Christophe Grova is an Associate Professor at the Department of Neurology and Neurosurgery at McGill University , with adjunct status in the Department of Biomedical Engineering . He leads the Multimodal Functional Imaging Laboratory , focusing on integrating EEG, MEG, fMRI, and fNIRS to study brain mechanisms in epilepsy and sleep disorders. Expertise in multimodal neuroimaging techniques Develops advanced source localization algorithms Key applications in epilepsy diagnosis and sleep physiology His research bridges neuroimaging and clinical translation , with a focus on: EEG-fNIRS integration for whole-night sleep monitoring Validation of MEG and fMRI connectomes with intracranial EEG Computational modeling of neuron-astrocyte interactions Development of open-source tools like NIRSTORM The lab collaborates across institutions, including the McConnell Brain Imaging Centre and Concordia University . Current projects emphasize glymphatic system dynamics , epileptogenic zone localization , and neurovascular coupling mechanisms.
David Heeger is a Silver Professor and Professor of Psychology and Neural Science at New York University. His research focuses on computational neuroscience, neural circuits, and cognitive modeling. He leads the Computational Neuroimaging Laboratory and has contributed extensively to understanding visual perception, attention mechanisms, and cortical processing. B.A. in Mathematics (University of Pennsylvania, 1983) Ph.D. in Computer Science (University of Pennsylvania, 1987) Postdoctoral Fellowship at MIT Media Lab (1987-1990) Former faculty at Stanford University (1991-2002) His research spans Neuroscience , Machine Learning , and Visual Perception . Key contributions include normalization models in neural circuits, computational frameworks for attention dynamics, and neuroimaging techniques. Recent work explores traveling waves in the visual cortex, hypoxia effects on cognition, and applications of recurrent neural networks. Scientific awards include: David Marr Prize in computer vision (1987) Alfred P. Sloan Research Fellowship (1994) Troland Award from the National Academy of Sciences (2002) Margaret and Herman Sokol Faculty Award (2006) He teaches courses on perception, computational neuroscience, and sensory-motor systems, with handouts covering signal detection theory, neural integrators, and linear systems. His publications (15 most recent) address topics ranging from attention mechanisms in binocular rivalry to arterial oxygen desaturation impacts on cognitive performance, normalization in neural networks, and cortical dynamics in visual processing.
Dr. W.J. (Wilson) dos Santos Silva is an Assistant Professor at the Faculty of Science , University of Utrecht, specializing in AI & Data Science and Biology . His research focuses on creating explainable and robust AI models for multimodal multi-centre medical data , with emphasis on privacy-preserving machine learning and out-of-distribution generalization . PhD in Electrical and Computer Engineering (2022), University of Porto Master's and Bachelor's in Electrical and Computer Engineering (2016), University of Porto Research Interests include: Explainable AI for medical decision-making transparency Privacy-Preserving Machine Learning in healthcare Multi-Centre Data Analysis across institutions Medical Imaging applications in oncology and neurology Recent Publications demonstrate expertise in: Medical image segmentation techniques Cross-modal learning approaches Federated learning for privacy Biomedical data interpretation Generalization in heterogeneous datasets Scientific Contributions include organizing the iMIMIC workshop at MICCAI 2024 and mentoring students receiving competitive awards. Students & Collaborators : PhD Candidates: Valentina Corbetta, Daan Boeke, Miriam Cobo, Aniek Eijpe, Jan van Eck Postdoctoral Researchers: Soufyan Lakbir Former Students: Tingyang Jiao, Laura Latorre, Filipe Campos, etc. Laboratory develops AI solutions for medical imaging , multi-centre collaboration , and ethical AI in healthcare contexts.
Dr. Kees de Hoogh is an Assistant Professor and Researcher at Utrecht University's Faculty of Veterinary Medicine, Department of Population Health Sciences, and the Institute for Risk Assessment Sciences (IRAS). He holds a joint appointment as Assistant Professor at the Swiss Tropical and Public Health Institute in Basel. His research focuses on spatial modeling and exposure assessment for environmental health studies, with specialization in exposome research and air pollution analysis. Primary research interests include: Advanced spatio-temporal modeling techniques using satellite data Exposome studies linking environmental exposures to health outcomes Air pollution exposure assessment methodologies Geographic Information Systems (GIS) applications in public health His recent publications demonstrate a strong focus on air pollution modeling, exposure assessment methods, and environmental health impacts across European populations. Research consistently explores the relationships between environmental factors (air quality, green space, temperature) and health outcomes including metabolic disorders, respiratory diseases, dementia, and stroke. Dr. de Hoogh leads significant research initiatives: Co-Principal Investigator of EXPANSE (European project) Co-PI of NWO Gravitation programme Exposome-NL Co-PI of Utrecht Exposome Hub Principal Investigator of MOBI-AIR studies Contributor to BioSHARE, ESCAPE, and ELAPSE projects He works within the Institute for Risk Assessment Sciences (IRAS) and collaborates through the Utrecht Exposome Hub, focusing on interdisciplinary approaches to environmental health challenges.
