جست‌وجوی استاد و پژوهشگر

Michael Garwoodمشاهده پروفایل

استاد

• Magnetic Resonance Imaging (MRI)
• Medical Physics
• Biomedical Engineering
• +۳ مورد دیگر

Michael Garwood is a Professor in the Department of Radiology at the University of Minnesota and serves as Associate Director of the Center for Magnetic Resonance Research (CMRR). He is also a faculty member in the PhD Program in Medical Physics and a preceptor for the Medical Scientist Training Program (MSTP), which trains combined MD/PhD students. His work focuses on advancing MRI technology, nanoparticle applications, and cryobiology. Garwood holds an office at the CMRR located at 2021 6th Street SE, Minneapolis, MN 55455. Research interests include optimizing MRI hardware design (e.g., ultra-compact magnets and wearable coils), developing novel MRI pulse sequences (e.g., SWIFT and DYNAMITE), and exploring ethical frameworks for deploying portable MRI systems globally. His projects often integrate physics-driven AI solutions to enhance imaging speed and accessibility. Recent work addresses challenges in nanoparticle quantification, cryopreservation of organs, and reducing MRI costs through low-field systems. Garwood’s contributions span both technical innovations (e.g., STAR MRI) and interdisciplinary collaborations bridging engineering, medicine, and public policy. Publications emphasize ethical considerations in field research, MRI signal processing, and medical device development. He advises trainees in the MSTP and CMRR, fostering the next generation of medical physicists and clinicians.

Geoffrey Ghoseمشاهده پروفایل

استاد

• Neuroscience
• Neurophysiology
• Cognitive Science
• +۳ مورد دیگر

Geoffrey Ghose, PhD is a Professor in the Department of Neuroscience at the University of Minnesota Medical School. His research focuses on understanding the neural mechanisms underlying perception, attention, and sensory processing in the brain. He employs advanced neuroimaging techniques like fMRI and electrophysiological recordings in combination with computational modeling to investigate how sensory information is processed across cortical hierarchies. Key research themes include the role of alpha oscillations in visual processing, the impact of attention on auditory and visual cortex activity, and the optimization of neuroimaging methodologies. His work bridges basic neuroscience with translational applications in neurotechnology and perceptual learning strategies. He has pioneered techniques for analyzing task-dependent cortical activity profiles and refining fMRI sensitivity without sacrificing spatiotemporal precision. Recent investigations explore the interplay between top-down microcircuitry and perceptual decision-making, as well as the neurophysiological bases of perceptual ambiguity resolution. His studies utilize both human and non-human primate models, with a particular focus on visual and auditory cortical areas such as V4, MT, and auditory cortex regions. Ghose's contributions have advanced understanding of how neural synchrony and microcircuit dynamics shape sensory perception and cognitive functions.

Gregory Metzgerمشاهده پروفایل

استاد

• Medical Physics
• Magnetic Resonance Imaging (MRI)
• Radiology
• +۳ مورد دیگر

Gregory Metzger, PhD, is a Professor in the Department of Radiology at the University of Minnesota, School of Medicine. He serves as a faculty member in the PhD Program in Medical Physics and a preceptor in the Medical Scientist Training Program (Combined MD/PhD). His research focuses on advancing MRI technologies, particularly at ultrahigh fields (e.g., 7T and 10.5T), RF coil design, and applications in prostate cancer imaging, neuroimaging, and clinical diagnostics. Dr. Metzger leads the Center for Magnetic Resonance Research, driving innovations in quantitative MRI, RF engineering, and translational imaging solutions. Key research interests include optimizing signal-to-noise ratios (SNR) for high-resolution imaging, developing novel RF coil arrays, and applying machine learning to improve diagnostic accuracy in prostate cancer. His work addresses challenges in clinical MRI safety, such as thermal noise reduction and RF shimming for parallel transmission systems. Recent studies explore in vivo metabolic imaging of the brain at 10.5T and non-invasive evaluation of meniscus degeneration using T2*-mapping. Dr. Metzger has contributed to the development of advanced imaging protocols, including universal mode acquisition methods and Bayesian spatial partitioning techniques for lesion detection. His interdisciplinary collaborations span radiology, biomedical engineering, and oncology, aiming to translate cutting-edge MRI innovations into clinical practice.

