جست‌وجوی استاد و پژوهشگر

Jean-Philippe Thiranمشاهده پروفایل

استاد

• Computational Imaging
• Medical Image Analysis
• Diffusion MRI
• +۵ مورد دیگر

Prof. Jean-Philippe Thiran is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he serves as Director of the Signal Processing Laboratory (LTS5) and Director of the Institute of Electrical and Micro Engineering. He also maintains a part-time Associate Professor position with the Department of Radiology of the University Hospital Center (CHUV) and University of Lausanne (UNIL). Born in Namur, Belgium in 1970, he received his Electrical Engineering degree and PhD from the Université catholique de Louvain (UCL), Belgium, in 1993 and 1997 respectively. He joined EPFL in 1998 and has established himself as a leading researcher in computational imaging. His research focuses on computational imaging , with significant contributions to medical image analysis (particularly diffusion MRI, ultrasound imaging, and digital pathology) and computer vision . His recent work integrates advanced modeling, simulation, and machine learning techniques to extract microscopic tissue information from macroscopic MRI signals. This approach combines hyper-realistic synthetic tissue models, advanced Monte-Carlo simulations, and ML-based estimation techniques for brain microstructure analysis with potential applications to other tissues. Senior Member of IEEE Fellow of the European Association for Signal Processing (EURASIP) Prof. Thiran has authored or co-authored 1 book, 9 book chapters, 250 journal papers and over 270 peer-reviewed conference papers, and holds 12 international patents. He previously served as Co-Editor-in-Chief of the Signal Processing journal (2001-2005) and associate editor of IEEE Transactions on Image Processing. He has chaired major conferences including EUSIPCO 2008 and IEEE ICIP 2015. His laboratory at EPFL brings together interdisciplinary researchers to develop innovative imaging techniques that bridge macroscopic measurements and microscopic tissue properties, with significant potential for medical diagnostics and treatment planning applications.

• Computational Modelling of Neural Networks
• Biophysical Modelling of EEG/MEG
• Diffusion Tractography
• +۲ مورد دیگر

Professor Thomas R. Knösche is a Group Leader at the Methods and Development Group Brain Networks within the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. His research focuses on computational modeling of neural networks, biophysical modeling of EEG/MEG data, diffusion tractography, and the neurocognition of language and music. He holds a professorship at the institute and leads research initiatives in brain networks and neuroimaging methodologies. His work bridges theoretical neuroscience with practical applications in understanding brain function through advanced computational techniques. Contact information includes his office phone (+49 341 9940-2619) and lab address: Stephanstraße 1A, 04103 Leipzig, Saxony, Germany.

• Nuclear Magnetic Resonance (NMR)
• In vivo imaging
• MRI pulse sequence development
• +۷ مورد دیگر

Professor Guy Williams is a leading academic at the University of Cambridge with a focus on imaging science and clinical neurosciences, affiliated with Downing College and the Wolfson Brain Imaging Centre . Holding a PhD in Physics from his initial Natural Sciences degree, he specializes in nuclear magnetic resonance (NMR) and MRI techniques for brain imaging. Education: BA, PhD in Physics His research centers on non-invasive imaging of brain structure and function, particularly in traumatic brain injury (TBI) and dementia. His work involves developing novel MRI pulse sequences and advanced data analysis algorithms, including AI-based diagnostic tools. He leads studies on white matter integrity post-trauma, longitudinal dementia assessment, and applications of MRI in disorders of consciousness and addiction. Recent publications highlight collaborations in traumatic brain injury outcomes, AI-guided dementia prediction, and neuroimaging of post-COVID cognitive deficits. His team's work on ultra-high field laminar fMRI and distortion correction methods has advanced clinical neuroscience applications. Key techniques include diffusion tensor imaging (DTI), 7 Tesla MRI, and positron emission tomography (PET/MR). His research spans from basic NMR physics to clinical translation, with a strong emphasis on multi-site studies and real-world diagnostic implementation.

