Dr. Ian Wilson is a researcher at Newcastle University with a focus on medical genetics, nephrology, and genomic analysis. His work spans genetic determinants of kidney diseases, mitochondrial disorders, and biomarker development. Notable contributions include studies on uromodulin genetics in African populations, copy-number variations in rare diseases, and kidney ciliopathies. He has collaborated extensively on projects involving genome sequencing, mitochondrial replacement therapy, and muscular dystrophy biomarkers. Wilson's research integrates computational tools like machine learning for predictive modeling in urolithiasis and employs advanced imaging techniques for disease progression monitoring. Key areas: Genetic epidemiology, renal genomics, mitochondrial DNA analysis Focus on translational applications: Biomarker development for kidney stones and muscular dystrophies Interdisciplinary collaborations in ophthalmology and orthopedics His publications reflect a commitment to advancing diagnostic accuracy and understanding complex genetic disorders through multi-omics approaches.
Zhi-Pei Liang is the Franklin W. Woeltge Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign, with joint appointments in the Department of Bioengineering, Beckman Institute for Advanced Science and Technology, and Coordinated Science Laboratory. His research spans biomedical engineering, medical imaging, and signal processing with a focus on advancing magnetic resonance imaging and spectroscopy technologies. His educational background includes a Ph.D. in Biomedical Engineering from Case Western Reserve University (1989) and a B.S. in Electrical Engineering from South-China University of Technology (1982), followed by postdoctoral training at UIUC (1989-1991). Professor Liang's research interests center on magnetic resonance imaging and spectroscopy , with particular emphasis on ultrafast imaging techniques , model-based reconstruction methods , and the integration of physics-based modeling with machine learning . His pioneering work on SPICE (SPectroscopic Imaging by exploiting spatiospectral CorrElation) has revolutionized high-resolution metabolic brain imaging by enabling label-free molecular imaging through the marriage of spin physics and machine learning. His research spans pattern recognition, parameter estimation, image formation theory, and algorithms for medical imaging applications. Analysis of his recent publications reveals a strong focus on high-resolution metabolic imaging , particularly using SPICE methodology to map brain metabolism with unprecedented detail. His work bridges fundamental physics of magnetic resonance with advanced computational methods to overcome traditional limitations in imaging speed and resolution. Current research directions include J-resolved spectroscopic imaging, deuterium-based metabolic mapping, and multimodal integration of PET and MRSI for studying neurological disorders. Elected to International Academy of Medical and Biological Engineering (2012) Gold Medal, International Society for Magnetic Resonance in Medicine (2022) Technical Achievement Award, IEEE Engineering in Medicine and Biology Society (2014) Fellow, National Academy of Inventors (2021) Author of influential book 'Principles of Magnetic Resonance Imaging' (1999) President of IEEE Engineering in Medicine and Biology Society (2011-2012) Professor Liang has advised numerous students and postdocs in biomedical imaging research and has received multiple teaching honors including the Ronald W. Pratt Outstanding Teaching Award (2005) and multiple listings among UIUC's Excellent Teachers. His research has been supported by various grants from NIH, NSF, and other funding agencies. He leads the SPICE (Spectroscopic Imaging by exploiting spatiospectral Correlation) research group which focuses on developing novel imaging techniques that combine physics-based modeling with machine learning for ultrafast metabolic imaging. His laboratory, part of the Beckman Institute's Integrative Imaging Theme, collaborates extensively with clinical researchers at Carle Illinois College of Medicine and other institutions to translate advanced imaging techniques into clinical applications for neurological disorders, cancer, and metabolic diseases. Current projects focus on high-resolution mapping of brain metabolism in Alzheimer's disease, stroke, and brain tumors using novel MR spectroscopic imaging techniques.
