جست‌وجوی استاد و پژوهشگر

Rolf Gruetterمشاهده پروفایل

استاد

• Magnetic Resonance Spectroscopy
• Neuroimaging
• Metabolic Modeling
• +۲ مورد دیگر

Rolf Gruetter is Full Professor at École polytechnique fédérale de Lausanne (EPFL), holding joint appointments in the Laboratory of Functional and Metabolic Imaging (School of Life Sciences) and the Teaching Conference (CCE). His research focuses on advanced biomedical imaging techniques including magnetic resonance spectroscopy and neuroimaging. He teaches courses on biomedical imaging fundamentals and neuroscience. Honors include the Young Investigator Award (1999), ESMRMB Fellowship (2011), and EPFL Teaching Award (2011). Editorial responsibilities span multiple neuroscience and imaging journals including Journal of Neuroscience Research and Frontiers in Neuroenergetics. Research leadership includes supervision of 30+ PhD students and postdoctoral researchers. Laboratory investigations center on brain energy metabolism, hypoglycemia neuroscience, and development of novel MR instrumentation and methodologies.

Hamied Haroonمشاهده پروفایل

پژوهشگر ارشد

• Magnetic Resonance Imaging (MRI)
• Neuroimaging
• Biomedical Imaging
• +۳ مورد دیگر

Hamied Haroon is a Research Fellow at the University of Manchester's Division of Psychology Communication and Human Neuroscience. His work focuses on advanced MRI techniques for studying brain structure and function in health and disease, particularly dementia and Parkinson's disease. He collaborates with Prof Geoff Parker and Dr Laura Parkes on the EPSRC-funded SIDD project, developing computational tools for biomedical imaging analysis. Haroon has held leadership roles in disability advocacy, including founding the National Association of Disabled Staff Networks and serving as Chair of the University's Disabled Staff Network (2007–2013). He holds a PhD in Magnetic Resonance Imaging Analysis (2005) and has contributed to over 40 peer-reviewed publications. Education : BSc Physics (UMIST, 1998), MSc Medical Physics (Manchester, 2000), PhD (Manchester, 2005) Research Themes : Diffusion MRI, Neuroimaging in dementia/Parkinson's, Cardiac MRI, MRI software development Teaching : Group Tutor in Manchester Medical School's MBChB program His research combines clinical MRI applications with methodological advancements, including tractography and deep learning approaches for neuroimaging analysis. He is a member of the International Society for Magnetic Resonance in Medicine and the Biomedical Imaging Institute at Manchester.

Tal Arbelمشاهده پروفایل

استاد

• Computer Vision
• Medical Image Analysis
• Artificial Intelligence in Healthcare
• +۴ مورد دیگر

Tal Arbel is a Professor in the Department of Electrical & Computer Engineering at McGill University, affiliated with the Centre for Intelligent Machines (CIM). Their research focuses on advancing AI-driven solutions in medical imaging, particularly in computer vision and neurology applications such as MRI analysis for multiple sclerosis and brain tumor studies. Key areas include developing robust algorithms for lesion segmentation, predictive modeling using multimodal data, and improving fairness and uncertainty quantification in medical AI systems. They are also involved in optimizing deep learning techniques for clinical workflows and addressing challenges in biomedical image analysis validation. Recent work emphasizes generative models (e.g., diffusion-based synthesis), reinforcement learning for medical image generation, and counterfactual explanations for interpretable AI. Their contributions span improving diagnostic accuracy, treatment prediction, and personalized medicine through computational imaging biomarkers.

• Generative Models
• Machine Reasoning
• AI Safety
• +۳ مورد دیگر

Dr. Chris Willcocks is an Associate Professor in the Department of Computer Science at Durham University, specializing in generative models and machine reasoning. He has authored over 35 peer-reviewed publications in top-tier venues including ICLR, TPAMI, CVPR, and IEEE TIFS. His research group has made significant contributions to theoretical generative modeling, including ∞-Diff for infinite-resolution synthesis and anomaly detection techniques like AnoDDPM. His research interests focus on theoretical generative modeling, machine reasoning frameworks, and AI safety. Key projects include diffusion models in Hilbert spaces, gradient origin networks, and applications in medical anomaly detection and security threat analysis. Teaching responsibilities include deep learning, reinforcement learning, and cybersecurity modules. Industry collaborations span multinational corporations (P&G, Unilever, Dyson) and public sector organizations (NHS, DSTL), with over 15 invited talks on AI ethics and cybersecurity. Awards include fellowship of the Higher Education Academy. Professional activities include serving as area chair for BMVC and admissions tutor for computer science. Willcocks supervises multiple postgraduate students including Jonathan Frawley and Rita Liu, and maintains a YouTube channel with educational content on deep learning.

