Reza Farivar-Mohseni is an Associate Professor at McGill University , affiliated with the Faculty of Medicine and Health Sciences and the Department of Ophthalmology and Visual Sciences . He serves as a Scientist at the RI-MUHC (Montreal General Hospital site), contributing to the Brain Repair and Integrative Neuroscience (BRaIN) Program and the Centre for Translational Biology . Research Interests: Dr. Farivar-Mohseni’s work focuses on cortico-cortical communication, information processing in the brain, and disruptions in neurological disorders like traumatic brain injury. He specializes in advancing non-invasive brain imaging (MRI) for both fundamental and clinical applications, particularly improving concussion detection and diagnosis. Publications: His research spans high-resolution MRI, visual perception, and functional imaging. Key themes include depth-cue invariance in object recognition, gamma-band neural representations, and cortical deficits in amblyopia. Recent studies (2025–2022) address computational neuroscience, vision screening tools, and neural imaging techniques. Labs & Collaborations: He collaborates with the MGH-MRI Research Platform and works within the Centre for Translational Biology , focusing on translating imaging advancements into clinical tools.
Associate Professor Andre Kyme is an academic staff member in the School of Biomedical Engineering at The University of Sydney. His research focuses on developing enabling technologies for biomedical imaging, including motion compensation in MRI/PET, robotic platforms for image-guided therapy, and cross-disciplinary applications like plant salt uptake analysis using PET. He collaborates with institutions globally and advises students on projects like lameness detection in horses and AI-based motion correction. Research Interests: Kyme's work spans motion correction in medical imaging modalities, medical robotics integration with imaging systems, and innovative applications of imaging technologies in non-traditional fields. His team emphasizes leveraging advancements in computer vision, machine learning, and instrumentation to improve imaging performance and accessibility. Recent Projects: Current research includes MRI-compatible robotic platforms for therapy applications, AI-driven lameness detection in horses, and pediatric neuroimaging improvements. He leads the BREEZE initiative to enhance MRI accessibility for children with cerebral palsy through eye-gaze communication technology. Publications: His work spans 20+ years with over 50 peer-reviewed publications in journals like Physics in Medicine and Biology and IEEE Transactions. Key areas include PET/SPECT/CT motion correction algorithms, robotic systems for medical imaging, and novel imaging applications in plant science. Teaching: Kyme instructs core biomedical engineering courses including thesis supervision and capstone projects at both undergraduate and postgraduate levels. Labs/Teams: Active in the Brain and Mind Centre and Biomedical Imaging, Visualisation and Information Technologies groups at Sydney. Collaborates with industry partners like TeleMedVet and academic institutions including University of California Davis and Chinese University of Hong Kong.
Jeffrey J. Borckardt is a Professor in the Department of Psychiatry and Behavioral Sciences at the Medical University of South Carolina (MUSC). His primary research focuses on neuromodulation techniques, including transcranial direct current stimulation (tDCS), transcutaneous auricular vagus nerve stimulation (taVNS), and transcranial focused ultrasound (tFUS), applied to chronic pain management and opioid use reduction. He leads multidisciplinary clinical trials investigating the efficacy of these technologies in diverse populations, including veterans and patients with hypermobile Ehlers-Danlos syndrome. Key research areas include the neurobiological mechanisms of pain, the integration of psychological interventions like cognitive-behavioral therapy (CBT), and the development of telehealth-delivered therapies. His work emphasizes improving healthcare access disparities and optimizing interprofessional teamwork. He collaborates across institutions, including the VA and international ENIGMA initiatives, to advance translational neuroscience. Recent studies explore the synergistic effects of tAN and tDCS with behavioral interventions, pain biomarkers in spine treatments, and real-time fMRI neurofeedback for addiction. His clinical trials often involve double-blind, sham-controlled designs to rigorously evaluate neuromodulation efficacy. Institutional Affiliations: MUSC College of Medicine, VA Medical Center Research Themes: Neuromodulation, Pain Rehabilitation, Opioid Crisis Mitigation
Grey Clare is a Professor of Materials Chemistry at the University of Cambridge and holds an adjunct professorship at the State University of New York (SUNY) at Stony Brook. She is a Fellow of Pembroke College, Cambridge, and has led major research initiatives, including the Materials Research Interest Group at Cambridge (2010–2015) and the Northeastern Chemical Energy Storage Center (2009–2015). Her research focuses on NMR spectroscopy, energy storage materials, batteries, supercapacitors, and carbon capture technologies. Key contributions include pioneering work on lithium-ion battery electrodes, structural analysis of energy materials via NMR, and advancements in fuel cell and supercapacitor technologies. Clare has held leadership roles in academic and industrial collaborations, including directorships of DOE-funded energy storage centers. Her honors include the Davy Medal (2014), Fellowship of the Royal Society (2011), and multiple international awards for battery research and mentoring. Research Highlights: Development of advanced battery materials, in situ NMR techniques for energy systems, and structural insights into electrochemical interfaces. Awards: Over 20 prestigious awards, including the Royal Society Kavli Medal, Laukien Award, and multiple honorary PhDs. Leadership: Directed interdisciplinary energy storage initiatives, mentored numerous researchers, and contributed to global energy technology advancements.
