Dr. Rebecca Gosling is an NIHR Clinical Lecturer at the University of Sheffield’s School of Medicine and Population Health, affiliated with the Academic Unit of Primary Medical Care. Her research focuses on computational modeling of cardiac physiology and advanced cardiac MRI techniques, particularly in ischemic heart disease and multi-morbid patients. She leads projects like VIRTU-5 and Virtu-AS, employing 4D flow quantification and virtual coronary interventions to optimize treatment. Dr. Gosling holds a BSc, MBChB, MRCP, and PhD. She is a member of the British Society of Echocardiography and European Society of Cardiology, and previously served as Director for Clinical Translation at the Insigneo Institute for In Silico Medicine. Her grants include a £29,999.80 AMS starter grant (2022) and a £4000 University of Sheffield award (2021). Her teaching spans clinical skills for medical students and lectures on cardiac physiology for the Cardiovascular Medicine MRes, including a new cardiac imaging module in development. Her research integrates AI-driven right ventricular remodeling analysis for pulmonary arterial hypertension and predictive modeling of coronary artery disease outcomes. Key Awards: BHF Clinical Research Training Fellowship (£156,750, 2016). Labs/Teams: Insigneo Institute for In Silico Medicine.
Keng C. Chou is a Professor in the Department of Chemistry at the University of British Columbia (UBC), Faculty of Science. His research spans interdisciplinary fields combining chemistry, physics, and biomedical engineering. Education: PhD in Physics (2001) and MSc (1994) from University of California, Riverside; BS in Physics (1989) from Tunghai University Research Focus: Machine Learning for Chemical Analysis: Integrating AI algorithms with chemical analytical methods for data interpretation Optical Microscopy Development: Creating super-resolution microscopes (e.g., 3D structured illumination) for studying biological systems like virus-host interactions and cardiomyocyte receptors Surface Chemistry Investigations: Studying water interfaces for ice nucleation and oil sands extraction processes using nonlinear optical spectroscopy Publication Trends: Recent work (2018-2023) emphasizes super-resolution microscopy techniques, machine learning applications in chemical analysis, and environmental/industrial surface chemistry. Key areas include Nipah virus assembly, cardiac calcium signaling, and bitumen-water interfacial dynamics.
Luc M.J. Florack is a Full Professor in the Applied Differential Geometry (ADG) group of the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). He also serves as Full Professor at EAISI Health and within the Center for Analysis, Scientific Computing and Applications. His academic credentials include an MSc in Theoretical Physics and a PhD in Medical Image Analysis, both earned at Utrecht University with honors (top 2%). Professor Florack's research centers on multiscale and differential geometric representations of complex imaging data , with primary applications in magnetic resonance imaging (MRI) techniques, particularly diffusion and tagging MRI. His work bridges theoretical mathematics with clinical applications through geometrical reformulation of image analysis challenges, including geodesic tractography for brain connectivity mapping (connectomics) and deformation/strain analysis for myocardial function quantification. His research aims to integrate these advanced mathematical techniques into clinical workflows. His scientific contributions have been recognized with several prestigious awards: “Een gepersonaliseerd zorgpad voor iedere hersentumorpatiënt” (NWO Scientific Project, 2020) PhD obtained with judicium cum laude (1993) “The Problem of Scale in Biomedical Image Analysis” (NWO Vici Scientific award, 2005) With approximately 200 peer-reviewed publications, Professor Florack has significantly advanced medical image analysis. His publication trends show consistent output with recent work focusing on diffusion tensor imaging, white matter structure analysis, and cardiac MRI applications. He has served on the editorial board of the Journal of Mathematical Imaging and Vision and reviewed for over 30 academic venues. In 1997, he co-founded the International Scale Space Conferences series (SSVM). He actively teaches courses in Differential Geometry and Tensor Calculus. Professor Florack serves as a Member of the Management Team 3TU.AMI representing TU/e and on the Advisory Board for Mathematics (‘Wiskunde Tafel’) of the Dutch Science Foundation NWO. His research contributes to UN Sustainable Development Goals, particularly in health-related areas through advanced medical imaging technologies.
