Find Academic Supervisors

Brad Sutton is a Professor of Bioengineering at the University of Illinois Urbana-Champaign and Technical Director of the Biomedical Imaging Center at Beckman Institute. He holds affiliate roles in the Neuroscience Program, Department of Electrical and Computer Engineering, and is a Health Innovation Professor at the Carle Illinois College of Medicine. His roles also include fellowship positions with the National Center for Supercomputing Applications and the CZ Biohub Chicago. Education: Ph.D. in Biomedical Engineering from the University of Michigan (2003). Research Interests: Focus on advanced MRI techniques for structural and functional brain imaging, including diffusion-weighted imaging, dynamic imaging, and neuromuscular coupling studies. His work emphasizes multi-scale bioimaging to understand brain function across interventions, aging, and disease. Publications: Over 180 peer-reviewed articles in 2025-2024 highlight innovations in MRI technology and applications in neuroscience, including breakthroughs in laminar fMRI specificity, myelin development modeling, and Alzheimer’s biomarker studies. Recent work extends to clinical applications like aortic imaging automation and mixed reality training tools. Awards: AIMBE and ISMRM Fellowships (2017/2024), Abel Bliss Scholar (2014-), and over 9 patents in imaging techniques. Labs & Teams: Leads the Magnetic Resonance Functional Imaging Lab. Collaborates with interdisciplinary teams across engineering, medicine, and computational science to advance imaging technologies and their clinical translation.

• Biomedical imaging
• Diffusion weighted imaging
• Dynamic imaging
• +7 more

Solomon G. Diamond is an Associate Professor of Engineering at Dartmouth College's Thayer School of Engineering, serving as Co-Director of the Design Initiative at Dartmouth. He holds degrees from Dartmouth (AB 1997, BE 1998) and Harvard (SM 2001, PhD 2004). His research focuses on biomedical imaging, functional neuroimaging, and magnetic nanoparticle imaging, with emphasis on diagnostic technologies and medical device development. He has received awards including the 2023 Outstanding Service Award and the 2002 Derek Bok Teaching Award. Research projects include neurovascular coupling studies, clinical optical-electric probes, and magnetic nanoparticle imaging. He co-founded Lodestone Biomedical, a medtech company advancing nanoparticle-based biosensors. His work bridges engineering and medicine, with notable contributions to magnetic nanoparticle characterization and imaging array systems. He teaches courses like ENGS 90 (Engineering Design Methodology) and ENGS 29 (Computer-Aided Design & Kinematics). Recent work includes a 2024 study on salt concentration effects in magnetic nanoparticle biosensors with PhD candidate Gabby Moss. He holds patents for technologies like magnetic susceptibility tomography and in-bed exercise machines. His interdisciplinary collaborations span biomedical engineering, materials science, and clinical diagnostics.

• Biomedical Imaging
• Functional Neuroimaging
• Magnetic Nanoparticle Imaging
• +3 more

Professor David Carmichael is a distinguished academic at King's College London , affiliated with the School of Biomedical Engineering & Imaging Sciences and the Department of Biomedical Computing . His research focuses on Magnetic Resonance Imaging (MRI) Physics , EEG-fMRI integration , and epilepsy neuroimaging , with a particular emphasis on mapping epileptogenic networks and optimizing MRI safety for concurrent neurophysiological recordings. Education : PhD in Medical Physics (UCL, 2004), MSci in Physics (UCL, 2000). External Role : Honorary Reader at UCL Great Ormond Street Institute of Child Health. His research interests span advanced neuroimaging techniques, including 7T MRI for pediatric epilepsy, quantitative susceptibility mapping to detect cortical abnormalities, simultaneous EEG-fMRI safety protocols, network-guided neuromodulation for treatment optimization. Recent publications highlight his work on ultra-high field MRI in drug-resistant pediatric cohorts, RF-induced heating safety during combined EEG-fMRI, image quality transfer for low-field MRI in developing regions, motion correction strategies in pediatric scans. He leads critical projects such as 7 Tesla Sodium MRI for Epilepsy (MRC-funded) and Minimal Motion MRI Systems (NIHR-funded), while contributing to global epilepsy research through the King’s Epilepsy Research Collective (KERC) .