Daniel B. Vigneron, PhD is a Professor at the University of California, San Francisco (UCSF) Department of Radiology and Biomedical Imaging. He serves as Director of the Hyperpolarized MRI Technology Resource Center (HMTRC), Director of Human Imaging Core Services, Director of Advanced Imaging Technologies SRG, and Operations Director of the Surbeck Laboratory for Advanced Imaging. As a core member of the UCB/UCSF Graduate Group in Bioengineering, Vigneron has established himself as a leader in molecular imaging research with over three decades of experience at UCSF. Vigneron's research focuses on developing advanced functional and metabolic MRI techniques, particularly hyperpolarized carbon-13 technology, for studying prostate cancer, brain tumors, and other diseases. His work enables non-invasive imaging of metabolic processes, allowing clinicians to monitor therapy effectiveness and guide treatments. The HMTRC, which he founded in 2011 with NIH funding and recently secured a 5-year renewal for, has supported 20 external projects domestically and 15 internationally, produced 239 publications, and trained 149 researchers. Vigneron's lab develops novel coil and software techniques for high-field MRI, MR spectroscopy, and diffusion imaging at 3T and 7T for studying brain, prostate cancer, and other organs. His recent publications demonstrate a clear trajectory toward clinical translation of hyperpolarized carbon-13 MRI across multiple organ systems. The research spans abdominal imaging with advanced denoising techniques, cardiac metabolism studies, whole-brain coverage applications, and cerebral perfusion analysis. This work represents a significant shift from basic science toward practical clinical applications in oncology, cardiology, and neurology, with particular emphasis on standardization for multi-center studies. Scientific Awards: 2022 Outstanding Faculty Mentoring Award from UCSF Department of Radiology and Biomedical Imaging Vigneron has mentored 149 trainees throughout his career, with several former students now serving as faculty members including Duan Xu, Peder Larson, and Susan Noworolski. As Principal Investigator overseeing eight grants, he has secured significant NIH funding for the HMTRC and other research initiatives. His administrative leadership extends to co-chairing the department's Safety and Compliance Committee, where he has helped establish robust safety protocols for PET-MR programs. Vigneron's mentoring philosophy emphasizes adapting to individual needs at different career stages, moving from instructor to coach to manager to cheerleader as trainees progress. The Vigneron Lab, located in Byers Hall on the UCSF Mission Bay campus, operates within the Surbeck Laboratory for Advanced Imaging. The lab group develops novel acquisition techniques and hardware for multinuclear MR spectroscopy, with particular focus on hyperpolarized carbon-13 metabolic imaging. The HMTRC serves as a hub for team science, bringing together researchers from diverse disciplines to advance metabolic imaging technology and its clinical applications.
