Find Academic Supervisors

• Solar Physics
• Astronomy
• Solar Telescopes
• +3 more

Wenda Cao is a Professor and Director of the Center For Solar Terrestrial Research - Big Bear Solar Observatory at the New Jersey Institute of Technology. Their research focuses on solar physics, including high-resolution imaging, magnetic field dynamics, and solar telescope technology. Cao has led federal grants totaling over $10 million, including projects on solar eruptions, polarimeter systems, and DKIST first science initiatives. Key projects include MRI Track 1: Development of Wide-band High-resolution Imaging Spectro-Polarimetric Explorer (WHISPER) and Collaborative Research on solar flare structures. Their work has been featured in media outlets like Nature Astronomy and Astrophysical Journal Letters. Advising and grants highlight ongoing collaborations with institutions like the National Science Foundation. The Center hosts advanced facilities for solar observation, including the 1.6-meter telescope at Big Bear Solar Observatory.

Juan Eugenio IglesiasView profile

Research Professor

• Machine Learning
• Medical Imaging
• Neuroscience
• +3 more

Juan Eugenio Iglesias is a Research Professor at the Martinos Center for Biomedical Imaging, affiliated with Massachusetts General Hospital (MGH) and Harvard Medical School. He directs the Laboratory for Ex vivo Modeling of Neuroanatomy (LEMoN) and co-directs the Center for Machine Learning. His academic background includes a Telecommunications Engineering degree from ETSI, a double degree in Electrical Engineering from the Stockholm Royal Institute of Technology (KTH), a PhD in Biomedical Engineering from UCLA, and postdoctoral research at the Martinos Center and BCBL in San Sebastián. He holds notable fellowships, including a Marie-Sklodowska Curie Fellowship and a Fulbright Scholarship, and received an ERC Starting Grant to fund his teaching role at University College London before returning to MGH in 2018. Research Interests: Iglesias specializes in applying machine learning to analyze brain MRI images, particularly focusing on ex vivo neuroanatomy modeling, clinical and low-field MRI interpretation, and understanding consciousness through brainstem connectivity. His work emphasizes scalable, resolution-agnostic approaches for neuroimaging tasks, including segmentation, super-resolution, and registration. He also investigates brain tumor segmentation challenges (e.g., BraTS-METS) and integrates dissection photography with AI for neuropathology analysis. Scientific Awards: European Research Council Starting Grant Marie-Sklodowska Curie Fellowship Fulbright Scholarship Advising & Grants: His ERC grant supported his prior position at UCL. Current projects include pediatric brain tumor segmentation, portable MRI applications in stroke and traumatic brain injury, and developing tools like USLR for longitudinal brain MRI analysis. Collaborations with companies like Endesa reflect his engineering background. Labs & Teams: Leads LEMoN Lab and co-directs the Center for Machine Learning. Engages in interdisciplinary teams for projects such as H-SynEx (hypothalamus segmentation) and PEPSI (MRI contrast-agnostic representations).

• Biomechanics
• Hemodynamics
• Cerebrovascular Disease
• +3 more

Anne Robertson is the Distinguished Service Professor and William Kepler Whiteford Professor of Engineering at the Swanson School of Engineering, University of Pittsburgh. She specializes in biomechanics, cerebrovascular disease, and computational fluid dynamics (CFD). Her research focuses on understanding hemodynamic factors in cerebral aneurysms, arterial tissue mechanics, and vascular grafts. Robertson has held prestigious positions such as Member of the Neuroscience and Ophthalmic Imaging Technologies Study Section (NIH) and has received awards including the 100 Women in STEM Award and the Beitle-Veltri Teaching Award. Education: Ph.D., Mechanical Engineering (Continuum Mechanics), University of California Berkeley (1992) M.S., Mechanical Engineering, University of California Berkeley (1987) B.S., Mechanical Engineering, Cornell University (1983) Research Interests: Biomechanical modeling of cerebral aneurysms Hemodynamic influences on vascular pathologies Development of predictive models for aneurysm rupture Material degradation in arterial walls Key Contributions: Pioneered studies on bleb formation and rupture mechanisms in intracranial aneurysms Advanced computational methods for analyzing cerebral blood flow dynamics Investigated the role of collagen recruitment and elastin failure in aneurysm progression Awards & Recognition: Over 20 major awards spanning teaching, research, and leadership Recipient of the 15th Elsevier Distinguished Lecture in Mechanics (2023) Grants & Advising: Secured grants from NIH, Whitaker Foundation, and others Advises on multidisciplinary projects involving engineering, medicine, and biology Labs & Collaborations: Partners with teams at the NIH, Instituto Superior Técnico (Lisbon), and global research institutions Active in developing computational tools for clinical applications

