Tokuya Miyagi is a Professor at the School of Culture, Media and Society (Waseda University). Holding a PhD in Literature from Kyoto University , his research focuses on European literature , particularly Latin and Greek classical studies . He actively contributes to comparative literature and late antiquity literary traditions . Research Themes : Classical reception, Roman epic/pastoral poetry, Senecan tragedy, Latin epithalamium, plague/war in ancient literature, Hellenistic-Renaissance connections Teaching : Offers courses on Greek/Roman literature , classical Latin , mythology , and comparative studies across multiple schools (Humanities, Global Education Center) Projects : Analyzed Claudian's role in transmitting classical traditions to medieval Europe, studied plague depictions in ancient texts through fieldwork in Athens, explored Senecan tragedy's influence on medieval literature International Collaboration : Conducted research at Florence University (2017-2018), examined classical manuscripts at Laurentian Library His work bridges classical philology with cultural studies , emphasizing virtus and pietas in Roman literature. Key publications include analyses of Seneca's Hercules Furens and Claudian's pastoral vision , often connecting ancient texts with their medieval and Renaissance echoes.
Dr K. A. Jane White is Senior Lecturer in Applied Mathematics at the University of Bath , Department of Mathematical Sciences, and has held this rank since 2003. She is concurrently Director of MASH (the Mathematics Resource Centre) and Vice-Chair of the sigma network , a national body promoting mathematics and statistics support in higher education. Since 1997 she has taught a broad spectrum of applied mathematics units ranging from foundation year service courses to advanced modelling and dynamical systems. Education & Career Timeline PhD in Applied Mathematics, University of Washington, Seattle, USA (1991–1995) Wellcome Trust Biomathematics Research Training Fellow, University of Cambridge, UK (1995–1997) Lecturer in Applied Mathematics, University of Bath (1997–2003) Senior Lecturer in Applied Mathematics, University of Bath (2003–present) Research Interests Jane White’s research lies at the intersection of applied mathematics, biology and public health. She develops and analyses mathematical models for: non-invasive drug monitoring via skin, combining pharmacokinetics with optimal control epidemic dynamics and cost-effectiveness of interventions (HPV vaccination, Chlamydia screening) ecological invasion processes (gypsy moth spread, puffin population decline) Her work integrates optimal control theory , network epidemiology and economic constraints to inform practical policy decisions in healthcare and ecology. Research Trends in Recent Publications Across the 15 most recent journal articles (1996–2013) a clear thematic arc emerges: early work on predator–prey and territorial dynamics (wolf–deer systems) evolved into sophisticated models of infectious disease, culminating in studies that embed economic optimisation within epidemiological frameworks (HPV, Chlamydia, HIV). A parallel stream addresses pharmacokinetic questions for transdermal drug monitoring, linking microscopic membrane processes to macroscopic control strategies. Professional Service & Scientific Recognition 2013–2016: Outer-circle member, Advisory Committee on Mathematics Education (ACME) 2012–present: Vice-Chair, sigma network External Examiner appointments: University of Ulster, University of Cumbria, University of Bath Foundation Year Plenary & invited talks: SIAM CSE (Miami, 2009), MSOR-CETL (Coventry, 2011), ICAM (Hong Kong, 2012) Advising & Grants Jane has supervised nine PhD students to completion and currently mentors three active PhD students working on optimal control of infectious diseases and non-invasive drug monitoring. She regularly offers undergraduate summer internships and MSc projects, supported by sigma-sw and internal university funds. Labs & Collaborative Networks She is affiliated with the Centre for Mathematical Biology at Bath and collaborates internationally with the NIMBioS group at the University of Tennessee and the Irish Mathematics Support Network . Interdisciplinary links include Pharmacy & Pharmacology (University of Bath) and Social Medicine (University of Bristol).
