Irena Živković is a Lecturer in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), where she specializes in Integrated Circuits and leads research in MRI Hardware Development. She is affiliated with the Center for Care & Cure Technology Eindhoven, focusing on cutting-edge biomedical engineering solutions. Her work bridges antenna design, electromagnetic systems, and clinical imaging technology. Her research centers on optimizing MRI hardware for ultra-high-field (7T+) and low-field systems, with innovations in: Coaxial cable coils for enhanced signal-to-noise ratios Monopole antennas for head/spine imaging Twisted-pair transmission lines for flexible, robust array elements Dielectric materials to improve transmit efficiency Recent publications (2023-2025) demonstrate a strong focus on coil miniaturization, electromagnetic interference mitigation, and SAR reduction—critical for advancing high-resolution diagnostic imaging. She teaches specialized courses including Electromagnetic Fields in MRI and Introduction to NMR/MRI , emphasizing hardware-software integration in medical imaging systems.
Grzegorz Chadzynski is a Research Fellow at the Department of High-field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, and concurrently at the Department of Biomedical Magnetic Resonance, University Hospital Tübingen, both affiliated with Eberhard Karls Universität Tübingen. His research focuses on advancing proton magnetic resonance spectroscopy techniques at ultra-high magnetic fields (9.4 T) for neuroscience and clinical applications. His educational background includes: Dr. sc. hum from Eberhard Karls Universität Tübingen (2009-2012) on 'Development of CSI without water suppression for the purpose of clinical applications in the human brain' Master Degree in Experimental Physics, Major in Medical Physics from University of Silesia, Katowice, Poland (2005-2007) Bachelor of Science Degree in Medical Physics from University of Silesia, Katowice, Poland (2002-2005) Dr. Chadzynski's research primarily addresses challenges in chemical shift imaging (CSI) at ultra-high fields, including improved signal-to-noise ratio, spectral resolution, and development of fast acquisition techniques. His work has significant applications in characterizing brain biochemistry and assessing gliomas through metabolite analysis, particularly focusing on detecting 2-hydroxyglutarate as a biomarker for IDH-mutated gliomas. His publications demonstrate expertise in overcoming technical limitations of ultra-high field MRSI, including lipid contamination reduction, phase distortion correction, and optimization of water suppression techniques. His research bridges physics, neuroscience, and oncology, with emphasis on translating advanced MRSI techniques to clinical applications for improved brain tumor diagnosis and monitoring. His research has been supported by competitive grants including the Fortüne junior grant (2014-2016) for 'A novel approach to assess an extended biochemical profile of the human brain by the means of fast and efficient in-vivo proton Magnetic Resonance Spectroscopic Imaging at 9.4 Tesla' (project no. F 1358006.1), a 2-year E13 full-time position funded by the Tübingen Medical Faculty research program.
Matthew Evans is a Clinical Research Fellow in the Department of Surgery & Cancer at Imperial College London's Faculty of Medicine. He specializes in developing high-resolution MRI techniques (7 Tesla) for imaging biomarkers in peripheral neuropathies and neuromuscular diseases. His work focuses on conditions like diabetic neuropathy, HIV polyneuropathy, and motor neurone disease, with future plans to explore neuropathic pain mechanisms. Affiliations: Pain Research Group (Chelsea & Westminster Hospital), Computational, Cognitive and Clinical Neuroimaging Laboratory (C3NL) Education: BSc Psychology (University of Nottingham), Research Assistantship (Dementia Research Institute, UCL), MSc Neuroscience (University of Oxford), DPhil in neuroinflammatory mechanisms in ALS Research Interests: Neuroimaging innovation, neurovascular mechanisms, clinical translation of MRI biomarkers. His DPhil work under Profs Turner, Sibson, and Anthony investigated ALS preclinical models. Current projects aim to non-invasively assess peripheral nerves using 7T MRI, creating 'virtual biopsies' for disease progression tracking. Grants & Training: NIHR Academic Clinical Fellow in Neurology, NIHR Academic Foundation Programme graduate. His training combines clinical practice with advanced research methodologies. Labs: Active member of the Pain Research Group and C3NL, collaborating on computational neuroimaging and clinical translation initiatives.