• Neuroscience
• Pain Perception
• Neuroimaging
• +3 more

Dr. Falk Eippert is a Research Fellow and Group Leader of the Max Planck Research Group Pain Perception at the Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS) in Leipzig, Germany. His research focuses on understanding pain mechanisms, neuroimaging techniques for spinal cord and brain function, and placebo effects. He holds a PhD in Systems Neuroscience from the University of Hamburg and completed postdoctoral training at the University of Oxford's FMRIB Centre. Key research interests include the neural basis of pain perception, non-invasive electrophysiological methods for spinal cord activity recording, and high-field MRI applications in CNS studies. His work bridges clinical pain management and fundamental neuroscience, addressing topics like thermosensation modulation, neuroimaging reliability, and therapeutic neuromodulation effects. He has pioneered spinal cord fMRI protocols and developed automated segmentation tools for neuroimaging data. His lab actively contributes to open science initiatives through multi-center collaborations and shared datasets, advancing spinal cord and brain imaging standards.

• Neuroscience
• Data Science
• Statistical Computing
• +3 more

Dr. Nico Scherf is a Group Leader at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. His research focuses on developing conceptual and computational tools to analyze neural data across scales, visualize complex biological systems, and model neural development and cognition. He leads the Methods and Development Group Neural Data Science and Statistical Computing , contributing to advancements in neuroscience, AI, and clinical practice. His work integrates experimental techniques like high-resolution MRI, light-sheet microscopy, and single-cell sequencing, addressing challenges in interpreting high-dimensional biological data. As Deputy Ombudsperson, he also supports institutional governance. Research interests include: Analysis: Mapping neural system structures and functions Exploration: Geometric visualization of complex biological systems Synthesis: Computational modeling of neural processes No specific awards or grants are listed in the provided text, and no advisee students are noted. His team focuses on interdisciplinary methods to bridge data science and life sciences.

Lixin ShenView profile

Professor

• Applied and Computational Harmonic Analysis
• Optimization
• Imaging Science
• +4 more

Lixin Shen is a Professor in the Department of Mathematics at Syracuse University, part of the College of Arts and Sciences. His research focuses on applied and computational harmonic analysis, optimization, imaging science, and information processing. Shen holds a Ph.D. in Mathematics from Sun Yat-Sen University (1996), an M.Sc. from Peking University (1990), and a B.Sc. from Peking University (1987). Education: Ph.D., Mathematics, Sun Yat-Sen University, 1996 M.Sc., Mathematics, Peking University, 1990 B.Sc., Mathematics, Peking University, 1987 Research Interests: Shen’s work emphasizes sparse optimization, image and signal processing, computational mathematics, and their applications. Notable areas include wavelet analysis, tensor decomposition, and robust algorithms for noise removal and high-resolution imaging. Grants & Awards: NSF Grant: Collaborative Research: Sparse Machine Learning and Sparse Optimization (2022–2025) Excellence in Graduate Education Faculty Recognition Award, Syracuse University (2024) Air Force Summer Faculty Fellowship (2024, 2023, 2021, 2020) Service & Leadership: Chair of Graduate Committee, Mathematics Department (2024–2025) Editor, Frontiers in Applied Mathematics and Statistics Organizer, SIAM Conferences on Optimization and Imaging (2023–2020) Teaching: Recent courses include Numerical Linear Algebra, Numerical Methods with Programming, Sparse Optimization, and Partial Differential Equations.