Behzad Ebrahimi is an Assistant Professor in the Department of Radiation and Cellular Oncology at the University of Chicago. He holds a PhD and MSc in Biomedical Engineering from the University of Michigan, followed by a residency in Medical Physics at the University of Miami and postdoctoral research appointments in Functional Imaging (Harvard School of Medicine, MGH) and Physiological Imaging (Mayo Clinic). University of Michigan: PhD Biomedical Engineering (2010), MSc Biomedical Engineering University of Miami: Residency in Medical Physics Harvard School of Medicine, MGH: Postdoctoral Research in Functional Imaging Mayo Clinic: Postdoctoral Research in Physiological Imaging His research focuses on radiomics and medical imaging applications for renal and cardiovascular diseases. Key areas include: renal artery stenosis , magnetization transfer MRI , oxidative stress imaging , cell-based therapies , and AI integration in radiation oncology . His 2024 work connects cerebral blood flow heterogeneity to glioblastoma prognosis, while earlier studies explore kidney-heart interactions and mitochondrial protection mechanisms. Publications demonstrate expertise in quantitative MRI , PET imaging , and computational physiology . He investigates biomarkers for renal fibrosis , shockwave therapy for ischemia , and AI tools like ChatGPT in clinical radiation oncology workflows. Current affiliations include the University of Chicago's Radiation and Cellular Oncology Department.
Archontis Giannakidis is a Senior Lecturer in Data Science at the School of Science and Technology , Nottingham Trent University (NTU). He leads modules in Discrete Mathematics & Computational Complexity (Year 2) and Convex Optimisation (Year 3), while supervising undergraduate and Masters dissertations. Education: PhD in Electronic Engineering (Inverse Problems), University of Surrey (2010) Research Interests focus on applying Deep Learning and Machine Learning to biomedical data processing, particularly in Biomedical Image Analysis , Convolutional Networks , and Diffusion MRI . His work emphasizes automating intellectual tasks, efficient data representation, hidden pattern discovery, and decision optimization in healthcare and environmental contexts. Recent Article Trends highlight his expertise in 2D echocardiography-based cardiac quantification , MRI-driven ACL tear diagnosis , and landslide-tsunami prediction via geometry-invariant machine learning. These studies often integrate uncertainty modeling, attention mechanisms, and lightweight architectures for clinical and environmental applications. Scientific Awards : Fellow of the Higher Education Academy (FHEA) Advisory Roles include mentoring PhD students Tuan Aqeel Bohoran (Marie Skłodowska-Curie-funded) and David Gwillym Jenkins (internal funding), alongside visiting/external PhD candidates Michael Lystbaek (Aarhus University) and Athanasios Siouras (University of Thessaly). He has received grants from HORIZON 2020 , EPSRC , and Innovate UK , and collaborates with institutions like the Archimedes Research Unit (Greece) and National Heart and Lung Institute , Imperial College London. Professional Activity includes editorial board membership for Frontiers in Physiology , peer reviewing for journals like IEEE Transactions on Medical Imaging , and external examining for University of Strathclyde’s MSc programs. He also contributes to conference organization and Portuguese grant evaluation panels.
Derek J. Dosdall, PhD, is an Associate Professor at the University of Utah, affiliated with the Department of Surgery (Division of Cardiothoracic Surgery) and holds adjunct appointments in the Department of Bioengineering and the Department of Internal Medicine (Division of Cardiovascular Medicine). His research focuses on mapping cardiac arrhythmias, particularly atrial fibrillation, using chronic animal models to investigate conduction disturbances and the role of fibrosis in arrhythmogenesis. Education: PhD in Bioengineering, Arizona State University Postdoctoral Training, University of Alabama at Birmingham His work explores the specialized cardiac conduction system in ventricles and its role in arrhythmia onset, alongside computational modeling for personalized ablation strategies. Recent publications highlight advancements in left bundle branch pacing, gene therapy for heart failure, and machine learning applications in electrogram classification. Key trends in his research include: chronic animal models of arrhythmias, fibrosis quantification, ablation optimization, and integration of artificial intelligence in cardiac signal analysis. He has authored patents on low-energy defibrillation methods and atrial fibrillation treatment systems.
Michel Godin is a Full Professor in the Department of Physics at the University of Ottawa's Faculty of Science. His research focuses on developing micro/nanofluidic technologies for biomedical applications, including medical diagnostics, regenerative medicine, and food safety. His work bridges biophysics, engineering, and molecular biology to create innovative platforms for cellular therapy, biosensing, and tissue engineering. Key research areas include microfluidic devices for cell encapsulation, nanopore sensors for molecular analysis, and mechanotransduction studies in 3D microtissues. His Godin Lab has pioneered techniques such as microgel encapsulation for targeted drug delivery and strain-based studies of cellular behavior. Recent work emphasizes integrating nanotechnology with biological systems to address challenges in cardiovascular repair, lung disease treatment, and precision diagnostics. Publications highlight advancements in lab-on-a-chip systems, nanomechanical resonators, and biomaterial design. His research has practical applications in improving stem cell therapies, enhancing diagnostic accuracy, and advancing personalized medicine. No scientific awards are explicitly listed in the provided texts. As a faculty member, Godin contributes to interdisciplinary collaborations and graduate training in biomedical engineering and physics. His lab serves as a hub for developing next-generation microfluidic tools and biocompatible materials with real-world clinical and industrial impact.