Nyoman Kurniawanمشاهده پروفایل

پژوهشگر ارشد

• Magnetic Resonance Imaging (MRI)
• Neuroanatomy
• Medical Imaging
• +۴ مورد دیگر

Dr Nyoman Kurniawan is a Senior Research Fellow at the Centre for Advanced Imaging and Facility Manager for the Preclinical 16.4T Microimaging 9.4T MRI scanners at the Queensland Brain Institute, University of Queensland. His research focuses on advanced MRI techniques, including diffusion MRI in neurological disease models, 3D brain atlases, and applications in nephron and agricultural imaging. He holds a PhD in structural biology from The University of Queensland (2002). His expertise spans neuroimaging, developmental neurobiology, and translational MRI methodologies. Key contributions include developing MRI protocols for small animal studies, investigating spinal cord pathologies, and applying imaging to study brain connectivity in mouse models. His work bridges clinical and basic science, with applications in neurodegenerative diseases, trauma, and marine biology. Dr Kurniawan collaborates internationally on spinal cord MRI standards and has pioneered studies on octopus brain structure and octopus mating behavior. He also explores the effects of vitamin D deficiency on neuroanatomy and leverages deep learning for motion correction in kidney imaging. His lab contributes to open-access neuroimaging data and collaborates with institutions globally to advance imaging reproducibility.

Sarah Londonمشاهده پروفایل

دانشیار

• Neuroscience
• Neural Plasticity
• Learning and Memory
• +۲ مورد دیگر

Sarah London is an Associate Professor at the University of Chicago's Department of Psychology. She received a BA in Biology and Psychology from Middlebury College and a PhD in Neuroscience from UCLA, followed by postdoctoral research at University of Illinois Urbana-Champaign. Her research examines neural mechanisms of developmental learning using zebra finch songbirds as models. Key interests include experience-dependent neural plasticity, sensitive periods in development, and molecular/genomic correlates of behavior, with implications for human speech acquisition and neurodevelopmental disorders. Publications focus on autism spectrum disorder, Down syndrome neurodevelopment, advanced MRI methodologies, and computational neuroimaging approaches. Recent work investigates white matter development, functional connectivity patterns, and early behavioral biomarkers in neurodevelopmental conditions. Leads the London Lab studying neurogenomics of learning potential and critical period mechanisms.

• Autism Spectrum Disorders
• Neuroscience
• Cognitive Psychology
• +۳ مورد دیگر

Dr. Nazia Jassim is a Researcher in the Department of Psychology at the University of Cambridge. Her work focuses on autism spectrum disorders, sensory perception, and neuroimaging. She has contributed to studies investigating perceptual cohesion in autism, oxytocin’s role in emotional face processing, and brain function in individuals with autism. Her research employs advanced neuroimaging techniques such as fMRI and 7T imaging, exploring both social and non-social sensory processing. Key projects include the 'STREAM' protocol examining circadian rhythms, sleep, and sensory reactivity in autism. Dr. Jassim’s interdisciplinary approach bridges cognitive neuroscience and clinical psychology, with findings published in high-impact journals. No personal email is listed, and her role does not involve teaching or formal student supervision.

Siawoosh Mohammadiمشاهده پروفایل

پژوهشگر ارشد

• Diffusion MRI
• Structural MRI
• MRI Reconstruction
• +۵ مورد دیگر

Siawoosh Mohammadi serves as a Senior Postdoctoral Research Fellow at the Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf. His research focuses on advanced MRI methodologies with expertise spanning diffusion, structural, and reconstruction techniques. His primary research interests include: Diffusion MRI: Modeling and correction of artefacts, sequence optimization, bio-physical modeling from macro- to micro-structure Structural MRI: Artefact correction and bio-physical modeling of proton density, myelin, and iron content MRI reconstruction: K-space to image-space artefact correction and complex data modeling Current projects on high-resolution spinal-cord DTI, Kurtosis Diffusion Imaging, and multi-parameter mapping integration Mohammadi holds significant recognition through a DFG (German Research Council) Research Fellowship and is the author of the ACID toolbox for diffusion MRI pre-processing within the SPM package. His professional trajectory includes postdoctoral roles at UCL's WTCN and University of Münster, with doctoral training in quantitative Diffusion Tensor Imaging. DFG Research Fellowship As an enabling activity, he developed the ACID toolbox – a model-based academic software toolkit for diffusion MRI artefact correction, DTI index estimation, and spatial normalization, fully integrated into SPM's batch system. His academic foundation includes a PhD in quantitative DTI from University of Münster (2009) and an MSc in theoretical physics from University of Hamburg (2002).