Prof. Ryan Keith Shosted is a full-time tenured Professor at the University of Illinois at Urbana-Champaign , affiliated with the Department of Linguistics , Spanish and Portuguese , American Indian Studies Program , Beckman Institute , Lemann Center for Brazilian Studies , Center for Latin American and Caribbean Studies , and Center for African Studies . He serves as Director of the Program in Translation and Interpreting Studies and leads the Chin-Woo Kim Phonetics Laboratory . Education: Ph.D. , Linguistics, University of California, Berkeley (2006) M.A. , Linguistics, University of California, Berkeley (2003) B.A. , Linguistics, Brigham Young University (2000) Shosted's research focuses on the intersection of phonetics , phonology , and historical linguistics . He pioneered the application of ultrafast dynamic MRI to study the vocal tract's physiological-acoustic mapping in diverse languages, including Hittite cuneiform , Deseret Alphabet , and endangered languages like Q'anjob'al. His work spans speech production modeling , nasalization mechanisms , and cross-linguistic articulatory analysis . The 15 most recent publications demonstrate his leadership in dynamic speech imaging , phonetic-aerodynamic modeling , and historical sound change analysis . Key trends include advanced MRI techniques for speech study, phonetic universals , and historical writing systems as tools for linguistic reconstruction. Scientific Awards: Campus Award for Excellence in Undergraduate Teaching (2021) Dean's Award for Excellence in Undergraduate Teaching (2021) Arnold O. Beckman Award (2009, 2010) Jacob K. Javits Fellowship (2001-2005) Shosted's grant portfolio includes NSF funding for nasalization research (BCS-1651197, BCS-1121780) and NIH collaboration (1R01DE027989-01A1) on cleft palate speech. He has directed 12 graduate students and taught courses ranging from Hittite language to quantitative phonetic methods . The Chin-Woo Kim Phonetics Laboratory , under his directorship since 2007, expanded in 2010 to include articulatory phonetics facilities with EPG, ultrasound, and MRI analysis capabilities. He continues to lead Beckman Institute collaborations in speech imaging technology.
Paul M Thibado is a Professor in the Department of Physics within the College of Arts & Sciences at the University of Arkansas. With over 100 refereed publications and 51 patents worldwide, his work focuses on cutting-edge research in graphene physics and energy harvesting technology. He has secured over $12 million in external research funding from sources including NSF, DoD, and the Walton Foundation, with current support from the WoodNext Foundation. Education: Ph.D. in Physics, 1994, University of Pennsylvania, Philadelphia, PA B.S. in Physics, 1990, San Diego State University, San Diego, CA B.S. in Mathematics, 1990, San Diego State University, San Diego, CA Professor Thibado's primary research focuses on the physical properties of novel two-dimensional systems, particularly pristine freestanding graphene and chemically-functionalized graphene. His work investigates electronic, mechanical, electromechanical, spin-dependent tunneling, and transport properties. A significant portion of his recent research centers on developing multimodal energy harvesting technology using graphene, with power sources including kinetic, solar, thermal, ambient radiation, acoustic, and nonlinear thermal energy. His groundbreaking discovery that thermal fluctuations in graphene can be harnessed to generate usable electrical power represents a paradigm shift in nanoscale energy generation. Analysis of his recent publications (2023-2025) reveals a clear progression from fundamental studies of graphene properties to the development of functional energy harvesting devices. Key research themes include spectrum analysis of thermally driven curvature inversion in graphene ripples, transient thermal energy harvesting at single temperatures using nonlinearity, and creating arrays of graphene solar cells on silicon wafers. His work demonstrates how Brownian motion in two-dimensional materials can be converted into electrical energy through innovative device architectures. Scientific Awards: Senior Member of the National Academy of Inventors NSF CAREER Awardee ONR award recipient NSF MRSEC funding NSF FRG funding NSF MRI funding NSF REU funding NSF-EM funding NRC Post-doctoral Fellow, Naval Research Laboratory (1994-96) Master Researcher Award, Fulbright College (2014) Professor Thibado has successfully mentored numerous students and postdocs, including Dr. Vince LaBella who was elected APS Fellow for clicker development work. His research has been supported by over $12 million in external funding from diverse sources. His laboratory combines advanced scanning tunneling microscopy techniques with electrical measurements to study and harness the unique properties of two-dimensional materials. Future work appears directed toward scaling up graphene energy harvesting technology for practical applications and commercialization, with several patents recently granted for energy harvesting devices and sensors.