• Inverse problems and reconstruction
• Neuroimaging
• Quantitative MRI
• +۱ مورد دیگر

Daan Christiaens is a tenure track lecturer at KU Leuven's Faculty of Medicine and Faculty of Engineering Sciences. He is affiliated with the Department of Electrical Engineering (ESAT) and Department of Imaging & Pathology, serving as a member of the Medical Imaging Division and the KU Leuven Brain Institute (LBI). His academic responsibilities include membership in the Faculty Councils of Engineering Sciences and Medicine. His research focuses on: Inverse problems in medical imaging reconstruction Neuroimaging techniques for brain analysis Advanced quantitative MRI methodologies Diffusion-weighted imaging for microstructural assessment Dr. Christiaens' recent publications (2023-2025) demonstrate a consistent focus on diffusion MRI innovations, including novel reconstruction algorithms, neonatal brain development mapping, and clinical applications for neurodegenerative disorders. Key technical themes include motion correction, multi-shell modeling, and AI-enhanced image processing, while clinical applications span Alzheimer's disease, cerebral palsy, and autism research. He leads significant research projects including: MRI reconstruction with dynamic field monitoring (2024-2028) Compressed sensing for microstructure imaging (2022-2026) Neonatal diffusion MRI network connectivity analysis (2024-2028) As a core developer of the MRtrix3 software framework for medical image processing, he contributes to essential tools in neuroimaging research.

Merry Maniمشاهده پروفایل

دانشیار

• Biomedical Imaging
• Signal Processing
• Image Reconstruction
• +۴ مورد دیگر

Dr. Merry Mani is an Associate Professor in Radiology and Imaging Sciences and Biomedical Engineering, specializing in biomedical imaging and signal processing. Her work focuses on advancing MRI-based imaging technologies to study neurological disorders such as Alzheimer's, Autism, and Epilepsy. She holds a Ph.D. in Electrical and Computer Engineering from the University of Rochester (2014) and completed a postdoctoral fellowship at the University of Iowa School of Medicine (2018). Her research combines biophysical modeling with machine learning to explore brain microstructures. Key achievements include the NNARSAD Young Investigator Grant and NIH-funded projects like 'Fast Multi-dimensional Diffusion MRI with Sparse Sampling'. Her lab develops cutting-edge reconstruction methods like qModeL and MUSSELS, prioritizing high spatio-temporal resolution imaging. Major contributions span diffusion MRI acquisition, model-based deep learning, and clinical applications in neurodegenerative diseases. Notable grants include NIH R01EB031169 for Alzheimer’s neurodegeneration studies and projects on rTMS for depression. Her work bridges imaging innovation with clinical impact, aiming to improve diagnosis and treatment through advanced imaging biomarkers.

• MRI
• Diffusion MRI
• Perfusion MRI
• +۶ مورد دیگر

Professor Fernando Calamante is a Professor of Biomedical Engineering at The University of Sydney and Director of Sydney Imaging Core Research Facility. He leads the National Imaging Facility node and focuses on advanced MRI methodologies, particularly Diffusion and Perfusion MRI, to study brain connectivity and neurological disorders. His work includes developing the MRtrix software, widely used in diffusion MRI analysis. He holds extensive funding (~$50M) and has been recognized with awards like ISMRM Fellowship and NHMRC grants. His research spans super-resolution imaging, brain connectomics, and clinical applications in stroke and tumors. Education: BSc (Physics, Argentina), PhD (Magnetic Resonance Imaging, University College London). Career highlights include leadership roles at The Florey Institute and ISMRM presidency (2021-2022). Research interests include: Novel MRI methods for brain connectivity and super-resolution imaging Applications of Diffusion and Perfusion MRI in neurology Integration of structural and functional connectomics Key achievements: Over 200 publications, software innovations, and leadership in global MRI societies.

Lawrence H. Staibمشاهده پروفایل

استاد

• Medical Image Analysis
• Machine Learning
• Nonrigid Registration
• +۶ مورد دیگر

Lawrence H. Staib is a Professor of Biomedical Engineering at Yale University, with additional academic appointments in Electrical & Computer Engineering and Radiology & Biomedical Imaging. He holds a Ph.D. from Yale University and specializes in automated medical image analysis, including techniques like model-based segmentation, nonrigid registration, and diffusion tensor imaging (DTI). His research focuses on applications in neuroscience, cardiology, and cancer imaging, emphasizing machine learning and functional MRI analysis. His key contributions include advancements in white matter tractography via anisotropic wavefront evolution, real-time neural tract parcellation (Fasciculography), and noise reduction in diffusion tensor fields. Staib is a Fellow of the American Institute for Medical and Biological Engineering (2015), recognizing his impactful work in medical imaging technologies. Staib's research also encompasses statistical deformation models, perturbation-based shape analysis, and 3D deformable models for volumetric segmentation. He has developed patented 3D ultrasound computed tomography systems (USPTO #6878115, 7025725). His work bridges clinical needs with computational methods, addressing challenges in image registration, structural connectivity analysis, and medical robotics.