Michael Sawada is a Full Professor at the University of Ottawa in the Department of Geography, Environment and Geomatics . With a career spanning decades, his work bridges geomatics, health geography, and machine learning applications in spatial analysis. Ph.D. in Geography (2001) M.A. in Geography (1996) B.A. (Hon.) in Geography with concentration in Philosophy (1994) His research focuses on geospatial methodologies for addressing complex environmental and public health issues, including: Health disparities and disease distribution Machine learning for remote sensing and land use analysis Natural hazard risk assessment and mitigation Urban healthscapes and climate change impacts Recent publications highlight his innovative integration of deep learning with geospatial datasets , including analysis of neighbourhood-level Lyme disease risks and neural network-enhanced lichen cover mapping . His work also explores income polarization patterns in Canadian metropolitan areas and health service utilization trends. Professor Sawada supervises graduate students including Krutiben Mehta , Sarah Gebert , Zhewen Luo , Raziyeh Ramezani , and Amirreza Farshchin . He teaches advanced geomatics courses like GEG 6102 - Advanced Geomatics , emphasizing digital earth technologies and spatial information systems.
Richard Bronen, MD is a Professor of Radiology and Biomedical Imaging and Professor of Neurosurgery (Secondary) at Yale School of Medicine. He serves as Director for Faculty Affairs in the Department of Radiology & Biomedical Imaging and is the imaging specialist for the Yale Comprehensive Epilepsy Center and Yale Pituitary Service. His educational background includes: MD from Emory University (1980) Residency in Diagnostic Radiology at Baylor Affiliated Hospitals, Houston, TX and Hahnemann Hospital, Philadelphia, PA Fellowship in Neuroradiology at Jackson Memorial Hospital, University of Miami, and Yale-New Haven Hospital Dr. Bronen's research focuses on advanced imaging techniques for neurological conditions, particularly epilepsy and pituitary disorders. His work spans several key areas: MR Imaging of patients with seizures and surgical epilepsy Temporal lobe embryology and anatomy Hippocampal sclerosis and focal cortical dysplasia Application of machine learning techniques to improve imaging detection of brain disorders MR imaging of pituitary anomalies and disorders His recent publications (2022-2025) demonstrate a strong focus on the intersection of artificial intelligence and medical imaging, particularly for epilepsy diagnosis and brain tumor characterization. These works highlight his ongoing commitment to advancing diagnostic capabilities through technological innovation. Dr. Bronen has received recognition as a "Top Doctor" in Connecticut from 2014-2022. As Director for Faculty Affairs, Dr. Bronen oversees faculty career development for the Department of Radiology & Biomedical Imaging. His administrative experience also includes previous roles as Section Chief and Vice Chair at Yale School of Medicine.
Dr. Mohammad Nami serves as Associate Professor of Cognitive Neuroscience and Clinical Neuropsychology at the School of Health Sciences and Psychology, Canadian University Dubai. He concurrently directs the Brain, Cognition, and Behavior Unit at BrainHub UAE and maintains associate membership in the Harvard Medical School Alumni network. Previously, he held leadership roles as Head of Neuroscience Department and Vice Chancellor for Research at Shiraz University of Medical Sciences. His academic credentials include: PhD in Cognitive Neuroscience from Institute for Cognitive Science Studies Dr. Nami's research centers on the interdependence of mental health and sleep health, with primary expertise in cognitive neuroscience, clinical neuropsychology, and sleep disorder interventions. He advocates that cognitive and affective potential can only be fully realized through integrated sleep-mental health approaches, emphasizing neuro-cognitive fitness and neurological aspects of sleep pathologies. His work bridges clinical practice with neuroscience to develop practical interventions for cognitive optimization. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) Sleep-neuroscience interfaces using quantitative EEG for insomnia and sleep disorder diagnostics, (2) Cognitive performance assessment in safety-critical occupations like aviation and industrial control rooms, and (3) Neurocognitive rehabilitation techniques for stroke, cerebral palsy, and neurodegenerative conditions. His methodology frequently combines clinical trials with advanced neuroimaging and computational modeling. As an associate member of Harvard Medical School Alumni and Harvard Alumni Entrepreneurs, Dr. Nami contributes to academic-industry knowledge translation. The provided text does not reference specific scientific awards. With 173 peer-reviewed publications (H-index 27, i10-index 77 as of August 2025), his research program demonstrates significant scholarly impact. While student mentorship details are absent, his leadership of the Brain, Cognition, and Behavior Unit suggests active supervision of research personnel. His publication record indicates consistent grant funding, particularly for sleep-neuroscience and occupational safety projects. The Brain, Cognition, and Behavior Unit at BrainHub UAE functions as his primary research hub, conducting studies on sleep-cognition interactions, neurocognitive fitness metrics, and real-world applications of neuroscience findings. Current initiatives appear focused on digital health tools for stress management and neurophysiological monitoring in occupational settings.