Remi Patriatمشاهده پروفایل

استادیار

• Neuroimaging
• Deep Brain Stimulation (DBS)
• Parkinson's Disease
• +۵ مورد دیگر

Remi Patriat, PhD, is an Assistant Professor in the Department of Radiology at the University of Minnesota. His work focuses on advancing neuroimaging techniques, particularly using 7-Tesla MRI, to improve understanding of brain structures and their clinical applications in movement disorders such as Parkinson’s disease and essential tremor. He specializes in deep brain stimulation (DBS) strategies, neural pathway mapping, and the development of precision medical imaging protocols. Dr. Patriat’s research integrates advanced MRI technologies with clinical neuroscience, emphasizing the anatomical and functional characterization of subcortical nuclei (e.g., thalamus, globus pallidus). His studies explore how DBS modulates neural oscillations and connectivity, particularly in the context of Parkinson’s disease, to optimize therapeutic outcomes. He has contributed to the development of automated segmentation tools for brain structures using machine learning and high-resolution imaging. His work on 7T MRI applications has addressed challenges in clinical imaging protocols, motion correction algorithms, and the visualization of subnuclear brain regions. He investigates how electrode placement and stimulation parameters in DBS correlate with clinical efficacy, leveraging computational modeling and patient-specific anatomical data. While no formal scientific awards are listed, his contributions to neuroimaging and DBS research reflect a focus on translational medicine and technological innovation in neurology. His research team collaborates closely with clinical teams to bridge imaging science with surgical and therapeutic advancements.

• Magnetoencephalography
• Functional MRI
• Neurovascular Response
• +۲ مورد دیگر

Dr. Nan Li is an Assistant Professor of Radiology and the Advanced Imaging Research Center at UT Southwestern Medical Center. She holds a B.S. in Biomedical Engineering from Shanghai Jiao Tong University and a Ph.D. from Johns Hopkins University School of Medicine. Her postdoctoral work was conducted at MIT under Dr. Alan Jasanoff, focusing on molecular fMRI techniques. Research interests include developing novel whole-brain imaging methods to integrate molecular and system neuroscience, with specific focus on reward, learning, and memory circuits. Her work combines magnetoencephalography (MEG) and functional MRI to study brain circuitry. Analysis of publications demonstrates specialization in neuroimaging technology development, particularly fMRI-based molecular sensors and optogenetic-neurovascular coupling. Awards: UT System Rising STARs Award Endowed Thomas O. Hicks Scholar McGovern Rising Star (MIT) Dr. Li leads a neuroimaging research group aiming to advance brain disorder treatments.

Jimin Renمشاهده پروفایل

استادیار

• Skeletal Muscle Energetics
• Metabolic Imaging
• Magnetic Resonance Spectroscopy
• +۲ مورد دیگر

Jimin Ren is an Assistant Professor at UT Southwestern's Advanced Imaging Research Center with joint appointments in Biomedical Engineering and Radiology. His research integrates NMR physics, physiology, and biochemistry to study skeletal muscle energetics using non-invasive MRS techniques. His work focuses on metabolic pathway interactions and homeostasis maintenance in healthy versus diseased/aged muscles. Research encompasses cerebral vascular function, metabolism, and physiology in aging, cognitive impairment, and metabolic disorders. Recent investigations examine perfusion changes in Parkinson's disease, deep-learning hemodynamic mapping, and metabolic responses to bariatric surgery.

Takao Henschمشاهده پروفایل

استاد

• Developmental Neuroscience
• Critical Period Plasticity
• Neurodevelopmental Disorders
• +۱ مورد دیگر

Dr. Takao Hensch is a Professor at Harvard University with joint appointments in Molecular and Cellular Biology and Neurology. He investigates critical periods of brain development, examining how early experiences shape neural circuits and their vulnerability to disorders like autism and epilepsy. His work has revealed that inhibitory circuits determine the timing of these critical periods, with translational applications for neurodevelopmental disorders. He directs the NIMH Conte Center at Harvard and holds affiliations with Boston Children's Hospital's Kirby Neurobiology Center. Dr. Hensch earned his Ph.D. from UCSF, trained at Harvard and the University of Tokyo, and received the Society for Neuroscience Young Investigator Award, NIH Director’s Pioneer Award, and Japan's Order of the Rising Sun. His research employs molecular, cellular, and systems neuroscience approaches. Recent work explores anesthesia effects on infant neurodevelopment, oxidative stress in traumatic brain injury, and gene therapies for epilepsy. Publications emphasize plasticity mechanisms, cortical circuit maturation, and therapeutic interventions. Dr. Hensch's lab studies neural circuit development across sensory systems and prefrontal cortex, collaborating globally through the ENIGMA Consortium to link genetic variation with brain structure.