Dr. Shajan Gunamony is the Head of MRI RF Engineering at the University of Glasgow's School of Psychology & Neuroscience. His work focuses on advancing MRI technology, particularly in RF engineering, coil design, and high-field MRI systems. He leads projects involving parallel transmit arrays, SAR management, and neurovascular imaging at 7T and higher field strengths. Grants & Awards: UKRI National facility for 11.7T human MRI (2024–2028) Wellcome Trust 7T Neurovascular Imaging Development (2021–2023) EU Living Lab Precision Medicine (2020–2025) Research Interests: Dr. Gunamony's research emphasizes cutting-edge MRI technology, including RF coil optimization, high-field imaging applications, and clinical translation. His contributions span from hardware development to biophysical modeling, with a focus on improving spatial resolution and safety in neuroimaging. Teams: Collaborates with interdisciplinary teams including physicists, clinicians, and engineers. Supervises research in MRI RF systems and leads the Glasgow MRI engineering group.
Graeme Keith is a Research Fellow at the University of Glasgow's School of Psychology and Neuroscience, affiliated with the Imaging Centre of Excellence within the College of Medical, Veterinary and Life Sciences. He specializes in developing advanced MRI techniques, particularly at ultrahigh field (7T), focusing on spectroscopic imaging, motion correction, and perfusion analysis. His work bridges clinical translation and technological innovation in neuroimaging and cardiology. Education includes a DPhil in Cardiac MRI from the University of Oxford, an MSc in Medical Physics from the University of Aberdeen, and prior roles as a Research Assistant in MRI technology. His research emphasizes optimizing 7T MRI for clinical applications, such as non-invasive brain disease biomarkers and metabolic imaging. Recent contributions include real-time motion correction algorithms, B1+ shimming techniques, and novel neurovascular coil designs. Collaborations span institutions like SINAPSE and Innovate UK-funded projects, advancing 7T MRI hardware and protocols. Awards include grants from the Neurosciences Foundation and Versus Arthritis for disease-specific imaging studies. Labs/Teams: Active in the Imaging Centre of Excellence and collaborates with multidisciplinary teams focused on clinical MRI translation and technical advancements in 7T systems.
Håvard Arnestad is a Research Fellow at the University of Oslo's Department of Informatics, affiliated with the Faculty of Mathematics and Natural Sciences. He is part of the Digital Signal Processing and Image Analysis (DSB) research group and serves as a Group Teacher and Lecturer for the course 'Ultrasound imaging' (IN3015/IN4015). He organizes a bi-weekly journal club focusing on acoustic imaging advancements in sonar and medical ultrasound. Education: Håvard holds a Master's in Engineering Physics from NTNU (Trondheim), specializing in acoustics. His work experience includes roles at NEO (spectroscopy), CERN (superconducting magnet testing), and Cisco (acoustics/audio engineering). Research interests span three core areas: classical/adaptive beamforming, interval arithmetic for beampattern analysis, and subsonic radiation from leaky Lamb waves. His work challenges conventional acoustics assumptions and explores applications in medical ultrasound and sonar systems. Key collaborators include Ole Marius Rindal, Andreas Austeng, Sven Peter Näsholm, and Gabor Gereb. Upcoming conferences include the 2025 Scandinavian Symposium on Physical Acoustics (Geilo), Northern Lights Deep Learning Conference (Tromsø), and the Acoustical Society of America meeting (New Orleans). Past engagements include international symposiums in Germany, Canada, Italy, and the UK. His advising includes MSc students Helene Wold (now at Sonitor) and Chaoran Han (now a PhD candidate). He maintains active profiles on Google Scholar, ResearchGate, ORCID, and LinkedIn, contributing to interdisciplinary research at the intersection of acoustics, signal processing, and numerical simulations.