Professional Overview Anahita Mehta, Ph.D., is an Assistant Professor in the Department of Otolaryngology-Head and Neck Surgery at the University of Michigan, affiliated with the Kresge Hearing Research Institute. Her academic journey includes a BSc in Audiology from the University of Mumbai, an MSc in Audiological Science from University College London, and a PhD in Auditory Neuroscience (UCL, 2015). Postdoctoral training and research associate roles at the University of Minnesota preceded her current position. Research Focus Dr. Mehta’s research explores auditory perception and neural mechanisms underlying pitch perception, particularly in cochlear implant users and normal-hearing listeners. Key areas include: Neural encoding of pitch via EEG/fMRI Context effects and hearing loss impacts Cochlear implant limitations in pitch perception Sensory integration in auditory neuroscience Lab & Collaborations The Mehta Lab investigates pitch perception, sound localization, and auditory processing through behavioral and neuroimaging methods. Collaborations include clinical and basic science studies on hearing rehabilitation and auditory system plasticity. Methodological Expertise Her work employs advanced techniques such as: Electroencephalography (EEG) Functional Magnetic Resonance Imaging (fMRI) Behavioral psychoacoustic testing Key Contributions Recent studies focus on cochlear implant recipient outcomes, pediatric pitch perception, and neurophysiological correlates of auditory perception. Methodological advancements in EEG-based auditory steady-state responses are also central to her work.
Dr. Ka-Loh Li is an Honorary Research Associate at the Division of Informatics, Imaging & Data Sciences, University of Manchester. Her research focuses on advancing MRI techniques to improve therapy monitoring for brain tumors, particularly through low-dose gadolinium contrast studies to reduce long-term health risks. She has pioneered novel methods like dual-temporal resolution DCE-MRI and high-spatial resolution imaging for tumor characterization. Education: PhD in Chemistry/NMR from Clark University (USA), postdoctoral training at City University of New York and Harvard Medical School. Research Interests: Gadolinium toxicity mitigation, DCE-MRI parameter optimization, neuro-oncology imaging. Her work addresses critical challenges in neuroimaging, including accurate microvascular parameter estimation and minimizing patient exposure to contrast agents. Collaborations include Prof. Timothy Cootes, Dr. Daniel Lewis, and Dr. Xiaoping Zhu, focusing on vascular input function modeling and antiangiogenic therapy monitoring in neurofibromatosis patients. Key Projects: Low-dose Gd DCE-MRI for vestibular schwannoma, tumor habitat delineation via ΔR1 mapping. Labs/Teams: Active in Manchester's Digital Futures and Christabel Pankhurst Institute initiatives.
Rajesh Nandy is an Associate Professor in the Department of Population and Community Health at the University of North Texas Health Science Center's College of Public Health. His research focuses on developing novel statistical methods for solving real-world problems in clinical trials, neuroimaging, and biomedical applications. He holds a PhD in Probability/Statistics from the University of Washington and has collaborated on over 20 sponsored projects spanning neurodegenerative diseases, audiology, and cancer research. Education BS and MS in Statistics, Indian Statistical Institute PhD in Probability/Statistics, University of Washington Research Interests Nandy specializes in multivariate statistical analysis, ROC methods, and machine learning applications. His work addresses challenges in functional MRI artifact correction, noise reduction in medical imaging, and epigenetic risk factors for Alzheimer's disease. He has pioneered methods for analyzing neuroimaging data and optimizing clinical trial designs. Grants & Collaborations His active projects include: NIA-funded Health & Aging Brain Study exploring cognitive decline mechanisms NEI-supported research on ocular pathogenesis and tissue engineering NCI projects investigating tumor-derived signaling pathways Epidemiological studies on noise-induced hearing loss and recreational audio device risks Labs & Teams Nandy collaborates with multidisciplinary teams across neuroscience, oncology, and audiology, contributing statistical expertise to translational biomedical research initiatives.
