains a sustained interest in how early sensorimotor experience influences neural circuit formation and maturation in the cerebral cortex, as well as the intersection of brain sciences with humanities. His recent publications (2020-2025) reveal a strong emphasis on high-resolution brain imaging techniques, particularly MRI and light sheet microscopy for creating detailed brain atlases. His work spans multiple species (mouse, rat, human) and addresses fundamental questions in neuroanatomy, connectomics, and developmental neuroscience. Notably, he has been developing the Duke Mouse Brain Atlas and exploring the impact of prenatal drug exposure on brain development. Dr. White has secured significant research funding, including the current 'Ultra-high Resolution Structural Connectome Atlases of the Animal Brain' grant (2022-2026) from the University of Pittsburgh, and previously led NIH-funded projects on visual cortex development spanning nearly two decades. He is deeply involved in medical education, serving as Director of Undergraduate Studies of Neuroscience and developing innovative approaches to teaching neuroanatomy. His educational scholarship includes work on integrating art into medical education and revitalizing neuroanatomy teaching methods. He also maintains an active presence in neurohumanities, exploring the intersection of neuroscience with arts and humanities.

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

Jan G. Bjålie is a Professor and Vice Dean for Research and Innovation at the Faculty of Medicine, University of Oslo. He has led neuroinformatics development since the 1990s and held leadership roles including Head of the Department of Basic Medical Sciences (2009-2016) and Head of Infrastructure Development for EBRAINS. His research bridges neuroanatomy, computational neuroscience, and digital brain atlases. Doctor of Medicine, University of Oslo (1990) Associate Professor (1991), Professor (1997) in Basic Medical Sciences 2016-: First Leader, International Neuroinformatics Coordinating Facility 2017-: Coordinator, Human Brain Project Neuroinformatics 2019-2021: Head, International Brain Initiative Research Interests span neuroinformatics, brain architecture, and digital brain atlases. His work focuses on: Developing standardized frameworks for brain atlas utilization 3D spatial mapping of neural systems Neuroanatomical connectivity in rodent models Integration of multi-modal neuroscience data International collaboration in brain research Computational modeling of brain structure-activity relationships Recent Publications highlight advancements in automated brain imaging registration, developmental brain mapping, cross-cultural neuroscience perspectives, and genetic influences on brain composition. His neuroinformatics tools (e.g., DeepSlice, Waxholm Space, AtOM) enable global standardization of brain data analysis. Leadership Roles include: Vice Dean for Research and Innovation (2023-2026) Infrastructure Development Lead for EBRAINS (2019-) International Brain Initiative Head (2019-2021) Coordinating EU-funded Human Brain Project neuroinformatics Collaborations extend across major brain projects in the USA, Japan, and Europe through initiatives like the International Brain Initiative and ESFRI roadmap projects.