William A. Grissom, PhD, is the Medtronic Professor of Biomedical Discovery and Innovation at the School of Medicine and a Professor of Biomedical Engineering at Case Western Reserve University's Case School of Engineering. He leads the Grissom Lab, which focuses on advancing MRI techniques through novel RF pulse designs, coil innovations, and computational methods to enhance imaging capabilities for ultra-high and low-field applications. His work includes developing real-time MRI-guided therapies such as focused ultrasound, ultrasound neuromodulation for pain treatment, and robotic laser thermal therapy for epilepsy. Collaborations span institutions like Vanderbilt, Stanford, and Harvard Medical School. His research is funded by NIH, DoD, and the Focused Ultrasound Foundation. Research interests emphasize maximizing MRI's informational value by integrating RF advancements with computational strategies. The lab's projects address challenges in imaging precision, real-time monitoring during interventions, and improving therapeutic targeting accuracy. Notable contributions include low-field MRI system designs, artifact mitigation in transcranial applications, and B1+ selective excitation techniques. Grissom's articles reflect a focus on cutting-edge MRI hardware, thermometry innovations, and translational applications of imaging technologies. His work bridges engineering and clinical needs, aiming to enhance diagnostic and therapeutic outcomes through advanced imaging systems.
Dr. Jacob Willig-Onwuachi is a Clinical Professor specializing in the physics of magnetic resonance imaging. His research advances MRI technology through innovations in: Parallel imaging techniques and reconstruction algorithms Radiofrequency field engineering for improved spatial encoding Integration of quantum and classical descriptions of spin physics Motion compensation methods for thermal imaging applications His work connects fundamental physics principles with clinical applications, particularly in developing faster, more accurate imaging methods and specialized scanner designs.
Judy Day is an Adjunct Associate Professor and Program Manager at The Broad Institute of MIT and Harvard. Her research focuses on integrating mathematical modeling with immunology and epidemiology to study disease dynamics, pathogen transmission, and therapeutic strategies. She specializes in developing computational frameworks to analyze complex biological systems and optimize clinical interventions. Her work emphasizes mathematical approaches to understand inflammation, infectious diseases, and optimal control strategies in critical illnesses. She has contributed to agent-based modeling of healthcare-associated infections, spatio-temporal anthrax transmission, and the development of model-free feedback systems for acute inflammation management. Her interdisciplinary approach bridges computational science, systems biology, and clinical medicine. Key research areas include: Immuno-epidemiology modeling Pathogen transmission networks Optimal control theory for medical applications Mathematical frameworks for small intestinal health metrics Agent-based simulations of public health interventions Her recent articles highlight innovative strategies for mitigating Clostridioides difficile transmission, modeling SARS-CoV-2 disease trajectories, and advancing precision systems medicine through control theory. No scientific awards are explicitly listed in the provided information. Her contributions include advancing computational tools like the 'Papas' framework for parallel parameter studies, demonstrating her commitment to advancing scientific methodology. As a Program Manager at The Broad Institute, she likely oversees collaborative research initiatives and interdisciplinary teams focused on translating mathematical models into clinical and public health solutions.
Arun Natarajan is a Professor in the Electrical Engineering and Computer Science department at Oregon State University . He leads the High-Speed Integrated Circuits Lab , focusing on millimeter-wave and sub-millimeter-wave integrated circuits for wireless communication and imaging applications. Education: Ph.D., Electrical Engineering, California Institute of Technology (2007) M.S., Electrical Engineering, Caltech (2003) B.Tech., Electrical Engineering, Indian Institute of Technology Madras (2001) His research bridges cutting-edge circuit design with practical applications in high-speed wireless systems, radar imaging, and energy-efficient computing. Current projects involve millimeter-wave phased arrays , self-healing circuits , and compute-in-memory architectures . His work has been recognized with the NSF CAREER Award and DARPA Young Faculty Award . Recent publications highlight advancements in analog correlators , full-duplex receivers , and wideband systems , with applications in 5G/6G communication, radar, and optical networks. He previously worked at IBM T.J. Watson Research Center (2007-2012) and serves on the technical program committee of the IEEE RFIC conference.