• Gene Therapy
• Neurodegenerative Diseases
• Molecular Biology
• +3 more

Toloo Taghian is an Instructor in the Department of Genetic and Cellular Medicine at the University of Massachusetts Chan Medical School, affiliated with the T.H. Chan School of Medicine. She holds additional positions in the Gene Therapy Center, Genetic and Cellular Medicine, and Radiology departments within the same institution. Education: - BS and MS in Physics, Isfahan University of Technology, Iran - PhD in Physics, University of Cincinnati, USA Research Focus: Dr. Taghian's work centers on gene therapy, neurodegenerative diseases, molecular biology, and biomedical engineering. Her research employs animal models to study conditions like Huntington’s disease, Tay-Sachs disease, and metabolic disorders. She explores advanced delivery techniques for gene therapy vectors and imaging technologies to monitor therapeutic efficacy. Key Contributions: - Developed minimally invasive CNS delivery methods for AAV vectors - Advanced understanding of synaptic protein changes in Huntington’s disease models - Investigated electric field modulation of cellular functions Labs/Teams: She contributes to interdisciplinary teams in gene therapy, neuroimaging, and vascular biology at UMass Chan Medical School.

Gabriel de ErausquinView profile

Research Professor

• Alzheimer's Disease
• Neurodegenerative Disorders
• Neuropsychiatry
• +6 more

Dr. Gabriel de Erausquin is the Zachry Foundation Distinguished Professor of Neurology and Research Professor at the Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases. His work bridges clinical neurology, neuroimaging, and translational research, with a focus on Alzheimer's disease, neurodegenerative disorders, and the neuropsychiatric consequences of systemic infections like SARS-CoV-2. He leads multicenter studies using advanced neuroimaging techniques (e.g., 7T MRI) to map brain structural and functional changes. His research also addresses psychiatric comorbidities in dementia, genetic networks influencing personality, and culturally adapted community health strategies for aging populations. Dr. de Erausquin's team investigates novel therapeutic approaches, including antiretroviral therapy repurposing (ART-AD) and rapamycin trials for Alzheimer's. His studies on post-COVID cognitive impairment highlight the role of Type I interferon signaling pathways and olfactory dysfunction. He collaborates globally through consortia like the Alzheimer’s Association International Cohort Study, emphasizing diverse populations including Hispanic and Andean communities. Key awards: Zachry Foundation Distinguished Professorship Major projects: Alzheimer’s Association Global Consortium on SARS-CoV-2 sequelae, South Texas Alzheimer’s Disease Research Center Clinical focus: Integrating genomic data with neuroimaging and neuropsychiatric outcomes His work extends to mental health education in resource-limited settings, including training programs for rural psychiatry and community health workers. Dr. de Erausquin’s interdisciplinary approach addresses both molecular mechanisms (e.g., gene expression networks) and societal impacts of neurodegenerative diseases.

• Multiple Sclerosis
• MRI Imaging
• Neuroimmunology
• +7 more

Dr. Christopher Corey Thomson Hemond is an Assistant Professor at UMass Chan Medical School within the Department of Neurology, with additional appointments in the T.H. Chan School of Medicine, NeuroNexus Institute, and Morningside Graduate School of Biomedical Sciences across MD/PhD, Neuroscience, and Translational Science programs. BS in Brain & Cognitive Science from Massachusetts Institute of Technology MD from Stanford University Dr. Hemond is a board-certified neurologist with clinical subspecialty training in neuroimmunology and multiple sclerosis. His research focuses on developing and validating MRI-based biomarkers to improve early identification and pathophysiological understanding of neurodegenerative processes in MS. His lab utilizes high-resolution MRI sequences, including structural, susceptibility-sensitive (iron), and diffusion imaging to characterize microstructural MS lesion features. Recent work incorporates deep learning models to accelerate identification and segmentation of novel CNS structures relevant to neuroinflammatory disease. Analysis of Dr. Hemond's publications reveals a strong focus on paramagnetic rim lesions as specific biomarkers for MS diagnosis and progression. His work spans neuroimaging, fluid biomarker development, Epstein-Barr virus research, and psychoneuroimmunological aspects of MS, particularly mindfulness-based interventions for symptom management. His publications consistently address the interface between imaging findings and underlying biological mechanisms in MS. 2022-2023: Riccio Foundation Award for CSF antibody profiling in MS 2020-2022: UMass PACE award for EBV-specific T cell responses in MS 2020-2024: Consortium of MS Centers award for mindfulness-based stress reduction research 2020-2022: NIH KL2 award for neurodegeneration prediction in MS 2018-2024: MS Foundation award for mindfulness interventions 2018-2020: National MS Society award for memory B-cell research Current NIH K23 grant (2022-2027) on paramagnetic rim lesions Dr. Hemond leads the Hemond Lab with a team including Mugdha Deshpande (clinical research coordinator), several medical students, and graduate researchers. His lab collaborates extensively with Dr. Carolina Ionete's MS biorepository and the NIH Translational Neuroradiology Section. Current projects include deep learning for brain structure segmentation, neural immune interface imaging, and mindfulness intervention studies for MS symptom management.