Dr. Neal Bangerter is a Visiting Professor in the Department of Bioengineering at Imperial College London's Faculty of Engineering. He specializes in medical imaging (MRI), artificial intelligence, machine learning, and signal processing. Dr. Bangerter holds adjunct appointments at INSEAD, the University of Utah, and Brigham Young University. His research focuses on ultra-high field MRI, AI applications in healthcare, and data-driven bioscience technologies. He leads the London Collaborative Ultra-High Field Scanner (LOCUS) project and advises companies on AI and innovation strategies. Education: B.S. in Physics (UC Berkeley), M.S. and Ph.D. in Electrical Engineering (Stanford University). Career highlights include roles at McKinsey & Company, Microsoft, and Reactrix, as well as founding BYU's Medical Imaging Research Center. He has pioneered cross-faculty initiatives like the Crocker Innovation Fellowship Program. Research interests include novel MRI pulse sequences, AI in medical imaging, and large-scale health data analysis. His work spans collaborations with Stanford, Oxford, Cambridge, and Siemens Healthcare. He teaches executive education at INSEAD, focusing on bridging technical concepts with business strategies. Key awards include the David Evans Chair at Brigham Young University. His contributions to the UK Biobank Neuroimaging study and development of MRI techniques like RAFO-4 highlight his impact on advancing imaging technologies and AI applications in healthcare.
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.
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 .
Professor Chew Sing Yian is a distinguished academic at Nanyang Technological University (NTU), Singapore, holding professorial appointments across three schools: the School of Chemistry, Chemical Engineering and Biotechnology (CCEB), the Lee Kong Chian School of Medicine, and the School of Materials Science & Engineering (as a courtesy appointment). She leads the Chew Lab, which focuses on biologically-inspired materials for regenerative medicine, with a particular emphasis on neural tissue engineering and drug/gene delivery systems. Professor Chew's research interests center on designing biomimetic scaffolds to understand and control cell fate. Her work specifically focuses on scaffold-mediated delivery of gene-silencing and biomimicking physical signals for neural tissue regeneration and remyelination. She engineers bio-functional platforms for long-term delivery of biologics, with applications in understanding and directing neural tissue regeneration after traumatic injuries, stem cell fate determination, and host-implant integration. Her lab employs combinatorial approaches involving substrate topography/compliance and biochemical cues from drugs, genes and cells to mediate tissue regeneration. Professor Chew's extensive publication record demonstrates consistent leadership in neural tissue engineering, with a focus on microRNA delivery for spinal cord injury treatment, bioprinted scaffolds for neuronal differentiation, and biomimetic materials for drug delivery. Her work spans fundamental science to translational research, with particular emphasis on scaffold-mediated gene-silencing approaches to understand and direct neural tissue regeneration, stem cell differentiation, and host-implant integration. Professor Chew has received notable recognition including: Fellow of Tissue Engineering and Regenerative Medicine (FTERM) Professor Chew actively mentors students and researchers, with evidence of her students achieving recognition such as the 'Young Scientist Travel Fellowship Prize' awarded to Jiah Shin. Her lab, the Chew Lab, has secured significant funding including the ScaNCellS project, which represents a Singapore/France collaboration with Laurent David from IMP. The lab is currently recruiting highly motivated PhD students for ongoing research in neural tissue engineering. The Chew Lab is at the forefront of developing bio-functional micro- and nano-structured scaffolds for regenerative medicine applications. Current research focuses on three main areas: cell-substrate interactions to understand how biomimicking nanofiber structures alter cell fate; controlled delivery scaffolds for sustained drug and gene delivery; and translational studies on tissue regeneration and host-implant integration for traumatic nerve injuries in both peripheral and central nervous systems.