Thomas Denney is the Mr. & Mrs Bruce Donnellan & Family Endowed Professor in the Department of Electrical and Computer Engineering at Auburn University's Samuel Ginn College of Engineering. He serves as Director of the Auburn University Neuroimaging Center (also known as the MRI Research Center), leading cutting-edge research in biomedical imaging and MRI technology. His educational background includes a Ph.D. in Electrical and Computer Engineering from Johns Hopkins University, an M.S., and a B.S. from Auburn University in the same discipline. Dr. Denney’s research focuses on ultra-high field MRI , cardiovascular MRI , image processing and analysis , image reconstruction , and modeling of multi-dimensional stochastic processes . His work spans critical areas in biomedical engineering, particularly in improving diagnostic imaging through advanced signal and image processing techniques. Additional interests include motion estimation, inverse problems, computer/robot vision, and numerical methods for medical imaging applications. His research has contributed to Auburn’s leadership in neuroimaging, including housing the world’s first field-installed, clinically approved parallel transmit 7T MRI scanner. He is involved in interdisciplinary projects exploring brain plasticity through art and PTSD biomarker identification in older adults. Dr. Denney maintains active research profiles through PubMed and Google Scholar , and his full curriculum vitae is available online. He has not been mentioned as receiving any specific scientific awards in the provided texts. Dr. Denney advises graduate students through his research center and leads a team at the Neuroimaging Center, though no individual students are named. He has not received any named fellowships or grants in the provided information, but his endowed professorship and directorship indicate significant institutional support and recognition. He leads the Auburn University MRI Research Center , a major interdisciplinary facility advancing MRI technology and applications in clinical and research settings. The center plays a pivotal role in Auburn’s engineering and medical research ecosystem, particularly in neuroscience and cardiovascular imaging.
Professor Martina Callaghan is a leading academic in MRI Physics at University College London , affiliated with the UCL Queen Square Institute of Neurology and the Wellcome Centre for Human Neuroimaging . She holds the title of Professor of MRI Physics since 2020 and has been Head of the Research Department of Imaging Neuroscience since 2022. Her research focuses on microstructural and quantitative imaging of the human brain to understand cortical layers and functional organization. BSc in Applied Physics from University of Limerick (2001) PhD in MRI Physics from Imperial College London (2005) Her research interests include: Microstructural imaging of the human brain Quantitative MRI techniques High-resolution image acquisition and reconstruction Modeling neural organization at cortical layers Application of Gadgetron and SPM software Development of 7T MRI systems for intra-cortical studies Her recent publications emphasize advancements in 7T MRI methodologies , motion artifact correction , and biophysical modeling for studying brain microstructure and cognition. She leads the Wellcome-funded Discovery Research Platform for Naturalistic Neuroimaging , aiming to enable neural recordings during real-world interactions. Martina also lectures on the MSc for Advanced Neuroimaging and contributes to international conferences like ISMRM and OHBM. At UCL, she oversees the Physics Group at the Functional Imaging Laboratory (FIL), collaborating extensively in neuroimaging infrastructure development. Her work bridges computational neuroscience , clinical neurology , and medical imaging technology .
Dr Arian Beqiri is a Research Fellow at King's College London , specialising in MRI physics and AI-driven cardiac imaging. Holding a PhD in MRI Physics from the same institution, he bridges electromagnetic safety in ultra-high-field MRI with modern deep-learning solutions for echocardiographic analysis. Education PhD in MRI Physics, King's College London (2015) MSci in Physics, King's College London (2011) Research Interests His work centres on two synergistic pillars: Ultra-high-field MRI engineering: RF shimming, SAR optimisation, and direct signal control at 7 T. AI in cardiac imaging: automated view detection, 3D reconstruction from 2D echo, and robustness of deep-learning models in clinical CT and ultrasound. Across both domains he emphasises safety, computational efficiency, and translational impact. Publication Trends Since 2015 Beqiri has published steadily, pivoting from technical MRI sequence design toward machine-learning applications in echocardiography. His 2024 preprint on black-box CT robustness and 2023 ultrasound foreshortening paper highlight a growing focus on clinical-grade AI validation. Collaborations & Supervision He has one formally supervised student on record and collaborates extensively with cross-disciplinary teams spanning engineering, cardiology, and radiology departments in the UK and abroad. Labs & Teams Work is conducted within the Biomedical Engineering & Imaging Sciences division at King’s, leveraging 7 T MRI platforms and high-performance GPU clusters for deep-learning experiments.