Roger Tam is an Associate Professor in the School of Biomedical Engineering (SBME) at the University of British Columbia (UBC), with a joint appointment in the Department of Radiology. He is also the Associate Director of Graduate Studies. His research focuses on machine learning and computer vision applied to medical imaging, particularly in personalized medicine and quantitative image analysis. Tam earned his PhD in computer science from UBC in 2004, specializing in computational geometry and visualization. Education: PhD in Computer Science, UBC (2004) MSc in Computer Science BSc (Honors) Research Interests: Medical imaging biomarkers Machine learning applications in healthcare Quantitative image analysis Personalized medicine His work bridges computer science and clinical medicine, emphasizing translational approaches to improve diagnostic accuracy and patient outcomes. Recent Research Trends: Focus on myelin content analysis in neurological disorders (e.g., multiple sclerosis) Development of efficient machine learning models for medical image classification Impact of physical activity on white matter health Labs & Programs: Directs the Engineers in Scrubs program, which integrates engineering principles into biomedical education. Active in collaborative research initiatives like the Centre for Brain Health and the Canadian Prospective Cohort Study (CanProCo).
Jozien Goense is an Associate Professor at the University of Illinois at Urbana-Champaign (UIUC), holding joint appointments in the Department of Psychology and Department of Bioengineering. She is also affiliated with the Beckman Institute for Advanced Science and Technology and the Neuroscience Program. Her primary research focuses on biomedical imaging, particularly functional MRI (fMRI) and its applications in understanding neurovascular coupling and cortical layer-specific activity. She is recognized for contributions to high-resolution fMRI methodology and laminar imaging techniques. Her work integrates advanced MRI techniques with neurophysiological studies, often using non-human primate models to validate findings in human studies. She has pioneered layer-specific fMRI approaches to map activity across cortical layers, particularly in the motor and visual cortices. Her expertise includes ultra-high field MRI (7T+), BOLD signal modeling, and software development for neuroimaging analysis (e.g., LayNII). Key research themes include the physiological basis of BOLD responses, neurovascular coupling mechanisms, and the application of laminar fMRI to study brain function in health and disease. She has collaborated extensively with neuroscientists, engineers, and clinicians to advance imaging technologies and their translational potential. Publications highlight her contributions to understanding dopamine and acetylcholine effects on neurovascular responses, resting-state gamma-band abnormalities in schizophrenia, and the development of high-resolution imaging protocols. Her work bridges basic science and clinical applications, including studies on vascular contributions to dementia and neuropharmacology. She has received the Beckman Seed Grant as part of a Bioengineering Faculty team, supporting innovative research initiatives. Her lab employs cutting-edge imaging tools and multidisciplinary approaches to unravel brain function at cellular and systems levels.
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.
Jiayun (Peter) Wang is a Postdoctoral Scholar Research Associate in the Department of Computing and Mathematical Sciences at the California Institute of Technology (Caltech). His research focuses on advancing AI-driven solutions in medical imaging, computational imaging, and computer vision. Current projects emphasize applying deep learning to diagnose ocular conditions like dry eye syndrome and improving 3D reconstruction techniques. Collaborations with institutions such as UC Berkeley, Microsoft, and NVIDIA highlight his interdisciplinary approach to solving real-world medical and imaging challenges. Research Interests: Medical AI and Healthcare Analytics Deep Learning Applications in Ophthalmology 3D Reconstruction and Scene Understanding Physics-Informed Neural Networks Compressed Sensing MRI Key Contributions: Developed machine learning models predicting dry eye-related outcomes using meibography images Pioneered physics-aware neural operators for ultrasound lung aeration mapping Advanced open-vocabulary 3D object detection systems Labs/Teams: Collaborates with Caltech's AI4Health initiative and NVIDIA's research group, contributing to medical imaging advancements through interdisciplinary teams.