Kep Kee Lohمشاهده پروفایل

مربی ارشد

• Comparative primate neuroanatomy
• Sulcal anatomy
• Frontal cortex function
• +۴ مورد دیگر

Kep Kee Loh is a Senior Tutor in the Department of Psychology at the National University of Singapore (NUS). Currently, he also holds an NUS Overseas Postdoctoral Fellowship position at both the Montreal Neurological Institute (McGill University) and the University of Oxford. His research focuses on comparative primate neuroanatomy, examining what makes the human brain special compared to other primates through multimodal MRI techniques. Ph.D. in Neuroscience from Université Claude Bernard Lyon I (2014-2018) M.Sc. in Cognitive Neuroscience from University College London (2011-2012) B.Soc.Sci. (Hons.) in Psychology from National University of Singapore (2007-2011) Dr. Loh's research primarily investigates the anatomical organization of brains across humans and various primate species including chimpanzees, baboons, and macaques. He employs different magnetic resonance imaging techniques (anatomical, resting-state, diffusion-weighted MRI) to compare brain organization across species, with particular focus on the medial frontal cortex, sulcal anatomy, and the evolution of speech and language in the human brain. His work adopts a multimodal approach to provide an integrative view of what sets human brains apart from other primates. His recent publications demonstrate a strong focus on comparative neuroanatomy across species, with particular emphasis on primate brain evolution, frontal cortex organization, and language-related neural pathways. The research spans multiple disciplines including neuroscience, cognitive science, and evolutionary biology, with increasing attention to methodological advancements in neuroimaging techniques for cross-species comparisons. NUS Overseas Postdoctoral Fellowship (2021) Institute of Language, Communications and the Brain (ILCB) Postdoctoral Fellowship (2019) Fondation Recherche Médicale (FRM) Fin de Thèse (PhD funding) (2017) BRAIN Student Travel Award, 6th Motivation and Cognitive Control Symposium (2016) Dr. Loh has been involved in numerous collaborative research projects across international institutions, including the French Institute of Health and Medical Research (Stem Cell and Brain Research Institute), Aix-Marseille Université, and currently McGill University and the University of Oxford. His work has received significant recognition with over 1,000 citations for his 33 publications. While specific grant information isn't detailed in the provided text, his postdoctoral fellowships indicate successful competitive funding. Dr. Loh collaborates with several research groups including the Montreal Neurological Institute at McGill University and research teams at the University of Oxford. His work connects with broader initiatives like the collaborative resource platform for non-human primate neuroimaging, indicating participation in larger research networks focused on advancing primate neuroscience through shared resources and methodologies.

Andrea Faliniمشاهده پروفایل

استاد

• Advanced MR Techniques
• Neuro-oncology
• Degenerative Diseases
• +۳ مورد دیگر

Andrea Falini is a Full Professor of Neuroradiology at the Vita-Salute San Raffaele University (School of Medicine). He holds leadership roles including Head of the Neuroradiology Department at the Scientific Institute S. Raffaele Hospital and Head of the Advanced Diagnostic in Neuro-oncology Unit. His career spans clinical, academic, and administrative roles since 1991, with extensive experience in neuroradiology, neuro-oncology, and neuroimaging research. Education: MD (1986, University of Milan), PhD in Neurological Sciences (1989), and specialized training in Neurology and Radiology at leading institutions, including a visiting scholar position at UCSF (1996). Research interests focus on advanced MRI techniques, neuro-oncology, neurodegenerative diseases, and cognitive neuroscience. His work emphasizes functional MRI, diffusion tensor imaging, and clinical applications in glioma management and neurodegenerative disorders. Awarded the 1989 'De Visart' Prize and grants supporting his international collaborations. He has authored 218+ peer-reviewed articles, with an H-index of 40+, and actively contributes to academic committees and international conferences. Leadership roles include Vice-Director of the Neuroscience Division (2014–present) and coordination of the BraiMap Research Program. His academic teaching spans neuroradiology, biomedical engineering, and cognitive neuroscience courses.