Dr. Markus Zimmermann is a researcher at the Institute of Neuroscience and Medicine (INM-4: Physics of Medical Imaging) at the Research Center Jülich. His work focuses on advancing quantitative MRI techniques, particularly in water content mapping, multiparametric imaging, and ultrahigh-field MRI applications. He contributes to developing methods for eddy current characterization, multi-exponential relaxometry, and rapid whole-brain protocols. His research addresses neurological and medical imaging challenges, including cerebral pathologies and neurobiological implications. Key areas of expertise include MRI parameter estimation, medical imaging algorithms, and the integration of advanced imaging techniques for clinical and neuroscience applications. His projects often involve collaborations to validate methodologies using in vivo/ex vivo experiments and super-resolution reconstruction. Dr. Zimmermann’s work aims to enhance diagnostic precision and understanding of brain physiology through innovative MRI technologies.
Giacomo Parigi is an Associate Professor of Chemistry at the University of Florence, affiliated with the Magnetic Resonance Center and the Department of Chemistry. His work focuses on paramagnetic effects in NMR, MRI contrast agents, and protein dynamics. He holds a Physics degree (1992) and a Chemistry PhD from the University of Florence, with postdoctoral and research roles at CERM since 1999. Research Interests: Parigi’s research explores paramagnetic effects in biological molecules, including protein structure determination, MRI contrast agent design, and relaxometry. He co-authored seminal books on NMR of paramagnetic molecules and pioneered methods for studying protein dynamics via field-cycling NMR. His lab integrates computational biology, bioinformatics, and experimental NMR to address biomedical challenges. Publications & Trends: Recent work emphasizes machine learning-enhanced NMR analysis, novel MRI probes (e.g., Mn-based nanogels), and structural studies of metalloproteins. His articles highlight innovations in paramagnetic NMR restraints, dynamic aggregation imaging, and low-field MRI applications. Awards & Grants: No explicit awards mentioned, but his extensive publications reflect significant contributions to NMR methodology. Active in securing grants for structural biology and biomedical imaging projects. Labs & Teams: Leads the Magnetic Resonance Center’s NMR group, collaborating on interdisciplinary projects involving biomaterials, drug design, and protein engineering. His team develops cutting-edge tools for in-cell NMR and metabolomics analysis.
Delphine Périé-Curnier is a Full Professor in the Department of Mechanical Engineering at Polytechnique Montréal and Director of Graduate Studies. Her research focuses on developing quantitative MRI techniques for non-invasive characterization of living tissue mechanical properties, particularly in cardiotoxicity detection and musculoskeletal mechanobiology . She leads the Bioperformance Analysis and Innovation Laboratory (LIAB) and contributes to the Institute of Biomedical Engineering. Education: Ph.D. from Paul Sabatier University, Toulouse, France Her work bridges medical imaging , biomechanical modeling , and finite element analysis to predict disease progression through pathomechanism understanding. Key projects include exercise-induced cardiac changes in childhood cancer survivors and spinal biomechanics in scoliosis. Recent publications (2023-2024) emphasize cardiovascular MRI for childhood cancer survivorship and hemodynamic modeling in left ventricle analysis. She supervises 26 graduate students, with completed theses spanning topics like doxorubicin cardiotoxicity , knee replacement stability , and spatial cardiac MRI protocols . Teaching includes graduate courses in biomedical design , advanced biomechanics , and modeling techniques .
Professor Mikko Nissi holds the Chair of Medical Physics and Engineering at the University of Eastern Finland’s Department of Technical Physics, Faculty of Science, Forestry and Technology. He leads research on quantitative magnetic resonance imaging (qMRI), focusing on musculoskeletal diseases and methodological advancements in ultra-short echo time techniques. His work integrates inverse problems research and machine learning to predict tissue properties unobservable via conventional MRI. Education: PhD in Physics (University of Kuopio, 2008), Adjunct Professor since 2015. Key roles include Associate Professor (2020–2024) and Academy Research Fellow (2015–2020). Active in research groups like the Academy of Finland Flagship (FAiME) and UEF’s Musculoskeletal Diseases (MSKD) community. Research interests span qMRI relaxometry, T1ρ/T2 anisotropy, and AI-driven virtual histology. Notable projects include EU-funded microMRI infrastructure for industrial applications and grants from the Research Council of Finland for AI-assisted MRI methods. Teaching: Course on MRI principles and applications. Advises on musculoskeletal biomechanics and finite element modeling. Recognized for contributions to medical physics, including societal roles in the Finnish Society for Medical Physics and International Society for Magnetic Resonance in Medicine. Hobbies: 3D printing for research tooling and handicrafts. Publications (>100 articles) address cartilage degeneration, myocardial perfusion, and MRI applications in agriculture/forestry.