Abbas Kouzani is a Professor of Engineering at the Deakin University School of Engineering , with a focus on cutting-edge biomedical engineering and AI applications. His work bridges 3D/4D printing and clinical challenges , particularly in dysphagia management and neurological disorders.
Kaomei Guan-Schmidt is a Full Professor at the Institute of Pharmacology and Toxicology within the School of Medicine at TU Dresden, where she leads cutting-edge research in cardiovascular regenerative medicine and stem cell biology. Her work primarily focuses on the maturation and functional assessment of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) for disease modeling and therapeutic applications. Her research interests include: Cardiovascular Regenerative Medicine Stem Cell Biology Cardiomyocyte Maturation Mechanisms Electrophysiological Characterization Mitochondrial Dynamics in Cardiac Cells Translational Cardiac Disease Modeling Recent publications demonstrate her innovative approaches to enhancing iPSC-CM maturation through integrated strategies involving electrostimulation, metabolic conditioning, and nanoscale engineering. Her work bridges fundamental stem cell biology with clinical cardiology, particularly in biomarker discovery for conditions like atrial fibrillation in stroke patients. Current research trends show strong emphasis on AI-driven analysis of cellular maturity and mitochondrial development in cardiac models. Dr. Guan-Schmidt maintains an active publication record in high-impact journals including Nature Communications and Stem Cells, reflecting her significant contributions to regenerative cardiology. Her collaborative network spans multiple disciplines within TU Dresden's medical and bioengineering research centers. She is affiliated with TU Dresden's Center for Regenerative Therapies Dresden (CRTD) and contributes to interdisciplinary initiatives in the Center for Molecular and Cellular Bioengineering (CMCB), focusing on translating stem cell research into clinical applications for cardiac repair and disease modeling.
Dr. Arianna L. Gianakos is an Assistant Professor of Orthopaedics & Rehabilitation at Yale School of Medicine, specializing in foot and ankle orthopedic surgery and sports medicine. She serves as a clinician, researcher, and educator with a focus on minimally invasive approaches to treating sports-related injuries. PhD Candidate, University of Amsterdam (Gender & Sex Related Differences in Foot & Ankle Surgery) International Foot and Ankle IONA and Sports Medicine Fellowship, NYU Langone Health Orthopedic Foot and Ankle Surgery Fellowship, Harvard-Massachusetts General Hospital Orthopedic Surgery Residency, Rutgers Health DO, Lake Erie College of Osteopathic Medicine BS, McGill University Dr. Gianakos' research focuses on gender- and sex-related differences in foot and ankle injuries, cartilage regeneration, tendon healing, and bone growth. She has pioneered work in in-office needle arthroscopy and has investigated the application of AI in orthopedic diagnostics. Her clinical practice emphasizes personalized treatment plans for athletes and active individuals with foot and ankle conditions. Analysis of her recent publications (2024-2025) reveals three key research trends: 1) Investigation of gender disparities and representation in orthopedics, 2) Exploration of AI applications in diagnostic accuracy for foot and ankle conditions, and 3) Advancement of minimally invasive surgical techniques including needle arthroscopy and distraction arthroplasty. Her work bridges clinical practice with innovative research approaches. #Trailblazer Award from Women in Medicine Summit (2022) Courage Award from Ruth Jackson Orthopedic Society (2021) Scientific Paper Winner from AOAO (2020) As an active researcher, Dr. Gianakos collaborates with colleagues across multiple institutions on studies related to foot and ankle biomechanics, gender differences in orthopedic outcomes, and innovative surgical techniques. Her commitment to mentorship extends to supporting women in orthopedics through various professional organizations and initiatives aimed at increasing diversity in the field. Dr. Gianakos leads the 3D Collaborative for Medical Innovation (3DC) and has established herself as a specialist in in-office needle arthroscopy procedures. Her work with elite athletes across multiple sports has informed her approach to returning patients to activity safely and efficiently.