• Computer Science
• Virtual Reality
• Scientific Visualization
• +۵ مورد دیگر

David H Laidlaw is a Professor of Computer Science at Brown University, specializing in virtual reality, scientific visualization, and medical imaging. His work spans interdisciplinary applications in neuroscience, biomedical research, and educational tools. Brown University Affiliation Department of Computer Science His research focuses on: Immersive visualization for complex data analysis Diffusion MRI and neuroimaging techniques Human-computer interaction in virtual environments 3D interaction methods for scientific exploration Collaborative visualization tools for multidisciplinary teams Recent trends in his publications highlight advancements in: Graph neural networks for biomedical data Memory-efficient segmentation algorithms Perceptual studies in VR environments Annotation and analysis of placental vasculature Technological innovations in foot dynamics research He teaches courses in virtual reality design and scientific visualization, including: CSCI 1370 - Virtual Reality Design for Science CSCI 1951S - Virtual Reality Software Review CSCI 1951T - Surveying VR Data Visualization Software CSCI 2370 - Interdisciplinary Scientific Visualization

Tanzil M. Arefinمشاهده پروفایل

استادیار

• Neuroimaging
• Neuroscience
• Brain Disorders
• +۵ مورد دیگر

Dr. Tanzil M. Arefin is an Assistant Professor of Neuroscience at the University of Rochester School of Medicine and Dentistry and Associate Director of the Preclinical Imaging Core at the Center for Advanced Brain Imaging and Neurophysiology (CABIN). His research focuses on developing neuroimaging techniques to study brain functions and microstructures in animal models of human disorders, including neurodegenerative and psychiatric illnesses. He holds affiliations with the Del Monte Institute for Neuroscience and the Neuroscience Ph.D. Program. **Education**: Ph.D., Neuroscience, University of Freiburg and University of Strasbourg (2017) M.Sc., Biomedical Engineering, Czech Technical University and University of Groningen (2012) B.Sc., Electrical and Electronic Engineering, Islamic University of Technology (2007) **Research Interests**: Dr. Arefin's lab employs multimodal MRI methodologies (resting-state fMRI, diffusion MRI, ASL perfusion MRI, MR spectroscopy) alongside optogenetics and chemogenetics to elucidate molecular mechanisms impairing brain plasticity. Current projects include studying cerebellar connectivity's role in non-motor behaviors and developing interventions for alcohol-dependent brains. **Awards**: Magna cum Laude, Summa Cum Laude, Erasmus Mundus Fellowships (both Doctoral and Masters). **Grants & Advising**: Not explicitly listed in texts, but lab activities suggest involvement in NIH-funded projects. Advising details are pending explicit student listings. **Lab & Affiliations**: Arefin Lab focuses on translational imaging tools. Affiliated with UR CABIN and URMC's Neuroscience programs. Location: 430 Elmwood Ave, Rochester, NY.

Christine Tardifمشاهده پروفایل

استادیار

• MRI-based Neuroimaging
• Quantitative MRI (qMRI)
• Biophysical Modeling
• +۸ مورد دیگر

Christine Tardif is an Assistant Professor in the Department of Biomedical Engineering and the Department of Neurology and Neurosurgery at McGill University. As head of the McConnell Brain Imaging Centre lab at the Montreal Neurological Institute, she develops advanced MRI techniques for in-vivo brain imaging, focusing on quantitative mapping of myelin and cortical microstructure. Her work spans methodological innovation (e.g., multi-modal biophysical modeling) and translational applications across preclinical (7 Tesla) and clinical (3 and 7 Tesla) systems. Undergraduate: B.Eng. in Computer Engineering, McGill University (2004) Master's: M.Sc. in Bioengineering, Imperial College London (2006) PhD: Biomedical Engineering, McGill University (2011) Her research explores myelin dynamics in health and disease, emphasizing its role in neural conduction, brain plasticity, and cognitive functions. The lab investigates dysmyelination in psychiatric disorders (e.g., bipolar disorder) and neurodegenerative conditions (e.g., multiple sclerosis) using relaxometry , magnetization transfer , and diffusion-weighted imaging . Recent methodological work includes 3D MERMAID sequences for motion-insensitive diffusion imaging and optimization of magnetization transfer saturation maps. Current projects integrate ultra-high field MRI with histological validation in preclinical models (e.g., marmoset brain sections), aiming to bridge microstructural metrics with macro-scale brain function. Applications span Alzheimer's disease risk assessment via white matter alterations, synaptic density mapping in psychosis, and cortical laminar differentiation studies.