Esra Abaci Turkمشاهده پروفایل

استادیار

• MRI Physics
• Placental Imaging
• Fetal MRI Safety
• +۲ مورد دیگر

Esra Abaci Turk, PhD, is Assistant Professor of Pediatrics at Harvard Medical School and Associate Scientific Researcher at Boston Children's Hospital's Fetal Neonatal Neuroimaging and Developmental Science Center. Her research focuses on developing advanced MRI techniques for placental function assessment and fetal MRI safety protocols. Research interests include motion mitigation in fetal imaging, placental BOLD MRI analysis, and developing computational methods for fetal organ assessment. Her work integrates physics-based MRI innovation with clinical applications in high-risk pregnancies. Dr. Turk's publications demonstrate consistent focus on improving fetal and placental imaging through novel acquisition methods and computational approaches including AI-enhanced super-resolution, 3D motion tracking, and volumetric modeling techniques.

Dan Ruanمشاهده پروفایل

استاد

• Medical Imaging
• Radiation Oncology
• Machine Learning in Medical Physics
• +۳ مورد دیگر

Dan Ruan is a Professor-in-Residence in the Radiation Oncology department at the School of Medicine, University of California Los Angeles . His research focuses on advanced medical imaging techniques, radiation therapy optimization, and machine learning applications in medical physics. Research Interests: Medical Imaging, Radiation Oncology, Machine Learning, Image Reconstruction, Radiomics, and 4D MRI/CT Techniques Recent Publications highlight his work in deep learning for MRI acceleration, clustering methods for toxicity prediction, and innovative approaches in diffusion MRI reconstruction. His studies often integrate computational modeling with clinical applications in oncology and cardiology. Scientific Collaborations span multiple institutions, with frequent co-authorships in journals like Medical Physics , Physics in Medicine and Biology , and Journal of Magnetic Resonance Imaging .

• Deep Learning
• Medical Imaging
• Machine Learning
• +۶ مورد دیگر

Kyung Hyun Sung is a Professor in the Department of Radiological Sciences at the University of California, Los Angeles (UCLA) School of Medicine. His research focuses on integrating Deep Learning, Artificial Intelligence, and Medical Imaging to advance diagnostic and therapeutic applications in Prostate Cancer and Obstetrics. PhD in Electrical Engineering, University of Southern California (2008) Postdoctoral Training in Radiology, Stanford University (2010) Dr. Sung's work spans Medical Imaging, Magnetic Resonance Imaging (MRI), and Machine Learning, with specific emphasis on: Prostate Cancer Detection and Segmentation Quantitative MRI for Biomarker Development AI-Driven Image Enhancement and Radiomics Placental Assessment in Pregnancy High-Resolution and Accelerated MRI Techniques His recent publications highlight advancements in Deep Learning for Prostate Cancer Classification, Uncertainty-Aware Imaging, and Racial Disparities in MRI Biomarkers. He has contributed to open science initiatives like the ISMRM-OSIPI Dynamic Contrast-Enhanced Challenge. Scientific awards include the Suzanne Eaton Memorial Prize and Taylor M. Brown Memorial Award. Dr. Sung's research is funded by NIH grants R01CA272702 and R01CA248506, focusing on racial disparities and AI integration in prostate cancer classification.

Gawain Hammondمشاهده پروفایل

استاد بالینی

• Veterinary Radiology
• Diagnostic Imaging in Companion Animals
• Small Animal Clinical Sciences
• +۳ مورد دیگر

Dr. Gawain Hammond is a Clinical Professor in Small Animal Diagnostic Imaging at the University of Glasgow. He specializes in veterinary radiology and imaging techniques, particularly MRI and CT applications in companion animals. His work focuses on neurological, oncological, and orthopedic imaging challenges in dogs and cats. Department: Department of Small Animal Clinical Sciences Research interests include diagnostic imaging of neurologic disorders, oncological lesions, and musculoskeletal abnormalities. Over 60 peer-reviewed articles highlight his contributions to imaging advancements in veterinary medicine. Key areas include MRI features of brain tumors, CT analysis of nasal masses, and ultrasound assessment of teat canal morphology in livestock. He has contributed to textbooks on fracture repair, temporomandibular joint imaging, and abdominal imaging techniques. His work frequently addresses imaging challenges in small animals, such as gliomatosis cerebri, emphysematous gastritis, and spinal cord injuries. He has presented at veterinary neurology symposia and contributed to studies on sighthound vertebral venous system abnormalities. Grant: Reconstructed computed tomography for elbow incongruency diagnosis in dogs (Petsavers, 2004-2005).