Thomas Decramer serves as Assistant Professor at the Department of Neurosciences within KU Leuven's Faculty of Medicine, where he leads research in the Experimental Neurosurgery and Neuroanatomy group. He holds significant academic governance roles as member of the Biomedical Sciences Doctoral School Committee, Faculty of Medicine Council, and Department of Neurosciences Council, reflecting his institutional influence in medical education and research strategy. His research program centers on translational neurosurgical innovation, with dual ongoing projects investigating endoscopic impacts on olfaction (2024-2028) and diffusion MRI of cranial nerves (2024-2028). Key specialties include skull base surgery, functional neuroanatomy, and advanced neuroimaging applications for Parkinson's disease, epilepsy, and neuro-oncology. His work bridges intraoperative techniques with electrophysiological validation, particularly in visual cortex mapping and subthalamic oscillation modulation through physical interventions. Recent publications (2024-2025) reveal a distinct pattern of clinically driven neuroscience: 60% focus on surgical innovation (endoscopic approaches, implant design), 30% on neurophysiological mechanisms (body representation, beta oscillations), and 10% on diagnostic imaging advances. The research consistently employs multimodal methodologies including photon-counting CT, diffusion tractography, and intracortical recordings, often through large collaborative networks across neurosurgery, oncology, and rehabilitation medicine. Scientific Awards: No awards documented in source materials As co-promotor for two major doctoral projects, Decramer supervises PhD candidates investigating olfactory outcomes in endoscopic surgery and cranial nerve imaging biomarkers. His research is institutionally funded through KU Leuven's internal grant mechanisms, supporting both clinical trials and experimental neuroanatomy work within the university hospital ecosystem. Teaching responsibilities span neurosurgery residency training and graduate neuroscience courses including Advanced Studies in System and Cognitive Neurosciences. The Experimental Neurosurgery and Neuroanatomy research group operates within KU Leuven's University Hospitals Leuven infrastructure, maintaining specialized capabilities in intraoperative neurophysiology, high-resolution imaging, and translational surgical models. Current team collaborations include the Neurology Department's Movement Disorders Unit, ENT Oncology Service, and the Laboratory of Biological Psychology for primate neurophysiology studies.
Tammy Tran, Ph.D., is a Postdoctoral Fellow in the Wagner Lab at Stanford University. Her research focuses on neural mechanisms underlying memory encoding in young adults and its changes in aging and Alzheimer’s disease. She employs virtual navigation to explore memory-spatial navigation interplay and investigates structural changes linked to biofluid and imaging biomarkers through the Stanford Aging and Memory study. Funded by the NIA F32 and Alzheimer’s Association Research Fellowship, her work bridges cognitive neuroscience with clinical biomarkers. Dr. Tran holds a Ph.D. from Johns Hopkins University (2019). Her research interests include Alzheimer’s disease progression, cognitive aging, and neuroimaging techniques. Her publications span topics like cortical selectivity in older adults, histological MRI protocols, and APOE’s role in tau accumulation. Scientific Awards: NIA F32 Fellowship, Alzheimer’s Association Research Fellowship Labs/Teams: Wagner Lab, Stanford Aging and Memory Study Grants: NIA F32 (Fellowship), Alzheimer’s Association Her articles emphasize translational neuroscience, linking molecular, structural, and functional biomarkers to memory performance. Current work explores how attention and pathology influence memory processes in aging populations.
Michael Lustig is an Associate Professor in the Department of Electrical Engineering and Computer Science at UC Berkeley. His research focuses on computational imaging methods in magnetic resonance imaging (MRI), with emphasis on compressed sensing, motion correction, and machine learning applications in medical imaging. He has contributed significantly to the development of open-source tools like SparseMRI and reconstruction algorithms such as ENLIVE and DSLR+. PhD in Electrical Engineering, Stanford University (2008) MSc in Electrical Engineering, Stanford University (2004) BSc in Electrical Engineering, Technion, Israel Institute of Technology (2002) Lustig’s work spans advanced MRI techniques including ultra-short echo time (UTE) imaging , low-rank reconstruction , and physics-informed neural networks . He has pioneered methods for integrating RF motion sensing via beat pilot tones during MRI scans and developed tools for memory-efficient large-scale image reconstruction. His recent publications focus on MRDust (wireless implantable interfaces), Twstr coils (discrete-component-free MRI hardware), and Resonet (noise-trained off-resonance correction). These works reflect trends in self-supervised learning, contact-free motion detection, and hardware-software co-design for diagnostic imaging. Scientific Awards & Fellowships International Society for MR in Medicine Gold Medal (2025) Pioneer Award (2023) ISMRM Fellow (2017) Electrical Engineering Outstanding Teaching Award (2016) Bakar Spark Award (2015) Okawa Research Grant (2014) Sloan Research Fellow (2013) Hellman Fellow (2012) Lustig advises PhD students like Frank Ong and leads research at the MikLab , contributing to open-source software platforms such as SigPy and DeepInPy . His work bridges computational methods, hardware innovation, and clinical translation in MRI.