Dr. Kibret Mequanint is a full Professor at Western University's Department of Chemical and Biochemical Engineering, with cross-appointments in Biomedical Engineering. Holding a PhD from University of Stellenbosch and postdoctoral experience at Technical University of Darmstadt and McMaster University, his research bridges polymer science, materials engineering, and life sciences with applications in Biomaterials , Tissue Engineering , and Regenerative Medicine . His work spans both fundamental and translational research in cell-material interactions , polymer biomaterial design , and therapeutic radiation dosimeters , with technologies transferred to commercial applications. Leading scholar and educator with awards from NSERC, CIHR, and Western University Fellow of: American Institute for Medical and Biological Engineering (AIMBE), Ethiopian Academy of Sciences, International Union of Societies for Biomaterials Science and Engineering, Canadian Academy of Engineering Extensive editorial and panel service for NSERC, CIHR, and international journals His research program has produced over 170 refereed publications, focusing on conductive hydrogels , bioadhesives , and vascular tissue engineering . Recent work on endoscopy-deliverable bioadhesives and snake venom-derived hemostatic gels has attracted global media attention. He has served in leadership roles at the Canadian Biomaterials Society and university governance bodies including Senate and Board of Governors.
Neda Haj Hosseini is a Senior Lecturer and Associate Professor in Biomedical Engineering at Linköping University's Department of Biomedical Engineering (IMT) . She contributes to teaching courses like TBMT56 - Medical Technology and TBME08 - Biomedical Modeling and Simulation , while leading research initiatives in AI-driven cancer diagnostics and biomedical optics. Research Focus: Development of AI methods for cancer diagnostics, optical coherence tomography (OCT) applications, and fluorescence spectroscopy in surgical guidance Affiliations: Center for Medical Image Science and Visualization (CMIV) , Analytic Imaging Diagnostic Arena (AIDA) , Swedish Medical Technology Association Recent Research Trends demonstrate expertise in applying deep learning to: Pediatric brain tumor classification using multimodal imaging Optical biopsy techniques for intraoperative decision support Automated biomarker quantification in histopathology Medical imaging data integrity and algorithm validation Scientific Awards include grants from: Joanna Cocozza Foundation (2022) Swedish Childhood Cancer Foundation (2024) Academic Leadership involves mentoring students in projects such as: "Multiple Instance Attention-based Learning for Brain Tumor Classification" "Vision Transformers for Multiclass Brain Tumor Tissue Classification" "Reaction-diffusion Models for Image-driven Tumor Simulation"
Wenfeng Zhao is an Assistant Professor in the Department of Electrical and Computer Engineering at Binghamton University. He holds a PhD from the National University of Singapore (2014) and BS/MS degrees from Huazhong University of Science and Technology (2007-2009). Prior to this role, he conducted postdoctoral research at the University of Minnesota's Biomedical Engineering Department. His research focuses on neural engineering, compressed sensing, ultra-low-power VLSI systems, and in-memory computing. Key areas include hardware security, biomedical signal processing, and energy-efficient computing architectures. His work spans applications in neural interfaces, cryptographic hardware, and IoT edge devices. Recent publications highlight advancements in block-cipher-in-memory architectures, emotion recognition via EEG analysis, and energy-efficient FPGA accelerators for neural networks. His research also addresses challenges in cryogenic memory systems and MRI-compatible neural recording devices. Zhao's contributions emphasize interdisciplinary approaches at the intersection of hardware design, signal processing, and cybersecurity. His lab develops novel solutions for low-power embedded systems and trustworthy IoT infrastructure.
Andrew Godley, Ph.D., is the Associate Vice Chair of Clinical Physics Operations and Quality and an Associate Professor of Radiation Oncology at UT Southwestern Medical Center. He is part of the Department of Radiation Oncology’s Division of Medical Physics and Engineering. Dr. Godley holds a Texas Medical Physics License and is board-certified in therapeutic radiologic physics by the American Board of Radiology. Education: Received his Ph.D. in high-energy physics from the University of Sydney as part of the NOMAD experiment at CERN. Completed a postdoctoral fellowship at the University of South Carolina with the MINOS experiment at FermiLab. Transitioned to medical physics at the Medical College of Wisconsin. Research Interests: Focus on advanced radiation therapy techniques including brachytherapy, SBRT, Gamma Knife, MR-linac integration, and adaptive radiotherapy. His work emphasizes improving treatment accuracy, patient-specific quality assurance, and innovative approaches to personalized oncology care. Publications: Over 118 peer-reviewed articles, with recent work emphasizing adaptive radiotherapy strategies, MR-guided therapies, and computational tools for dose verification. Professional Contributions: Active in developing clinical protocols for radiation physics operations, including machine QA/commissioning and program development for new technologies like MR-linac systems.
.png)