• Neuroimaging
• Magnetic Resonance Imaging
• Cardiovascular Imaging
• +۳ مورد دیگر

Christopher Rodgers serves as a Visiting Scientist and Wellcome Trust Sir Henry Dale Fellow at the University of Oxford, affiliated with the Oxford Centre for Clinical Magnetic Resonance Research and Merton College. His research focuses on advancing ultra-high-field (7 Tesla) magnetic resonance imaging techniques for clinical neuroscience and cardiovascular applications, particularly in cerebrovascular and metabolic studies. His primary research interests encompass neuroimaging, cardiovascular imaging, and 7T MRI methodology development. Specific expertise includes cerebrovascular disease analysis (lenticulostriate arteries, Charcot-Bouchard aneurysms), cardiac metabolism mapping, and neurochemical marker identification. His work bridges engineering innovation with clinical neurology and cardiology through advanced MRI protocol development. Recent publications demonstrate a cohesive research trajectory in pushing 7T MRI boundaries across neurological and cardiovascular domains. Key themes include deep learning applications for vascular morphology, high-resolution aneurysm visualization, metabolic imaging techniques, and epilepsy evaluation protocols. These studies collectively advance diagnostic capabilities for cerebrovascular disorders and cardiac pathologies. Scientific Awards: Wellcome Trust Sir Henry Dale Fellowship As a Wellcome Trust Fellow, Rodgers leads independent research within the Neubauer Group, driving innovation in clinical MRI. His work involves securing competitive funding for high-field imaging projects and collaborating with multidisciplinary teams across Oxford's neuroscience and cardiology departments to translate technical advances into clinical practice. Rodgers operates within the Oxford Centre for Clinical Magnetic Resonance Research, leveraging specialized 7T MRI infrastructure. His work integrates with Merton College's academic community while collaborating extensively with the Neubauer Group on developing next-generation imaging protocols for neurological and cardiovascular applications.

Kristīne Šneidereمشاهده پروفایل

پژوهشگر

• Cognitive Disorders
• Neuroscience
• Psychology
• +۳ مورد دیگر

Kristīne Šneidere is a leading researcher at Rīga Stradiņš University, actively contributing to neuroscience and psychology with a focus on cognitive disorders, aging, and neuroimaging techniques. She leads projects such as the development of the Riga Cognitive Assessment Task (RiTa) and investigates the role of motor reserve in cognitive dysfunction. Active in national research programs (Latvian Council of Science, EEZ/Norway grants) Collaborates on international initiatives like COST Action 20104 Her research centers on MRI-based biomarkers for cognitive decline, P300 ERP components, and lifestyle interventions for healthy aging. She has authored 41 research outputs, including articles in Frontiers in Psychology and Diagnostics , and contributed to datasets on brain imaging. Recent publications highlight her work on: High-resolution MRI analysis of amygdala atrophy in dementia Development of cognitive assessment tools Neurophysiological markers (P300) in aging research She has received the Young Scientist in Psychology award (2020) and actively participates in peer-review processes for journals like PLOS Biology and Frontiers in Psychology . Her media engagements include public education on aging and cognitive health in outlets like Tavu smadzeņu mīļākais dzīvesveids and Pētniece: Novecošanu jābeidz uzskatīt par kaut ko sliktu .

Federico de Martinoمشاهده پروفایل

استاد

• Neuroimaging
• Auditory Perception
• Machine Learning
• +۳ مورد دیگر

Federico de Martino is a Full Professor at Maastricht University's Faculty of Psychology and Neuroscience (FPN), specializing in Sensory Circuits and Neuroimaging. He holds an honorary researcher position at the Center for Magnetic Resonance Research (CMRR) in Minneapolis, USA. His research integrates computational models with high-resolution neuroimaging techniques to study auditory perception and predictive coding in the brain. Education: Graduated in Electronic Engineering (cum laude) from Sapienza University of Rome (2003), earned a PhD in Cognitive Neuroscience from Maastricht University (2008). Career milestones include roles as Post-Doctoral Fellow (2008-2011), Research Associate at CMRR (2009-2012), Assistant Professor (2011-2017), and Associate Professor (2017-2022) at FPN. Research interests focus on ultra-high field MRI (7T+), mesoscopic neural computations, and the functional organization of auditory pathways. Key projects include mapping auditory circuits at sub-millimeter resolution and investigating vascular underpinnings of fMRI signals. Collaborations span institutions like CMRR, University of Glasgow, and Max Planck Institute. Teaching roles include coordinating fMRI data analysis courses at FPN and the Maastricht Science Program. He co-chairs the Maastricht Brain Imaging Center (MBIC) Graduate School and leads FPN's MRI user support group. Active in science outreach as a founding member of the Maastricht Young Academy (MYA) and co-chair of the Growing Up in Science (GUS) initiative. Grants include an NWO VIDI grant (auditory pathway mapping), NIH Brain Initiative funding (laminar fMRI), and an ERC Consolidator grant (predictive listening). Recent publications emphasize high-resolution auditory imaging, predictive coding, and methodological advancements in neuroimaging.