Ewald Weber is a Senior Research Officer at the University of Queensland (UQ), affiliated with the School of Electrical Engineering and Computer Science and the Australian Institute for Bioengineering and Nanotechnology. His primary roles include research and development in biomedical engineering, particularly focusing on MRI technology, RF coil design, and electromagnetic field applications in medical imaging. He holds a Postgraduate Diploma from the University Politechnica of Timisoara. His research interests span biomedical engineering, medical imaging systems, and advanced MRI techniques. Notably, he has contributed to projects involving MRI-Linac integration, RF shielding for high-field MRI, and image reconstruction algorithms. Over the years, Weber has been involved in multiple grants, including projects on high-field MRI optimization and real-time cardiac imaging. His expertise includes designing phased-array RF coils, improving SAR management, and addressing challenges in MRI system design for clinical and preclinical applications. Weber collaborates on projects at the Low Field MR National Imaging Facility (NIF) and has authored over 95 works, including books, journal articles, and conference publications. His work emphasizes interdisciplinary approaches to advancing imaging technologies and their clinical applications.
Dr Gavin Paterson is a Researcher at the School of Psychology & Neuroscience, University of Glasgow. His work focuses on medical physics applications in neuroscience, particularly involving advanced MRI technology development and neurophysiological signal analysis. He has contributed to 7T MRI coil design, high-field imaging safety protocols, and studies on neural oscillations in visual processing. His research interests span biomedical engineering solutions for neuroimaging, including multi-channel transmit arrays and EEG-MRI integration. He has collaborated on projects analyzing causal brain network interactions using MEG data and investigating alpha-band modulations in visual pathways. Notable contributions include developing an 8-channel transmit 32-channel receive 7T head coil and validating close-fitting transceiver coils at 7T. His work bridges engineering innovations with cognitive neuroscience insights, emphasizing both hardware development and neurophysiological mechanisms.
Xinqiang Yan is a Research Associate Professor of Radiology & Radiological Sciences and a Research Assistant Professor of Electrical Engineering and Computer Science at Vanderbilt University's School of Engineering. He leads the Electric and Radiofrequency Lab at the Vanderbilt University Institute of Imaging Science (VUIIS), focusing on novel hardware and algorithmic advancements for MRI and MR-guided focused ultrasound (MRgFUS). His lab has secured eight NIH grants and holds multiple patents, including the self-decoupled coil (Nature Communications, worldwide patent), passive reflectional antennas, and RF-transparent B0 shimming coils. Dr. Yan earned his B.S. in Nuclear Physics from Lanzhou University (2009) and Ph.D. in Particle Physics from the Chinese Academy of Sciences (2014). After postdoctoral training at Vanderbilt, he joined the university’s research faculty in 2016. His research emphasizes improving MRI performance through innovations in RF coils, parallel transmission, and artifact reduction. He actively recruits students and postdocs for projects in MRI hardware development, software algorithms, and clinical translation. Key achievements include Magna Cum Laude Awards (ISMRM 2017) for self-decoupled coil and RAPS circuit innovations, and Best Poster Awards (ISMRM 2021-2022). His work spans MRI hardware miniaturization, bioresorbable RF circuits, and artifact mitigation in transcranial MRgFUS. The lab also develops RF-transparent shimming coils and wireless resonator arrays for high-resolution imaging of joints and soft tissues. Current NIH-funded projects aim to translate these technologies into clinical practice.