Sahar Darvish Molla is an Adjunct Assistant Professor in Interdisciplinary Science at McMaster University, with expertise spanning medical physics, radiation oncology, and biomedical engineering. Her work bridges advanced detector technologies and clinical radiation applications. Ph.D. in Medical Physics (2016), McMaster University M.Sc. in Medical Physics (2012), McMaster University Postdoctoral Fellow (2016-2017), McMaster University Postdoctoral Researcher (2018-2019), Nova Scotia Health Authority Medical Physics Resident (2019-2023), Juravinski Cancer Centre Her research focuses on radiation dosimetry , medical imaging , and detector development , particularly for applications in dual-energy x-ray imaging, THGEM detectors, and Monte Carlo simulations. She has contributed to innovations in dose distribution measurement and cancer detection via x-ray fluorescence. Recent publications highlight her work in high-dose-rate brachytherapy , 7 Tesla MRI , and multi-input signal processing systems , reflecting interdisciplinary approaches to radiation science and biomedical engineering challenges. She has served as Instructor for Research Methods in Medical Radiation Sciences (MEDRADSC 3X03) in 2024-2025, indicating active involvement in academic training.
Dr. Lei Li is an Associate Professor at the University of Southern California, specializing in advanced magnetic resonance imaging (MRI) techniques and their applications in neuroscience and biomedical engineering. Their research focuses on quantitative susceptibility mapping (QSM), neural representation models, and neurodegenerative disease diagnostics. Recent publications (2025-2023) highlight innovations in wireless implantable neural interfaces , Multiphoton MRI , and deep learning-based image reconstruction . These works address challenges in neurodegeneration (e.g., Parkinson's, Alzheimer's), iron accumulation mapping , and robotics for MRI scanners .
Barrett Caldwell is a Professor of Industrial Engineering at Purdue University's Edwardson School of Industrial Engineering, with dual affiliation in Aeronautics and Astronautics. Based in the GRIS building on West Lafayette campus, he directs the GrouperLab research group and serves on the EPICS Curriculum Committee. His research centers on Human-Systems Integration across aerospace human factors (aviation weather decision-making, spaceflight crew coordination), healthcare systems engineering (sleep management, chronic care), and distributed team coordination (humanitarian operations, cyber security). He applies systems engineering principles to design safety-critical solutions that enhance human performance through physiological monitoring, machine learning, and augmented reality technologies. Analysis of his 2023-2025 publications reveals a strong trend toward transdisciplinary integration of physiological data streams, resilience engineering, and user-centered design to address challenges in high-stakes environments. His work consistently bridges theoretical human factors with practical applications in aviation, space exploration, and healthcare delivery systems. The GrouperLab serves as the primary research hub for Caldwell's investigations, fostering collaboration across engineering disciplines to develop innovative approaches for complex system coordination and human-automation interaction.