BOHI Amine is a researcher at CESI (School of Engineering and Digital Tools, Department of Computer Science), with a PhD in Computer Science from the University of Toulon (2017). His academic profile spans disciplines including Machine Learning, Signal and Image Processing, and Biomedical Engineering, with a focus on applications in Digital Health and Human-Robot Interaction. Education : PhD in Computer Science (University of Toulon, 2013-2017); Master 2 in Computer Science (University of Fes, Morocco, 2009-2011); Bachelor’s in Mathematical and Computer Sciences (University of Fes, 2006-2009). His research interests include: Machine Learning and Deep Learning Signal and Image Processing 3D Shape Analysis Computer Vision Digital Health Biomimetic Feature Design BOHI’s publications reflect expertise in facial emotion recognition for elderly care, cortical folding modeling, and soft tissue organ deformation analysis using MRI. He supervises diverse research internships, mentoring students from institutions like Sorbonne Paris Nord, Université de Technologie King Mongkut, and INP Grenoble. Current projects involve developing intelligent solutions for emotional interaction with elderly individuals suffering from neurodegenerative disorders, in collaboration with VyV3 Bourgogne. He also contributes to the design of multimodal datasets and wearable health monitoring systems. BOHI’s technical work includes contributions to maritime surveillance systems (PARE project) and semantic information platforms, demonstrating a capacity to bridge theoretical research with practical applications across domains.
Francesco Cappello is a Full Professor in the Department of Biomedicine, Neuroscience and Advanced Diagnostics at the University of Palermo, Italy, where he also serves as Vice-Rector for Student Life. His office is located in the Human Anatomy and Histology Building, where he maintains regular office hours for students. Professor Cappello teaches across multiple departments including Medicine and Surgery, Biomedical Engineering, and Sciences of Motor and Sport Activities. Professor Cappello's research program centers on molecular chaperones, particularly Heat Shock Protein 60 (Hsp60), and their roles in various physiological and pathological conditions. He has developed the concept of the "muco-microbiotic layer" as a novel morphofunctional structure and investigates how probiotics and nanovesicles might target this layer in disease conditions. His work spans multiple systems including the digestive system, skeletal muscle, neuroendocrine system, and respiratory system, exploring Hsp60's potential as both a biomarker and therapeutic target. Analysis of Professor Cappello's recent publications reveals a comprehensive exploration of Hsp60 across multiple disease contexts. His 2025 publications demonstrate particular interest in the relationship between Hsp60 and skeletal muscle diseases, digestive system pathologies, and the neuroendocrine system. He is also pioneering connections between molecular chaperones and artificial intelligence applications in biomedical research, while investigating the therapeutic potential of probiotics like Lactobacillus fermentum LF31 in modulating inflammatory pathways and muscle atrophy. Professor Cappello has maintained consistent teaching responsibilities across multiple academic years, instructing Human Anatomy II in Medicine and Surgery programs, Elements of Anatomy in Biomedical Engineering specializations, and Human Morphology courses in Motor and Sport Sciences. His teaching spans both foundational anatomy and specialized applications across various health science disciplines, reflecting his broad expertise in anatomical sciences.