Leanna Hernandezمشاهده پروفایل

استادیار

• Neuroimaging in Autism Spectrum Disorders
• Genetics of Psychiatric Disorders
• Sex Differences in Brain Development
• +۵ مورد دیگر

Leanna Hernandez, Ph.D., is Assistant Professor-in-Residence in the Department of Psychiatry and Biobehavioral Sciences at the David Geffen School of Medicine, University of California, Los Angeles. She directs the Hernandez Lab and can be reached at leannahernandez@ucla.edu . Her research integrates multimodal neuroimaging with large-scale genetics to uncover mechanisms underlying autism spectrum disorders, sex differences in brain development, and the role of immune–neurodevelopment pathways such as the complement system. Core themes include: Mapping how common genetic variation shapes brain structure and function across development. Identifying neural signatures that explain the female protective effect in ASD. Elucidating interactions between sleep physiology and brain maturation in youth. Across more than 40 peer-reviewed publications (2012-2023) she has leveraged data from the Adolescent Brain Cognitive Development (ABCD) Study, the GENDAAR Consortium, and multiple international biobanks, generating insights into white-matter microstructure, functional connectivity, and transcriptomic correlates of psychiatric traits. Scientific collaborations span UCLA, UC San Diego, University of Queensland, and the Busselton Health Study, reflecting an interdisciplinary approach that combines neuroimaging, genomics, lipidomics, and behavioral phenotyping. Dr. Hernandez’s laboratory website ( hernandezlabucla.org ) provides further resources, although specific trainees, grants, and awards are not detailed in the supplied text.

Anna Vilanovaمشاهده پروفایل

استاد

• Visual Analytics
• Explainable AI
• Biomedical Image Analysis
• +۶ مورد دیگر

Anna Vilanova is a Full Professor in Visual Analytics at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e), and is associated with the Electrical Engineering department's Signal Processing Systems. Previously, she served as Associate Professor at TU Delft (2013-2019) and Assistant Professor at TU/e (2002-2013). Her research focuses on Visual Analytics for high-dimensional data , explainable AI , and biomedical applications including Diffusion Weighted Imaging, 4D Flow, and Pangenomics. Education: Doctorate in Computer Graphics & Visualization (2001) Master in Computer Science (1997), Universitat Politècnica de Catalunya Research Highlights: Vilanova leads work on Visual Analytics systems for biomedical data, with recent publications in Diffusion MRI modeling , Tractography visualization , Explainable AI frameworks , and Pangenomic variant analysis . Her work bridges dimensionality reduction , uncertainty visualization , and medical imaging applications. Scientific Contributions: NWO-Veni grant (2005): "Visualization of global tensor information for diffusion tensor imaging" NWO-Aspasia grant (2013) Best Poster Award EuroVis (2025) Best Demo/Poster Awards (2022) Leadership & Service: Vilanova serves on the IEEE VIS Steering Committee , was EUROGRAPHICS President (2019-2022), and contributes to conferences like IEEE Visualization and EG-EuroVis . She co-founded the EAISI Health research initiative at TU/e.

• Tumor Microenvironment
• Magnetic Resonance Imaging (MRI)
• Quantitative Imaging Biomarkers
• +۵ مورد دیگر

Professor Sungheon Gene Kim holds a faculty position at the Weill Cornell Medicine Graduate School of Medical Sciences within the Department of Radiology . His research focuses on quantitative MRI methodology for oncological applications , particularly in breast cancer and head and neck cancer . Kim's lab develops advanced dynamic contrast-enhanced MRI (DCE-MRI) and diffusion MRI (dMRI) techniques to assess tumor microenvironment and treatment response . Key research areas include: Tumor vascular properties via 3D UTE-GRASP MRI Cellular microstructural analysis through POMACE framework Adipose-tissue cancer interaction via MR spectroscopic imaging His lab has received continuous funding from the National Cancer Institute (R01CA219964, UG3/UH3CA228699, R01CA160620). Recent publications demonstrate technical advancements in ultrafast MRI reconstruction , deep learning-enhanced perfusion analysis , and multi-parametric tumor characterization . Collaborations with the National Institutes of Health Quantitative Imaging Network have produced novel cellular water exchange rate measurements that correlate with patient survival outcomes .