• Neuroinformatics
• Brain Architecture
• Digital Brain Atlases
• +۷ مورد دیگر

Professor Daniel Murphy is a Professor of Lung Cancer & Mesothelioma at the University of Glasgow's Institute of Cancer Sciences, based at the CRUK Beatson Institute. His research focuses on understanding the molecular mechanisms underlying lung cancer and mesothelioma, with particular emphasis on genetically engineered mouse models and kinase signaling pathways. His work bridges basic science with clinical applications to develop new therapeutic approaches. Professor Murphy's research interests span multiple areas of cancer biology, with a strong focus on lung cancer and mesothelioma pathogenesis. His laboratory investigates how oncogenes like MYC drive tumor development and progression, with particular attention to metabolic reprogramming, kinase signaling networks, and the role of environmental factors like asbestos in mesothelioma. He has made significant contributions to understanding NUAK1 kinase signaling in cancer, centrosome regulation in pancreatic cancer, and mitochondrial dysfunction in tumor progression. His work often employs sophisticated genetically engineered mouse models to study cancer biology in physiologically relevant contexts. Analysis of Professor Murphy's recent publications reveals a strong thematic focus on molecular mechanisms of cancer development, with particular emphasis on kinase signaling pathways (especially NUAK1), metabolic reprogramming in tumors, and the molecular basis of mesothelioma. His research increasingly incorporates advanced computational approaches, as evidenced by publications on histomorphological atlases using self-supervised learning. The work spans basic molecular mechanisms to translational applications, with several studies identifying potential therapeutic targets in liver cancer, pancreatic cancer, and myeloproliferative disorders. Pharmacological inhibition of MYC in lung cancer (Beatson Cancer Charity, 2025-2026) Dactinomycin has an immunopotentiation effect by inducing MHC-I expression of cancer cells (University of Oxford, 2024-2025) REMIT: REconstruction of disease evolution in Mesothelioma for Improved Therapy (Cancer Research UK, 2023-2028) Using complex state of the art mouse models of cancer to improve the understanding and treatment of human cancer (Medical Research Council, 2022-2027) PREDICT-Meso: PRE-malignant Drivers Combined with Target-Drug validation in Mesothelioma (Cancer Research UK, 2020-2025) Professor Murphy leads a research group focused on oncogene-induced vulnerabilities, particularly studying how MYC and related pathways drive cancer development. His laboratory utilizes advanced genetically engineered mouse models to investigate lung cancer and mesothelioma pathogenesis, with recent work increasingly incorporating computational approaches to analyze complex histopathological data. The research has significant translational potential, with several recent studies identifying novel therapeutic targets across multiple cancer types.

• Lung Cancer
• Mesothelioma
• Cancer Research
• +۵ مورد دیگر

Professor Hong Wei Dong is a faculty member in the Department of Neurobiology at the David Geffen School of Medicine, University of California Los Angeles (UCLA). His research focuses on creating comprehensive connectome maps of the C57Bl/6 mouse brain to understand functional network organization and behavioral output mechanisms. He integrates Connectomics Genetics 3D high-resolution imaging Artificial intelligence to explore the fundamental architecture of the central nervous system. Key research directions include: Classification of mouse brain/spinal cord cell types through anatomic, molecular, and physiological properties Development of microscopy/histological technologies for human brain mapping at axonal resolution Application to neurodegenerative disease models (Alzheimer’s, Huntington’s) Recent publications highlight his work on: Visceromotor cortex networks High-resolution brain atlases Thalamic subnetworks Neuronal diversity analysis Advanced image processing tools Transsynaptic tracing methodologies Awardeeship highlights: Suzanne Eaton Memorial Prize Taylor M. Brown Memorial Award His lab develops scalable technologies like Gossamer for petabyte-scale image processing and Morphohub for multi-morphometry generation, while maintaining affiliations with UCLA Brain Research & Artificial Intelligence Nexus (B.R.A.I.N.) and NIH T32 training grants.

• Neuroanatomy
• Connectomics
• Neural circuits
• +۵ مورد دیگر

Dr. Meiqi Niu is a Researcher at the Institute of Neuroscience and Medicine (INM-1) , Research Center Jülich GmbH, specializing in neuroimaging and brain architecture. Her work focuses on mapping cortical structures and receptor distributions in macaque and human brains, with applications in comparative neuroscience, bilingualism effects, and neurodegenerative disorders. She contributes to creating population-based brain atlases (e.g., MEBRAINS 1.0) and advancing neuroimaging techniques like 3D Polarized Light Imaging (PLI). Expertise: Brain mapping, receptor distribution analysis, computational neuroanatomy Techniques: 3D neuroimaging, machine learning, diffusion tensor imaging (DTI) Key Projects: Macaque brain atlases, somatosensory cortex organization, bilingualism impact studies Her research integrates cytoarchitectonic, receptor, and functional connectivity data to understand brain structure-function relationships. Recent work explores how neurotransmitter receptor gradients influence neural processing and how early language acquisition shapes brain networks. Labs/Teams: Active contributor to the Structural and Functional Organization of the Brain group (INM-1), collaborating on multimodal brain mapping initiatives.