Gary M. Hollenberg, M.D. serves as a Professor of Clinical Imaging Sciences at the University of Rochester School of Medicine and Dentistry within the Department of Imaging Sciences. He is a key member of both the University of Rochester Medical Faculty Group (URMFG) and Accountable Health Partners (AHP), specializing in Body and Musculoskeletal MRI and Cross-Sectional Imaging with over 16 years of clinical experience in diagnostic radiology. His educational foundation includes a Medical Doctorate from the University of Rochester School of Medicine and Dentistry (1990), followed by an Internship in Internal Medicine at Highland Hospital of Rochester (1990-1991), a Radiology Residency at Rochester General Hospital (1991-1995), and a Cross-Sectional Imaging Fellowship at the University of Rochester Medical Center (1995-1996). He maintains active certification from the American Board of Radiology in Diagnostic Radiology. Dr. Hollenberg's research program bridges musculoskeletal radiology and prostate oncology imaging. Early career work established him in spinal MRI classification systems and tendon ultrasound diagnostics, while recent publications demonstrate a strategic pivot toward advanced prostate cancer imaging. His investigations focus on correlating MRI findings with clinical outcomes, particularly in developing quantitative biomarkers for prostate cancer detection and refining MR/US fusion biopsy techniques to guide treatment decisions in urology. Analysis of his 15 most recent publications (2000-2025) reveals a distinct trajectory: foundational musculoskeletal studies (2000-2003) centered on spine/wrist imaging and tendon pathologies have transitioned to a dominant prostate cancer focus (2016-2025). This evolution reflects growing clinical demand for precision imaging in urologic oncology, with his work increasingly appearing in high-impact urology journals while maintaining methodological roots in advanced MRI techniques. His scientific recognition includes: PROSE Award for publishing excellence (2016) Election as Fellow of the American College of Radiology (2014) NIH Summer Research Fellowship during medical training (1987-1988) Dr. Hollenberg contributes to academic medicine through editorial service on The Journal of The University of Rochester Medical Center (1989-1990) and as a Medical Student Interviewer for admissions (1988-1990). His research funding includes the Department of Radiology Fischer fund as co-investigator for Doppler sonography of the patellar tendon (2000-2001), demonstrating sustained grant acquisition capability across both musculoskeletal and prostate imaging domains. Professionally, he maintains active leadership through the Rochester Roentgen Ray Society (serving as past president) and membership in major national societies including the American College of Radiology, Radiological Society of North America, American Roentgen Ray Society, New York State Radiological Society, and Society of Skeletal Radiology. These affiliations facilitate multidisciplinary collaborations that drive innovation in imaging science and clinical application.
Daifeng Wang is an Associate Professor at the University of Wisconsin-Madison, holding an affiliate appointment in the Department of Computer Sciences within the College of Letters and Science. His research is conducted through the Waisman Center, where he directs the Daifeng Wang Laboratory focused on developing computational approaches to understand brain function and disease. Dr. Wang's research interests center on developing machine learning approaches and bioinformatics tools to analyze multimodal data for improving genotype-phenotype prediction and understanding functional genomics and gene regulation in human brains and brain diseases. His current research topics include bio-inspired machine learning, single-cell functional genomics, and multimodal integration and imputation. His work bridges computational biology with neuroscience to address complex questions in brain development and disease. Analysis of Dr. Wang's recent publications reveals a strong focus on developing computational frameworks for integrating diverse biological data types. His research demonstrates expertise in applying machine learning to neurogenomics, with particular emphasis on Alzheimer's disease, intellectual and developmental disabilities, and brain organoid models. His work consistently combines theoretical innovation in machine learning with practical applications to pressing biological questions. National Institutes of Health National Science Foundation Simons Foundation Autism Research Initiative University of Wisconsin-Madison Dr. Wang's laboratory develops machine learning and artificial intelligence approaches and bioinformatics tools to bridge computation and biology for mechanistic insights into complex brains and brain diseases. Their applications focus on functional genomics, gene regulation, cell dynamics, and neural circuits, with particular attention to translating computational findings into biological understanding.
Per Steinar Halvorsen is a Professor at the University of Oslo, affiliated with the Division of Technology and Innovation and Oslo University Hospital (Rikshospitalet). His primary focus is on cardiovascular engineering and medical technology innovation, with an emphasis on developing advanced monitoring systems for critical care and cardiac applications. His work integrates biomedical engineering principles with clinical practice to address challenges in ECMO, left ventricular assist devices (LVADs), and real-time cardiac monitoring. Research Interests: Halvorsen’s research spans accelerometer-based cardiovascular monitoring, thrombosis detection in extracorporeal systems, and the application of machine learning in medical diagnostics. His studies often utilize porcine models to validate novel sensor technologies and device functionalities. He has contributed to advancements in non-invasive waveform analysis for emergency triage and therapeutic hypothermia protocols. Key Research Trends: His articles emphasize innovations in medical device design, particularly accelerometers for continuous cardiac monitoring. Recent work includes deep learning applications for valve event detection and vibration analysis for LVAD thrombosis. Collaborations with engineering teams (e.g., MEMS sensor development) highlight his interdisciplinary approach. Labs/Teams: He is part of the Clinical and Experimental Cardiovascular Monitoring research group, focusing on translational research between engineering and clinical cardiology.