Corbin Covault is Professor and Chair of the Department of Physics at Case Western Reserve University (CWRU), within the College of Arts and Sciences. He is a leading researcher in experimental particle astrophysics, focusing on ultra-high energy cosmic rays, gamma-ray astronomy, and advanced instrumentation for astroparticle detection. B.A., Massachusetts Institute of Technology (1985) Ph.D., Harvard University (1991) His research interests span Experimental Particle Astrophysics , Ultra-high Energy Cosmic Rays , Gamma-ray Astronomy , Dark Matter Detection , and Exoplanet Imaging . He leads the CWRU group in the Pierre Auger Cosmic Ray Observatory and contributes to the Cherenkov Telescope Array (CTA) , with expertise in photodetection, GPS timing, and wireless data systems. Additional projects include Optical SETI (SOFOS), spectral CT imaging, and macro dark matter searches. The selected publications reflect a strong focus on cosmic ray anisotropy, mass composition, neutrino searches, and instrumentation. Key themes include multi-messenger astrophysics , air shower detection , and precision calibration of large-scale observatories. His work is deeply collaborative, often involving major international teams such as the Pierre Auger, IceCube, and TOTEM collaborations. Scientific awards are not listed in the provided text. Dr. Covault leads active research groups involved in major funded projects, including an MRI grant for CTA camera development. His leadership in large collaborations implies advising roles for graduate students and postdoctoral researchers. He is involved in developing next-generation detectors and instrumentation for cosmic ray and gamma-ray observatories. His research group at CWRU is engaged in multiple experimental efforts, including instrumentation development for Auger and CTA, data analysis, and prototype testing at facilities like Mt. Hopkins Observatory. The team collaborates widely across institutions and international consortia.
Dennis R. Schaart is a Professor and head of the Medical Physics & Technology section at the Department of Radiation Science & Technology, Faculty of Applied Sciences, Delft University of Technology (TU Delft). He is also a member of the R&D Program Board of the Holland Proton Therapy Centre (HollandPTC), highlighting his significant role in advancing clinical radiation technologies. His work bridges fundamental physics with medical applications, particularly in imaging and therapy. His primary research interests include Medical Physics, Radiation Oncology, Medical Imaging, Radiation Detection, Dosimetry, and Biomedical Engineering . He specializes in positron emission tomography (PET), time-of-flight methods, proton therapy, and scintillation detector development. His expertise in Monte Carlo simulation and experimental physics enables rigorous evaluation and innovation in detector systems and imaging protocols. The recent publications (2025–2021) reveal a strong trend toward photon-counting X-ray and PET detectors , proton therapy optimization , and novel scintillator materials . There is a clear emphasis on improving spatial, temporal, and energy resolution in imaging, with applications in both diagnostics and treatment planning. The integration of machine learning and Monte Carlo simulations further enhances the predictive and analytical power of his research. Scientific Awards: SNMMI 2015 International Best Abstracts Award Awarded for the highest number of citations for an article published over 2004–2008 Most cited paper in preceding five years (GATE V6 paper) Recognition at Trace 'n Treat conference for radionuclide state determination Dennis Schaart has (co-)authored over 100 journal papers and is a frequently invited speaker, indicating strong leadership and influence in the medical physics community. While no direct mention of students is found, his leadership role and extensive publication record suggest active supervision and mentorship. He is involved in national advisory roles, including serving on committees for the Ministry of Economic Affairs, reflecting broader impact beyond academia. His work is supported by collaborations with institutions like Philips, CERN, and various medical centers. Laboratories and Research Groups: He leads the Medical Physics & Technology research group within the Radiation Science & Technology department at TU Delft. The group focuses on developing and evaluating novel detector systems for medical imaging and therapy, using both experimental and computational approaches. The lab is equipped for scintillator characterization, detector prototyping, and advanced simulations, particularly using the GATE platform.
Professor Phil Dinning is a Principal Medical Scientist in the Department of Surgery and Gastroenterology at Flinders Medical Centre, affiliated with Flinders University. His academic roles include membership in the College of Medicine and Public Health, Flinders Health and Medical Research Institute, and the Medical Device Research Institute. He holds a PhD and B.Sc. (Hons) in Human Physiology. Dinning’s research focuses on functional gut disorders, colonic motility, and gastrointestinal motility mechanisms. His work has led to over 170 peer-reviewed publications and innovations like the fiber-optic high-resolution catheter. His awards include the 2011 Eureka Prize, Engineers Australia’s Sir William Hudson Award (2014), and the Bradfield Award (2014). His research emphasizes clinical applications, such as colonic motility disorders and constipation, with contributions to diagnostic tools like high-resolution manometry and MRI studies. He collaborates internationally on projects like the RECLAIM study, investigating constipation pathophysiology. Dinning’s work bridges clinical practice, device innovation, and translational research, addressing functional gastrointestinal disorders and surgical outcomes.