• Magnetic Resonance Imaging (MRI) Physics
• EEG-fMRI Integration
• Epilepsy Research
• +3 more

Avery Berman is an Assistant Professor in the Department of Physics at Carleton University and a Scientist at the University of Ottawa Institute of Mental Health Research (IMHR) at The Royal. His work focuses on advancing functional MRI (fMRI) techniques for high-resolution imaging of brain activity and physiology, with applications in neuroscience and mental health disorders. PhD in Biomedical Engineering and MSc in Medical Radiation Physics from McGill University Postdoctoral research at Harvard Medical School and the Martinos Center for Biomedical Imaging Research Interests include: High-resolution fMRI at 7 Tesla Biophysical modeling of vascular networks Quantitative biomarkers for oxygen metabolism PET-MRI hybrid imaging systems Neurovascular coupling in mental illness Scientific Awards include: NSERC Canada Graduate Scholarship (Master's) CIHR Canada Graduate Scholarship (Doctoral) CIHR Postdoctoral Fellowship (top 10/600 applicants) NSERC Postdoctoral Fellowship (top Physics section recipient) Research Funding from NSERC, CFI, and institutional support from Carleton University and IMHR. His lab develops the open-source BOLDsωimsuite software for fMRI signal modeling and collaborates with Canada-wide vascular training programs.

• Medical Physics
• Functional Neuroimaging
• Biomedical Engineering
• +5 more

Benjamin M. Ellingson is Professor of Radiological Sciences, Psychiatry, and Neurosurgery at UCLA's David Geffen School of Medicine. He directs the Brain Tumor Imaging Laboratory (BTIL) and co-directs the Center for Computer Vision and Imaging Biomarkers. His research focuses on developing advanced MRI/PET biomarkers for brain tumor diagnosis, characterization, and therapeutic response assessment. Dr. Ellingson has co-authored over 250 peer-reviewed articles and leads multiple NIH/DoD grants validating imaging in multicenter trials. Education: BS Biomedical Engineering, Milwaukee School of Engineering (2003) MS Biomedical Engineering, Marquette University (2005) PhD Functional Imaging - Biomedical Engineering, Marquette University & Medical College of Wisconsin (2008) Fellowship in Radiology/MRI Physics, Medical College of Wisconsin (2010) His research integrates quantitative imaging, artificial intelligence, and metabolic profiling to address challenges in neuro-oncology. Key interests include: Development of sodium/pH-weighted MRI for tumor acidosis mapping AI-driven super-resolution and artifact reduction techniques Diffusion/perfusion phenotyping for immunotherapy response prediction Multimodal biomarker validation in clinical trials Recent publications demonstrate a dominant focus on glioma imaging innovations, particularly: Advanced diffusion/perfusion MRI techniques for treatment response assessment Integration of AI for image synthesis and artifact correction Novel metabolic imaging approaches targeting glycolysis and pH dynamics Standardization of response criteria (RANO) for clinical trials Awards: ISMRM Young Investigator Award (2010) ACRIN Young Investigator Award (2012) Johnny Mercer Foundation Award (2013) SNO Excellence in Neuroimaging (2019) He leads major grants including: DoD CDMRP projects targeting EGFR signaling and multinuclear MRI (2021-2028) NIH R01 grants for MR-PET imaging of glioblastoma glycolysis (2023-2028) UCLA Brain Tumor SPORE Neuro-Imaging Core (2017-2027) His laboratory develops imaging protocols for national/international clinical trials and maintains industry partnerships for biomarker implementation.