Stefano Anzellottiمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Social Neuroscience
• Face Recognition
• +۷ مورد دیگر

Stefano Anzellotti is an Associate Professor in the Department of Psychology at Boston College's Morrissey College of Arts and Sciences. His research explores cognitive and neural mechanisms at the perception-conceptual knowledge interface, focusing on person understanding through advanced computational models and neuroimaging techniques. Education: Ph.D. in Psychology, Harvard University (2014) M.A. in Psychology, Harvard University (2010) B.A. in Mathematics, University of Trento (110/110 cum laude, 2008) Diploma in Clarinet, Conservatory of Trento (2007) Research interests include computational neuroscience approaches to person knowledge acquisition, facial expression recognition, and multimodal identity representation. His work integrates fMRI, MVPA, and deep learning to model neural mechanisms underlying social perception. Recent articles demonstrate strong focus on multivariate pattern analysis in fMRI studies, neural representations of identity/expression, and computational modeling of brain networks. Work frequently appears in high-impact journals including Cerebral Cortex and Annual Review of Psychology . Scientific Awards: Simons Center Fellowship (2015-2017) Harvard GSAS Dissertation Fellowship (2013-2014) Mind, Brain and Behavior Award (2013) INDAM Mathematics Scholarship (2005-2008) Leads the Social and Cognitive Computational Neuroscience Lab, supervising graduate students in fMRI research. Secured major funding including NSF CAREER Award #1943862 for computational modeling of social perception.

Scott Slotnickمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Visual Memory
• Visual Attention
• +۶ مورد دیگر

Scott Slotnick is Professor of Psychology at Boston College, leading the Memory, Attention, and Perception Lab. His research examines neural mechanisms of memory and perception using fMRI, EEG, and signal detection models. Research focuses on: Neural basis of true vs. false memories Sex differences in cognitive processing Visual memory retrieval mechanisms Methodological advances in fMRI Publications resolve debates in memory systems and provide fMRI analysis tools.

Vikram Ravindraمشاهده پروفایل

استادیار

• Machine Learning
• Deep Learning
• Multi-modal Learning
• +۴ مورد دیگر

Vikram Ravindra is an Assistant Professor at the University of Cincinnati in the Department of Computer Science, with research interests spanning machine learning, deep learning, multi-modal learning, and network science. He develops computational tools for analyzing biomedical images, particularly neuroimages, and works with biomedical signals in wearable technology and robotics contexts. Research focus areas include: Machine learning for neuroimage analysis Multi-modal data integration techniques Biomedical signal processing Network science applications in healthcare Dr. Ravindra's publications demonstrate a consistent interdisciplinary approach, combining deep learning with neuroscience applications. Recent works focus on neuroimaging analysis, connectome interpretation, and medical AI applications. His research group currently includes PhD candidates working on biomedical applications of machine learning. He serves as co-organizer of the CS Graduate Student Seminar and was recently elevated to Senior Member of IEEE. Ravindra holds a PhD from Purdue University and MSc from Technical University of Munich.

Bert Aldenkampمشاهده پروفایل

استاد

• Neuroimaging
• Neurodegeneration
• Epilepsy
• +۳ مورد دیگر

AP (Bert) Aldenkamp is a part-time Professor at Eindhoven University of Technology (TU/e) in the Department of Electrical Engineering, specializing in Signal Processing Systems. He concurrently holds positions as Full Professor at Maastricht University Medical Center (MUMC+) and as a key research leader at Kempenhaeghe Epilepsy Center. His research focuses on brain MRI imaging, neurodegeneration processes, and the cognitive impacts of epilepsy. He has held professorships at Leiden and Amsterdam universities, and since 2013, has been a part-time professor at TU/e. Education: PhD in Cognition and Epilepsy from Groningen University (1984). Academic leadership includes Editor-in-Chief roles in epileptology journals and memberships in editorial boards of Epilepsy and Behavior , Acta Neurologica Scandinavica , and others. He also serves on advisory boards for pharmaceutical industries. Aldenkamp leads a collaborative MRI program connecting TU/e, MUMC+, and Kempenhaeghe, emphasizing signal analysis for neurodegeneration and neuromodulation research. Research interests include epilepsy comorbidities’ cognitive effects, functional MRI applications, and neuropharmacology. His work contributes to UN Sustainable Development Goals related to health and innovation. External roles include Visiting Professor at Ghent University and leadership in the Epilepsy Imaging Research Group at Maastricht.

Alona Fysheمشاهده پروفایل

استادیار

• Natural Language Processing
• Computational Neuroscience
• Machine Learning
• +۱ مورد دیگر

Alona Fyshe is an Assistant Professor with joint appointments in Computing Science and Psychology at the University of Alberta. She holds a CIFAR AI Chair and researches computational linguistics, machine learning, and neuroscience to model how the brain processes language. Her lab develops methods to analyze brain imaging data (EEG/fMRI) during language tasks, seeking to improve NLP models through neuroscientific insights. Current projects include neural representations of phrases and improving object recognition via brain-inspired architectures. Fyshe teaches graduate courses on machine learning applications in psychology and neuroscience. She has received funding from NSERC, CIFAR, and the Alberta Machine Intelligence Institute, with recent publications in Neural Networks and PLOS ONE.