Enrique L. Ostrzega, MD is a Clinical Professor of Medicine at the Keck School of Medicine, University of Southern California . He is affiliated with Keck Medical Center of USC and LAC+USC Medical Center , specializing in Cardiovascular Disease . Dr. Ostrzega is fluent in both English and Spanish. Graduated from Universidad Nacional de Cordoba, School of Medicine (1973) Completed three fellowships in cardiology at Ichilov Hospital, Cedars-Sinai Medical Center, and LAC+USC Medical Center Dr. Ostrzega’s research focuses on cardiovascular disease, heart failure, arrhythmias, and pharmacological therapies. His work explores hemodynamic effects of nitrates, diagnostic imaging techniques (thallium tomography, echocardiography), and management of rare cardiac pathologies. The 15 most recent publications (1989–2020) emphasize heart failure pharmacology , cardiac imaging , and diagnostic challenges in cardiology. Key themes include nitrate tolerance mechanisms, thallium-201 imaging validation, mitral valve pathology, and arrhythmia studies.
Rene R S Packard serves as an Associate Professor-in-residence in both Medicine and Physiology at the University of California Los Angeles (UCLA) David Geffen School of Medicine. With a comprehensive background spanning clinical medicine, cardiovascular biology, and advanced imaging techniques, Dr. Packard has established herself as a leading researcher in cardiac imaging and cardiovascular pathophysiology. Dr. Packard's research interests focus on advanced cardiac imaging techniques, particularly PET imaging applications in cardiology, myocardial perfusion assessment, atherosclerosis characterization, and anthracycline-induced cardiotoxicity. Her work bridges molecular imaging, cardiovascular physiology, and clinical applications, with particular emphasis on developing novel imaging approaches for coronary artery disease diagnosis and management. She has pioneered research in 18F-flurpiridaz PET imaging, quantitative myocardial blood flow analysis, and the development of advanced imaging techniques for assessing cardiac structure and function. Her extensive publication record demonstrates consistent contributions to the fields of nuclear cardiology and cardiovascular imaging, with recent publications (2022-2025) focusing on emerging PET radiotracers, quantitative image analysis techniques, and clinical applications of advanced imaging in coronary artery disease. Dr. Packard's research shows a clear trajectory toward precision medicine applications in cardiology, particularly in improving diagnostic accuracy and understanding disease mechanisms through advanced imaging modalities. Scientific Awards and Honors: David Geffen School of Medicine Dean's Seed Grant, UCLA (2022-2023) Lauren B. Leichtman and Arthur E. Levine Cardiovascular Discovery Fund Investigator, UCLA (2021-2023) Basic Cardiovascular Sciences Early Career Mentorship Program, American Heart Association (2020) 1st Place, Cardiovascular Council Young Investigator Award, Society of Nuclear Medicine and Molecular Imaging (2019) Kenneth Brown Award, American Society of Nuclear Cardiology (2018) Outstanding Distinction in Cardiology Fellowship Award, Cardiovascular Research Foundation of Southern California (2016) Outstanding Research Award, Cardiology Fellowship Training Program, UCLA (2015) T32 Fellowship, NIH/NHLBI Cardiovascular Scientist Training Program, UCLA (2012-2015) Tibor Fabian Research Award, UCLA (2012-2015) Dr. Packard has secured significant research funding as Principal Investigator for multiple NIH and foundation grants focusing on cardiovascular imaging, anthracycline-induced cardiotoxicity, and advanced imaging techniques for plaque characterization. Her research program integrates multiple disciplines including nuclear medicine, cardiovascular physiology, biomedical engineering, and computational analysis to advance cardiac imaging and diagnostics.
Dr. Perla Ayala is an Associate Professor in the Biomedical Engineering Department at California State University, Long Beach , where she has been since Fall 2016. Her research focuses on engineered therapeutic systems for tissue regeneration, integrating microstructural design and stem cell therapies . Her academic journey includes a Ph.D. in Bioengineering from the University of California, Berkeley and San Francisco (2011), followed by a postdoctoral fellowship at Harvard Medical School and the Wyss Institute (2012-2016). Research Trends : Dr. Ayala's publications span cardiac repair microstructures , immune-modulating tissue systems , and anti-infective biomaterials . Key themes include 3D biomaterial scaffolding , stem cell delivery optimization , and topography-driven cellular responses . Current Status : Contactable at perla.ayala@csulb.edu , her Office Hours indicate no instruction for Spring 2024.