• Neuro-oncology
• Imaging Biomarkers
• Magnetic Resonance Imaging
• +3 more

Kathleen M. Schmainda, PhD, is a Professor in the Department of Biophysics at the Medical College of Wisconsin (MCW). She joined the faculty in 2002 and leads a translational brain tumor imaging research laboratory focused on developing MRI biomarkers for brain tumor diagnosis and treatment monitoring. Her work has contributed to national consensus protocols for perfusion MRI in brain tumors and clinical trial leadership roles. Education: BSE in Biomedical Engineering, Marquette University (1986) MSEE in Electrical Engineering, MIT (1989) PhD in Medical Engineering, Harvard-MIT (1993) Postdoctoral Fellowship in MRI, Massachusetts General Hospital (1993-1995) Research Interests: Dr. Schmainda’s lab develops MRI methods to assess tumor angiogenesis, invasion, and perfusion. Key areas include: Cerebral blood volume (CBV) and flow (CBF) measurements Diffusion MRI for tumor progression tracking Anti-angiogenic therapy evaluation Integration of machine learning with MRI Publications & Awards: Over 100 peer-reviewed articles and patents, including awards such as the AIMBE Fellowship, Dean’s Award for Clinical Research, and Lucien Levy Best Research Article Award. Her work has been recognized for advancing MRI standards in neuro-oncology. Lab & Teams: Collaborations include the MCW Neuro-Oncology team and industry partnerships. Current lab members include graduate students Robert Wujek and Casey Zoss, along with research staff like Mona Al-Gizawiy and Melissa Prah.

• Magnetic Resonance Imaging (MRI)
• Brain Tumor Research
• Neuro-Oncology
• +4 more

Full Professor at Erasmus University Medical Center (Erasmus MC) in the Department of Radiology & Nuclear Medicine. Specializes in advanced imaging techniques for neurological disorders, particularly brain tumors. Her research focuses on magnetic resonance imaging (MRI), functional ultrasound, and AI-driven diagnostic methods in neuro-oncology. Dr. Smits has supervised 13 academic works and contributed over 255 publications, including high-impact studies on tumor progression differentiation and brain metastasis analysis. Her work bridges clinical practice and cutting-edge imaging technologies. Research interests include: Magnetic Resonance Imaging, Neuro-Oncology, Brain Tumor Imaging, and Development of Innovative Diagnostic Tools. Key contributions involve improving diagnostic accuracy through perfusion MRI and functional ultrasound, as well as integrating deep learning into medical imaging workflows. Major contributions: Mobile functional ultrasound brain imaging, data-centric AI for brain metastasis analysis Publications focus on MRI techniques for glioblastoma, dynamic susceptibility contrast imaging, and clinical applications Active in multidisciplinary collaborations, contributing to both academic and clinical advancements in neurological imaging.

• Magnetic Resonance Imaging
• Neuro-Oncology
• Brain Tumor Imaging
• +3 more

Dr. Felix Werner Wehrli is a Professor of Radiologic Science at the Perelman School of Medicine, University of Pennsylvania. He serves as Director of the Laboratory for Structural, Physiologic and Functional Imaging and is a member of the Department of Radiology's Research Executive Committee. Education: MS (1967) and PhD (1970) in Chemistry from Swiss Federal Institute of Technology Research focuses on quantitative MRI for tissue physiology characterization, with applications in cerebral oxygen metabolism , preclinical vascular disease , and bone matrix properties . Recent publications highlight advancements in time-resolved MRI oximetry for cerebral and renal metabolism, bone-selective imaging for craniofacial surgery, and deep-learning segmentation techniques. His lab develops patient-specific models for hip fracture prediction and investigates e-cigarette aerosol impacts on vascular systems.

• Magnetic Resonance Imaging (MRI)
• Tissue Physiology and Metabolism
• Vascular Disease
• +5 more

Fatemehsadat Arzanforoosh is a Researcher at the Department of Radiology & Nuclear Medicine, Erasmus University Medical Center. Her doctoral thesis (2024) focused on glioma oxygenation and vasculature using MRI techniques. Her research interests include advancing MRI applications for brain tumor characterization, particularly gliomas and gangliogliomas. She investigates tumor microvasculature, hypoxia, and vascular dynamics through interdisciplinary approaches. Collaborations involve intraoperative Doppler ultrasound and histology correlation. Her work bridges clinical MRI with neuro-oncology, aiming to improve preoperative tumor assessment and treatment strategies. Key research areas include perfusion MRI, BOLD imaging, and dynamic susceptibility contrast techniques. She contributes to both experimental and review articles, highlighting MRI's role in understanding glioma biology and vascular pathophysiology. Her studies emphasize translational applications, such as clinical oxygen extraction fraction metrics. Current efforts focus on refining MRI protocols for tumor hypoxia detection and vascular analysis. No scientific awards are explicitly mentioned in the provided texts. She has advised no listed students but collaborates with multidisciplinary teams in neuroimaging and oncology. Her work is part of Erasmus MC's broader Radiology & Nuclear Medicine initiatives, contributing to advancements in diagnostic and therapeutic strategies for brain tumors.