Venceslav KafedzhiskiView profile

Professor

• Wireless Communications
• Signal Processing
• Information Theory
• +6 more

Dr. Venceslav Kafedzhiski is a Professor at the Department of Telecommunications, Faculty of Electrical Engineering and Information Technologies (FEIT) at the Ss. Cyril and Methodius University in Skopje. He holds a Ph.D. from Arizona State University (2000) and has held academic positions since 1983, progressing through ranks including Assistant Professor (2001), Associate Professor (2005), and Full Professor (2010). His roles include coordinating Master's programs in Wireless and Mobile Communications and Wireless Systems, Services, and Applications, and leading the Signal Processing in Telecommunications Laboratory. Education: Bachelor's and Master's in Electrical Engineering from FEIT (1982, 1989) Ph.D. in Electrical Engineering from Arizona State University (2000) Research focuses on wireless communications, signal processing, information theory, MIMO/OFDM systems, and compressed sensing. He has authored over 80 publications in IEEE journals and conferences. Key contributions include work on channel estimation, radar systems, and telecommunication standards (e.g., WiMAX, LTE, 5G). He has led and participated in projects funded by NATO, EU (TEMPUS), and national grants, including initiatives on broadband strategies and spectrum measurement techniques. He serves as Senior Member of IEEE and has organized conferences like the Information Theory and Complex Systems (TINKOS). He has advised students on projects involving video transmission over MIMO channels and interference alignment in distributed storage systems. His leadership roles include chairing national strategy committees for electronic communications and broadband internet, and leading the Technical Committee for Electronic Communications at Macedonia's Standards Institute. Notable awards include honorary membership in Phi Kappa Phi (top academic honor society). His research extends to applied projects like radar systems for landmine detection and MRI signal processing, showcasing interdisciplinary impact in telecommunications and engineering.

• Radio Astronomy
• Medical Imaging
• Compressed Sensing
• +3 more

Yves Wiaux is a Professor at Heriot-Watt University's School of Engineering & Physical Sciences, affiliated with the Institute of Sensors, Signals & Systems. He specializes in advanced signal processing techniques with applications in radio astronomy and medical imaging. His research focuses on compressed sensing, optimization algorithms, and imaging methods for radio interferometry and MRI. His work integrates mathematical frameworks like wavelet transforms and sparse regularization to address challenges in high-dimensional data reconstruction. Notable contributions include the development of algorithms like SARA (Sparsity Averaging Reweighted Analysis) and PURIFY for radio interferometric imaging, as well as applications in medical imaging such as magnetic resonance fingerprinting. Wiaux collaborates extensively in international projects, including the LOFAR Two Meter Sky Survey. He advises PhD students through the BASP (Biomedical and Astronomical Signal Processing) group and leads research initiatives in scalable imaging techniques for large datasets.

• Cardiac Magnetic Resonance Imaging (CMR)
• Myocardial Perfusion
• Cardiovascular Imaging
• +5 more

Dr. Adriana Villa is a researcher specializing in Cardiac Magnetic Resonance Imaging (CMR) and myocardial perfusion analysis , with 819 citations and 28 research outputs. Her work intersects medical imaging, cardiovascular diagnostics, and advanced computational methods. Key Research Areas : Cardiac MRI, Hypertrophic/Takotsubo Cardiomyopathy, Myocardial Perfusion, Sudden Cardiac Death risk stratification Notable Projects : Calibrated multimodality quantitative myocardial perfusion analysis (2018-2022, British Heart Foundation funded) Collaborations : Active in international networks with 26+ co-authors, including Prof. S. Plein and Prof. R. Razavi Innovation : Developed CardiSort (2022) - a neural network for automated CMR image sorting Her publications span high-impact journals like JACC: Cardiovascular Imaging and European Radiology , covering topics from multi-slice perfusion techniques to machine learning applications in cardiac imaging. While no formal awards are listed, her work has been referenced in patents and widely shared across academic networks. Current research focuses on quantitative CMR for ischemia detection, myocardial strain analysis in cardiomyopathies, and AI-driven image processing to improve diagnostic accuracy.