Simone Pezzuto is an Assistant Professor in the Department of Mathematics at the University of Trento, specializing in computational cardiac electrophysiology and mathematical biology. His research integrates mathematical modeling, numerical analysis, and biomedical applications. Research focuses on inverse problems in electrocardiography, arrhythmia mechanisms, and cardiac digital twins. Recent work (2024-2025) develops novel methods for Purkinje network reconstruction, atrial fibrillation source localization, and fibrosis-based inducibility prediction. Computational approaches include physics-informed neural networks, multirate schemes, and eikonal modeling for efficient simulations. Key innovations address cardiac conduction system identification from surface ECGs, ablation strategy optimization, and anatomically-accurate atrial modeling. Methodological contributions span regularization techniques for ill-posed problems and parallel-in-time algorithms for large-scale electrophysiology simulations.
Michel White is a Clinical Professor at the Université de Montréal's Faculty of Medicine, Department of Medicine. His research focuses on the functional role of kinins in cardiovascular pathophysiology, including urine kinin quantification and their effects on cardiac function and exercise tolerance. He leads and co-leads multiple research projects, such as the 2013-2021 grant from the Fondation de l'Institut de cardiologie de Montréal. Affiliated with the ICM Research Centre, he has supervised numerous PhD and Master's students since 2007. Research Expertise: Cardiomyopathies, Myocardial Infarction, Clinical and Fundamental Pharmacology Grants: Includes projects on heart failure, pharmacotherapy, and kinin mechanisms His work bridges clinical and laboratory research to improve cardiovascular health outcomes.
Spencer Bowen is an Assistant Professor at UT Southwestern Medical Center's Department of Radiology and a member of the Radiology Research section. He specializes in nuclear tomographic scanner development for precision imaging in oncology, neurology, cardiology, and rheumatology. Education: B.S. in Biomedical Engineering from University of Washington; Ph.D. in Biomedical Engineering from University of California, Davis Previous positions: Research Assistant Professor at Fralin Biomedical Research Institute; Research Fellow at Massachusetts General Hospital Research Focus: Development of advanced PET imaging technologies including: Nuclear tomographic scanners for hybrid PET-CT/MR systems Partial volume correction methods Transmission source aided attenuation correction Deep learning applications in medical imaging Quantitative imaging techniques for clinical care Advanced acquisition/reconstruction algorithms His work impacts oncology , neurology , and cardiology imaging. He has contributed to more than a dozen publications including featured works in the Journal of Nuclear Medicine.
Dr. Gareth Matthews is an NIHR Clinical Lecturer at the Norwich Medical School, University of East Anglia (UEA), with academic affiliations at the Norfolk and Norwich University Hospital (NNUH). His academic background includes an MB PhD from the University of Cambridge and training at Royal Papworth Hospital as an NIHR Academic Clinical Fellow. He specializes in mechanisms, risk stratification, and treatment of atrial and ventricular arrhythmias, with a focus on cardiovascular imaging and hemodynamic modeling. Key research projects include the NIHR Clinical Lecturer program (2022–2026) and the Clinical Relevance of Right Heart Flow Haemodynamics (2025–2028), funded by Edwards Lifesciences. His work leverages cardiac MRI and pressure-volume loop analysis to improve diagnostics and prognostics in heart failure, particularly HFpEF and HFrEF. Collaborations span institutions across the UK and internationally, emphasizing multi-centre studies. Research interests extend to arrhythmia mechanisms, imaging biomarkers (e.g., aortic flow abnormalities, left atrial strain), and translational cardiovascular medicine. Recent studies highlight MRI-derived models for right atrial pressure and sex-specific pulmonary capillary wedge pressure, alongside investigations into cardiovascular health in cancer patients. His publications reflect a blend of clinical and methodological innovation. Dr. Matthews has been awarded grants totaling £[X] through NIHR and industry partnerships. His work is disseminated through high-impact journals like Trends in Cardiovascular Medicine and Heart , with a focus on peer-reviewed articles and abstracts. He advises no formal trainees but collaborates extensively with researchers and clinicians in cardiology and imaging.
Jason Betson serves as Senior Lecturer in Paramedicine within the School of Nursing, Midwifery and Paramedicine at the Faculty of Health Sciences. His academic role focuses on paramedic education and research in emergency medical care contexts. Research interests center on physiological and psychological stressors in paramedic practice, with emphasis on shift work impacts, cognitive load during high-acuity scenarios, and cardiac emergency management. Key areas include sleep disruption in early-career clinicians, psychophysiological measurement during simulations, and evidence-based prehospital interventions for myocardial infarction. Analysis of his 2019-2025 publications reveals consistent methodological innovation, particularly in applying functional near-infrared spectroscopy for cognitive load assessment and developing threat-response frameworks for clinical education. His work bridges emergency medicine practice with educational psychology to enhance paramedic training efficacy and patient safety outcomes.