• Neuroscience
• Cognitive Neuroscience
• Neuroimaging
• +۳ مورد دیگر

Rogier Mars is a Professor of Neurosciences and MRC Senior Non-clinical Fellow at the University of Oxford, affiliated with the Nuffield Department of Clinical Neurosciences (NDCN) and St Hilda's College. His research focuses on understanding how brain structure and function evolve in response to environmental challenges, combining human neuroimaging techniques (e.g., fMRI, TMS) with comparative analyses of post-mortem animal brains. Key projects include cross-species tractography, cortical surface reconstruction pipelines, and evolutionary studies of language-related neural infrastructure. Research interests emphasize structural connectomics, neuroecology, and primate brain evolution. His work bridges human and non-human primate neuroanatomy, exploring adaptations in brain organization across species. Recent publications highlight innovations in imaging techniques like hybrid MRI-microscopy and computational tools for multi-species brain comparisons. Scientific awards include the prestigious MRC Senior Non-clinical Fellowship. He leads the Neuroecology & Anatomy Lab and the Preclinical Imaging Group, advancing open-access resources such as the Digital Brain Bank for post-mortem datasets. Collaborative efforts prioritize multi-center initiatives to standardize protocols for neuroimaging and comparative neuroscience.

• Comparative Neuroanatomy
• Neuroimaging
• Evolutionary Neuroscience
• +۴ مورد دیگر

Mahyar Firouzi is a Researcher at Vrije Universiteit Brussel, affiliated with the department of Physiotherapy, Human Physiology and Anatomy and the Brain, Body and Cognition research group. His work focuses on neurorehabilitation, motor learning, and the application of non-invasive brain stimulation (e.g., tDCS) in neurological conditions like Parkinson’s disease. He is the principal investigator of the ongoing project 'Neural networks underlying implicit motor sequence learning in Parkinson's disease: effects of non-invasive brain stimulation' (2021–2025). His research integrates cognitive neuroscience with clinical rehabilitation, exploring topics such as cerebellar function, dual-task gait performance, and exoskeleton design for aging populations. Firouzi has supervised two Master’s theses examining perioperative pain management strategies and lumbar radiculopathy. He actively participates in academic events, including organizing symposiums on portable technology and presenting at conferences on neurostimulation. Key contributions include systematic reviews on stroke rehabilitation electrotherapy and tDCS effects in Parkinson’s disease, as well as developing exergames and functional cerebellum atlases. He received the Best Presentation Award at the C4N PhD Day in 2020 and holds a FWO Fundamental Research Fellowship.

• Neuroscience
• Neurorehabilitation
• Motor Learning
• +۵ مورد دیگر

Bennett A. Landman is the Stevenson Chair of Engineering and a Professor of Electrical and Computer Engineering at Vanderbilt University's School of Engineering. He holds additional professorships in Computer Science, Biomedical Engineering, Radiology, Psychiatry, Biomedical Informatics, and Neurology. Landman leads the Vanderbilt Lab for Immersive AI Translation (VALIANT) and has been instrumental in advancing medical image processing and AI-driven personalized medicine. Education: B.S. & M.Eng. in Electrical Engineering and Computer Science from MIT (2001-2002) Ph.D. in Biomedical Engineering from Johns Hopkins University (2008) Research Focus: Landman's work centers on applying image-processing technologies to large-scale medical imaging studies, particularly in neuroimaging and radiology. His research integrates machine learning, big data analytics, and AI to improve diagnostic accuracy and personalized healthcare. Key areas include diffusion MRI harmonization, functional MRI analysis, and automated medical image segmentation. Recent Trends in Articles: Landman's latest publications focus on spatial smoothing techniques in white matter imaging, super-resolution eye atlases, and scalable medical data processing. His work emphasizes cross-disciplinary collaboration and the development of robust preprocessing methods for multi-site datasets. Awards: Fellow of the SPIE (2021) Grants & Advising: Secured grants from NIH, NSF, and DoD. Advised over 340 co-authors across institutions, resulting in 450+ peer-reviewed publications and 24,000+ citations. Served as editor for IEEE Transactions on Medical Imaging and co-chair of SPIE Medical Imaging conferences. Labs & Teams: Director of VALIANT and founding director of Vanderbilt's Center for Computational Imaging. Active in the Vanderbilt Brain Institute and Kennedy Center, advancing interdisciplinary research in surgery, engineering, and neuroscience.

• Medical Imaging
• Biomedical Engineering
• Machine Learning
• +۶ مورد دیگر