• Alzheimer’s Disease
• Neurodegenerative Disorders
• Neuroimaging
• +4 more

Elizabeth Joe is an Assistant Professor of Clinical Neurology at the University of Southern California (USC). Her research focuses on neurodegenerative disorders, particularly Alzheimer’s disease, with an emphasis on vascular mechanisms, biomarkers, and clinical translation. She investigates cerebral hypoperfusion, blood-brain barrier dysfunction, and neuroimaging techniques to understand cognitive decline and dementia progression. Key areas of investigation include the role of vascular factors in Alzheimer’s pathophysiology, the development of sensitive biomarkers for early detection, and the impact of FDA guidelines on clinical trial design. Her work bridges laboratory research with clinical practice, aiming to improve diagnostic accuracy and patient care in underserved populations. Dr. Joe’s publications span neuroimaging advancements, vascular-neurological interactions, and translational research. She contributes to interdisciplinary teams addressing barriers to dementia care and advancing memory clinic models. Her research has been published in journals such as Alzheimer’s & Dementia , Brain Imaging and Behavior , and Nature . No scientific awards are explicitly listed in the profile. Her work emphasizes clinical-neuroscience collaboration without noted grants or student advisement details provided here.

• Magnetic Resonance Imaging
• Nuclear Magnetic Resonance
• High-Field Spectroscopy
• +3 more

Julia Krug is an Assistant Professor in the BioNanoTechnology department at Wageningen University. Her research focuses on ultra-high field magnetic resonance imaging (MRI) and spectroscopy, with applications in plant sciences, biofilm characterization, and material science. She has published extensively on topics such as microcoil calibration, spatial resolution optimization, and biofilm structure analysis using MRI. Her work integrates high-field MRI techniques with interdisciplinary challenges, including plant root imaging in Medicago truncatula and microbial biofilm dynamics. She has co-promoted multiple PhD candidates in projects related to novel MRI/XRF techniques for plant sciences, electroactive biofilm characterization, and low-field NMR methodologies. Key projects include developing MRI sensors for nanoparticle contrast mechanisms, advancing microalgal biofilm monitoring, and enhancing magnetic resonance microscopy at cellular resolution. Her contributions span theoretical modeling, experimental validation, and practical applications of high-field MRI systems.

Enrico RaveraView profile

Associate Professor

• Solid-state NMR
• Paramagnetic NMR
• EPR Spectroscopy
• +3 more

Enrico Ravera is an Associate Professor in the Department of Chemistry at the University of Florence, affiliated with the Magnetic Resonance Center. He holds a B.Sc., M.Sc., and Ph.D. in Chemistry from the University of Florence (2008–2013), followed by postdoctoral fellowships at CERM and a FIRC Fellowship at CIRMMP. His research focuses on NMR spectroscopy (solution/solid-state), paramagnetic systems, EPR, and biomaterial characterization. Key achievements include developing novel NMR methodologies for protein-material interactions and co-authoring influential textbooks like NMR of Paramagnetic Molecules . Education: B.Sc. Chemistry, University of Florence (2008) M.Sc. Chemistry of Biological Molecules, cum laude (2009) Ph.D. in Chemistry (2013) Research interests span solid-state NMR, paramagnetic systems, EPR, and bioinspired materials. Notable contributions include engineering enzymes for bioinspired silica formation and studying protein dynamics via paramagnetic tagging. Awards include the 2020 Premio Raffaello Nasini, GIDRM Under 35 Award, and UNESCO/IUPAC Green Chemistry Prize. His work bridges chemistry, biology, and materials science, with applications in drug design and medical imaging. Grants and collaborations include projects on protein-drug conjugates, NMR-based drug development, and biotherapeutic characterization. He leads efforts in developing interdisciplinary approaches for structural biology. Labs/Teams: Active in the Magnetic Resonance Center (CERM) and collaborates with CIRMMP. Research integrates NMR with computational methods and biophysical techniques.