Adam Hantmanمشاهده پروفایل

دانشیار

• Neuroscience
• Motor Control
• Neural Circuits
• +۳ مورد دیگر

Adam Hantman, PhD is an Associate Professor and Edward R. Perl Investigator at the University of North Carolina School of Medicine, affiliated with the Department of Cell Biology and Physiology. His Hantman Lab focuses on understanding how neural circuits generate coordinated motor behaviors, particularly through the cortico-cerebellar loop's role in learned tasks like reaching and grasping. Research combines genetics, anatomy, physiology, and dynamical systems modeling to dissect neural network functions. Key research interests include motor control mechanisms, neural circuit dynamics, and the interplay between sensory input and motor output. The lab employs cutting-edge techniques such as viral vector engineering (AAV variants), advanced imaging (fMRI, Neuropixels probes), and computational modeling to study neural activity patterns. Awarded the Edward R. Perl Investigator title, Dr. Hantman’s work bridges molecular, cellular, and systems neuroscience. Notable contributions include identifying cerebellar-thalamocortical pathways critical for movement initiation and revealing how cortico-cerebellar communication underpins dexterity. Labs/Teams: Hantman Lab at UNC Neuroscience Center actively explores neural circuit basis of skilled movements and pain modulation. Collaborations span neuroengineering (e.g., SORDINO fMRI technology) and molecular biology (genetic circuit mapping).

Ashish Rajمشاهده پروفایل

استاد

• Medical Imaging
• Neuroscience
• Graph Theory
• +۷ مورد دیگر

Ashish Raj, PhD, is a Professor in the Department of Radiology at the University of California, San Francisco (UCSF), School of Medicine. His interdisciplinary research focuses on applying computational methods and graph theory to biomedical applications, particularly in neuroimaging and brain connectivity. He leads research teams in NIH-funded projects on neurodegenerative diseases, including Alzheimer's and Parkinson's, leveraging structural and functional connectome analysis. Raj has over 70 peer-reviewed publications, two US patents, and prestigious awards like the NIH EUREKA Award and BRAIN Initiative grants. Education: PhD in Electrical and Computer Engineering from Cornell University (2005) and BE in Electrical Engineering from the University of Auckland (1998). Research interests include modeling brain network dynamics, tau and amyloid pathology progression, and developing algorithms for accelerated MRI and motion correction. His work bridges computer science, neuroradiology, and clinical neuroscience, aiming to advance precision medicine in neurology and radiology. Key achievements include pioneering mathematical models of brain connectivity networks and developing novel imaging techniques like tractography and Q-ball imaging. His lab explores network diffusion models to predict disease progression and has contributed to understanding microglial roles in tauopathy. Grants and collaborations span NIH-funded projects on network-based disease modeling, with a focus on translational applications. He directs the Brain Networks Laboratory, advancing computational neurology and multimodal data integration.

Srikantan Nagarajanمشاهده پروفایل

استاد

• Biomedical Engineering
• Neuroimaging
• Human Neuroscience
• +۵ مورد دیگر

Srikantan Nagarajan, PhD, is a Professor in the Department of Radiology and Biomedical Imaging at the University of California, San Francisco (UCSF). He holds joint appointments in the Department of Bioengineering and Therapeutic Sciences and the Department of Otolaryngology, Head and Neck Surgery. As the Director of the Biomagnetic Imaging Laboratory, his research focuses on biomedical engineering, integrative neuroscience, and translational neuroimaging. His work addresses brain plasticity in learning and disease, speech motor control mechanisms, and multimodal neuroimaging techniques (MEG, EEG, fMRI) for patient populations including Alzheimer’s, epilepsy, and traumatic brain injury. Education: B.E. in Electrical Engineering (University of Madras), MS and PhD in Biomedical Engineering (Case Western Reserve University), postdoctoral fellowship at UCSF with Drs. Michael Merzenich and Christoph Schreiner. Research Interests: Combines neuroimaging, machine learning, and computational models to study sensorimotor control, cortical plasticity, and neural mechanisms of speech. Key areas include brain-computer interfaces, auditory feedback processing, and neurodegenerative disease diagnostics. Over 200 peer-reviewed publications and two co-authored books on electromagnetic brain imaging techniques. Grants & Awards: Principal/Co-PI on NIH/NSF grants. Recognitions include AIMBE Fellowship (2020), IEEE Fellow (2017), and the International Society for Biomagnetism Mid-Career Award (2016). Ongoing projects include network modeling of Alzheimer’s dynamics and speech motor control in cerebellar ataxia. Labs & Teams: Leads the Biomagnetic Imaging Laboratory, collaborating with the UCSF Brain Research Interest Group and the UCB-UCSF Joint Bioengineering Program. Active in clinical translation of neuroimaging tools for diagnostics and therapy assessment.