Dr. Alan M. Allgeier is a Professor in the Chemical and Petroleum Engineering Department at the University of Kansas School of Engineering, where he also serves as Associate Director of the Center for Environmentally Beneficial Catalysis (CEBC). He joined KU in Fall 2017 after 20 years of industry experience at DuPont and Amgen. Dr. Allgeier holds a B.S. in Chemistry from Case Western Reserve University (1992) and M.S./Ph.D. degrees in Inorganic Chemistry from Northwestern University (1997). His research focuses on sustainable catalysis and manufacturing with four primary themes: characterization of porous materials using multi-technique approaches including NMR relaxometry; continuous flow processing for pharmaceuticals; synthesis of heterogeneous catalysts; and design of redox enzyme catalytic processes. His work bridges fundamental understanding of catalytic species with practical applications in renewable resource utilization and pharmaceutical manufacturing. Analysis of Dr. Allgeier's recent publications reveals a strong trend toward sustainable chemical processes, particularly in biomass conversion to valuable chemicals and materials. His work integrates advanced characterization techniques (especially NMR-based methods) with catalytic process development, focusing on hydrodeoxygenation reactions, biocatalysis using ethanol as a terminal reductant, and novel reactor design for pharmaceutical manufacturing. The research demonstrates a consistent commitment to Green Chemistry principles across multiple application areas. Bellows Faculty Scholar, University of Kansas School of Engineering (2021) Catalysis Club of Philadelphia Award (2021) Russell Malz Award for Service to Catalysis, Organic Reactions Catalysis Society (2014) Amgen Green Chemistry Award for "A Novel, Green Process for AMG 423" (2011) Sigma Xi Award for excellence in graduate research, Northwestern University (1994) Dr. Allgeier has successfully mentored numerous graduate and undergraduate students, with several completing Ph.D. dissertations under his supervision. His research is supported by significant funding including an NSF RII Track-2 FEC grant ($4 million), multiple Kansas Corn Commission awards, and industry partnerships with Honeywell, IFF Inc., and DuPont. His current projects focus on renewable polymers, ethanol derivatives, and advanced characterization of porous materials. The Allgeier Research Group maintains active collaborations with industry partners and national laboratories, operating specialized facilities for catalysis research, NMR characterization, and continuous flow pharmaceutical manufacturing. The group's work on sustainable catalysis directly supports the UN definition of sustainable development by developing processes that meet present needs without compromising future generations' ability to meet theirs.