• Magnetic Resonance Imaging (MRI)
• Neuro-Oncology
• Tumor Vasculature
• +3 more

Whitney B. Pope, M.D., Ph.D., is a Professor in the Department of Radiological Sciences (Neuroradiology) at the David Geffen School of Medicine, University of California, Los Angeles. Her research focuses on neuro-oncology, glioblastoma, and advanced MRI techniques for tumor characterization and treatment response assessment. University: University of California, Los Angeles School: David Geffen School of Medicine Department: Radiological Sciences (Neuroradiology) Dr. Pope’s work explores the application of diffusion MRI, perfusion imaging, and molecular MRI techniques to predict outcomes in glioma patients. She has contributed extensively to understanding tumor heterogeneity, metabolic imaging, and the integration of AI in neuroimaging analysis. Recent publications highlight her research on synthetic perfusion MRI, T2-FLAIR mismatch quantification, and AI-driven tumor response assessment. Her studies often bridge imaging protocols with genetic and metabolic tumor profiling to optimize clinical decision-making.

• Neuro-oncology
• Glioblastoma
• Magnetic Resonance Imaging (MRI)
• +3 more

Dr. Nikae te Moller is an Assistant Professor at the Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University. Her research focuses on equine musculoskeletal health , combining gait analysis (kinematics/kinetics), osteoarthritis progression in equine joints, and longitudinal data analysis . She employs advanced techniques like facial electromyography (fEMG) and R programming for statistical analysis, with applications in science communication (e.g., public dance demonstrations of joint dynamics). Expertise in equine cartilage injury models (blunt vs. sharp lesions) Developed equine carpal groove model for osteoarthritis studies Innovator in optical coherence tomography (OCT) and near-infrared spectroscopy for cartilage assessment Recent publications (2024-2023) emphasize quantitative MRI , micro-CT , and infrared spectroscopy for early detection of cartilage defects. Her work bridges regenerative medicine and equine locomotion , with collaborations across biomedical engineering (e.g., 3D T1 relaxation time studies) and veterinary science. Awards include the Public Engagement Seed Fund . Current projects involve objective pain quantification and biomechanical response to treadmill exercise in horses.

• Gait analysis (kinematics and kinetics)
• Osteoarthritis
• Longitudinal Data Analysis
• +5 more

Shalini Sharma, PhD, serves as a Research Fellow in the Department of Diagnostic Radiology and Nuclear Medicine, specializing in molecular imaging probe development and radiopharmaceutical applications. Her work bridges nuclear medicine, nanotechnology, and therapeutic monitoring with emphasis on translational research. Her primary research domains include Molecular Imaging, Radiopharmaceuticals, Nanomedicine, Theranostics, Nuclear Medicine, Neuroimaging, and Infection Imaging. She pioneers novel PET tracers for tracking viral vectors, differentiating bacterial infections from sterile inflammation, and monitoring cell-based therapies. Her methodology integrates radiochemistry, nanomaterial engineering, and in vivo validation to address challenges in blood-brain barrier penetration, neuroinflammation imaging, and infection diagnostics. Analysis of her 2019-2025 publications reveals consistent innovation in zirconium-89 radiometal applications for tracking AAV vectors, white blood cells, and stem cells. Key thematic threads include: (1) blood-brain barrier modulation strategies for neurotherapeutics, (2) dual-modality nanoparticle systems for combined imaging and antibacterial action, and (3) platform technologies for real-time monitoring of alpha radionuclide therapy. Her work demonstrates exceptional technical breadth across radiochemistry, nanomaterial design, and preclinical validation.

• Molecular Imaging
• Radiopharmaceuticals
• Nanomedicine
• +4 more

Dr. Xuan Vinh To is a Postdoctoral Research Fellow at the Queensland Brain Institute, The University of Queensland. His research focuses on neuroimaging techniques and their application to traumatic brain injury (TBI), neuroinflammation, and neurodegenerative diseases such as Alzheimer's. He holds a PhD in Neuroscience from The University of Queensland (2021). Education: PhD in Neuroscience, The University of Queensland, 2021 Research Interests: Development of advanced MRI techniques for TBI assessment Neuroinflammation biomarker discovery Functional connectivity analysis in aging and disease Preclinical imaging in rodent models Machine learning applications in neuroimaging Publications Trends: His work shows strong focus on translational neuroimaging, particularly in TBI pathophysiology and recovery mechanisms. Recent studies explore MRI biomarkers linking inflammation, structural changes, and cognitive outcomes in both clinical and preclinical settings. Data Resources: He has contributed multiple datasets on TBI neuroimaging through platforms like The University of Queensland's data repository, enabling reproducible research in rodent models and clinical TBI cohorts.

• Neuroimaging
• Traumatic Brain Injury (TBI)
• Neuroinflammation
• +5 more

Dee Wu is an Associate Professor and Chief of Technical Application and Translational Research Development at the University of Oklahoma Health Sciences Center (OUHSC). He holds advanced degrees in Mathematics, Systems Engineering, and Biomedical Engineering from Case Western Reserve University. His research focuses on medical physics, particularly in MRI techniques for tumor imaging, radiation therapy planning, and functional brain imaging. He has contributed to advancements in tumor delineation algorithms, partial volume correction in spectroscopic imaging, and inter-observer variability in tumor delineation. His work bridges clinical applications and technical innovation in medical imaging. Education: B.S., Mathematics, Case Western Reserve University M.S., Systems Engineering, Case Western Reserve University M.S., Biomedical Engineering, Case Western Reserve University Ph.D., Biomedical Engineering, Case Western Reserve University Research Interests: Dr. Wu’s expertise includes medical imaging technologies such as MRI and fMRI, radiation oncology treatment planning, tumor response modeling, and artifact correction methods. He has developed methodologies for improving tumor delineation accuracy and optimizing contrast-enhanced imaging techniques. His translational research emphasizes bridging computational algorithms with clinical outcomes in oncology and neurology. Key Contributions: His publications highlight advancements in tumor imaging biomarkers, image registration techniques, and multi-center imaging standardization. He has also contributed to educational initiatives in computational science for non-experts. His role as Chief of Technical Application underscores his commitment to translating research into practical tools for medical practice.

• Medical Imaging
• Radiation Therapy
• Biomedical Engineering
• +7 more

Steven Yong Cen, PhD is a Professor of Research in Radiology, Neurology and Radiation Oncology at the Keck School of Medicine of the University of Southern California. His office can be reached at +1 323 442 1570 and his professional email is cen@usc.edu. Dr. Cen's research spans multiple domains within medical imaging, with particular focus on radiomics, neuroimaging, and artificial intelligence applications in medicine. His work encompasses advanced MRI techniques, CT imaging analysis, Alzheimer's disease diagnostics, cancer imaging (particularly renal cell carcinoma), and stroke imaging. He has pioneered research in robotic surgery feedback systems and human-AI collaboration for surgical training. Analysis of Dr. Cen's recent publications reveals a strong trend toward integrating artificial intelligence with medical imaging to improve diagnostic accuracy and treatment outcomes. His work bridges quantitative imaging biomarkers, neurodegenerative disease assessment, and surgical education technology. The interdisciplinary nature of his research connects radiology, neurology, oncology, and computer science to address critical challenges in modern medicine. Dr. Cen has made significant contributions to understanding blood-brain barrier function in aging, developing AI-assisted surgical training systems, and establishing quantitative imaging biomarkers for neurological conditions. His work on health disparities in stroke treatment highlights his commitment to addressing inequities in healthcare delivery.

• Medical Imaging
• Radiomics
• Neuroimaging
• +7 more