Harald E. Möller is a Professor and Head of the Nuclear Magnetic Resonance Research and Development Unit at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig. With a career spanning over four decades, he has held academic positions including Honorary Professor at the University of Leipzig and leadership roles in institutions like Duke University Medical Center and the University of Münster. His research focuses on advancing MRI methodologies, biophysical imaging principles, and their applications in neurology and neuroscience. Education: 1979-1985: Chemistry & Physics studies at Universities of Dortmund and Münster 1985: M.Sc. (Diploma) in Chemistry 1988: PhD in Physical Chemistry (summa cum laude) 2000: Habilitation in Physical Chemistry 2002: Habilitation in Biophysical Chemistry Research Interests: Development of novel MRI methods Quantitative tissue characterization Myelin sheath imaging Cerebral blood flow dynamics High-field MRI hardware
Peter J. Basser is a leading research scientist at the National Institutes of Health (NIH), specifically within the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), where he heads the Section on Quantitative Imaging and Tissue Sciences (SQITS). His work bridges physics, engineering, and neuroscience to develop non-invasive MRI methods for probing tissue microstructure, particularly in the brain. His educational background is not explicitly mentioned, but his scientific achievements reflect deep training in biophysics and medical imaging. He earned his Ph.D. and has built a career at NIH as a principal inventor of key neuroimaging technologies. Basser's research focuses on quantitative imaging and tissue sciences , especially using diffusion MRI to study brain structure and function. He pioneered Diffusion Tensor MRI (DTI) , Streamline Tractography , and advanced methods like MAP MRI , CHARMED , and AxCaliber , enabling in vivo measurement of axon diameters and microstructural features previously accessible only through histology. His work aims to translate these tools into clinical use for diagnosing developmental disorders, trauma, and neurodegeneration. The 15 most recent articles reflect a consistent focus on developing novel MRI biomarkers, particularly through diffusion and relaxometry methods. They explore water exchange, restriction, glymphatic clearance, latency connectomes, and cortical microstructure, demonstrating a trajectory toward in vivo MRI histology and precision imaging for pediatric and neurological applications. Scientific Awards: National Academy of Engineering (NAE), Inducted 2020 National Academy of Inventors (NAI) Fellow, 2024 Eduard Rhein Technology Award, 2021 ISMRM Gold Medal, 2008 ISMRM Lauterbur Lecturer, 2020 American Society of Neuroradiology Honorary Member, 2019 Victor M. Haughton Award, 2017 ISMRM Fellow, 2010 AIMBE Fellow Best Paper Award, Frontiers in Physics, 2023 Basser leads a dynamic research group that mentors postdoctoral fellows and trainees, many of whom have received prestigious awards. His lab has secured significant grants from the NIH BRAIN Initiative, NICHD, USUHS, and the Bill & Melinda Gates Foundation. The SQITS lab develops open-source software tools like TORTOISE , dmritool , and HI-SPEED , which are widely used in the neuroimaging community. The lab collaborates with institutions such as Uniformed Services University and participates in major initiatives like the Human Placenta Project and the Human Connectome Project. Basser’s vision is to transform clinical MRI scanners into quantitative scientific instruments for precision medicine and large-scale brain mapping. Labs and Teams: Section on Quantitative Imaging and Tissue Sciences (SQITS), NICHD, NIH Neuropathology-Neuroradiology Integration Core (with USUHS) Advanced Translational Neuroimaging Research & Development Core Diffusion – Data Processing Center (DPC)
Ravinder R. Regatte, PhD is a Professor at NYU Grossman School of Medicine , affiliated with both the Department of Radiology and the Department of Orthopedic Surgery . His academic work focuses on advanced MRI techniques for musculoskeletal and metabolic imaging. Key Research Interests: Musculoskeletal MRI Quantitative Imaging Biomarkers Deep Learning for Image Reconstruction MR Fingerprinting Metabolic Profiling in Diabetes Email: Ravinder.Regatte@nyulangone.org
Dr. Kristin O'Grady is an Assistant Professor in the Department of Biomedical Engineering and Department of Radiology & Radiological Sciences at Vanderbilt University's School of Engineering. Her research focuses on developing quantitative MRI methodologies for the brain and spinal cord, particularly improving spinal cord MRI for neurological diseases like multiple sclerosis. She specializes in diffusion tensor imaging, functional connectivity analysis, and high-field MRI applications. Her work spans advanced imaging techniques including MP2RAGE, susceptibility-weighted MRI, and phase imaging, with a focus on clinical feasibility and disease markers. She has contributed to studies on spinal cord morphometry, paramagnetic rim lesions, and biological interactions affecting CNS structure. No scientific awards or grants are explicitly listed in the provided materials. Dr. O'Grady collaborates across interdisciplinary teams within the School of Engineering, focusing on translational research in neuroimaging technologies.
