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Yuankai (Kenny) Tao is an Associate Professor of Biomedical Engineering at Vanderbilt University's School of Engineering and an SPIE Faculty Fellow. He directs the Graduate Studies program in Biomedical Engineering and leads research in optical imaging systems for clinical diagnostics and therapeutic monitoring in ophthalmology, gastroenterology, and oncology. His lab develops technologies like intraoperative OCT and SECTR, focusing on noninvasive subcellular visualization and biomarker monitoring. Collaborations span engineering, basic sciences, and medicine to translate innovations into clinical tools. Education: Ph.D., Biomedical Engineering, Duke University M.S., Biomedical Engineering, Duke University B.S.E., Biomedical Engineering and Electrical Engineering, Duke University Research Interests: Biomedical optics, optical coherence tomography (OCT), image-guided surgery, therapeutic monitoring, big data analytics, and high-throughput imaging for drug discovery. His work bridges engineering and medicine, emphasizing real-time feedback systems and interdisciplinary innovation. Grants & Labs: Director of the Vanderbilt Institute for Surgery and Engineering (VISE)-affiliated lab, focusing on surgical imaging and translational research. Projects include automated instrument tracking, SECTR systems, and AI-driven imaging analysis. Collaborations involve clinicians and researchers across disciplines.

• Biomedical Engineering
• Medical Imaging Technologies
• Optical Imaging Systems
• +9 more

Preet Singh is a Professor and Associate Chair for Graduate Studies in the School of Materials Science and Engineering at Georgia Tech, with affiliations to the College of Engineering. His research focuses on corrosion science, electrochemistry, and environmental degradation of materials, particularly metals and alloys. Prior to joining Georgia Tech in 2003, he was a faculty member at the Institute of Paper Science and Technology (IPST), where he investigated corrosion issues in the pulp and paper industry. Professor Singh's work explores fundamental mechanisms of material degradation in industrial environments, aiming to develop mitigation strategies against environment-induced failures. Key research areas include corrosion fatigue, hydrogen embrittlement, stress corrosion cracking, and oxidation behavior. His group employs experimental approaches to study material reliability under varying chemical and mechanical conditions. Recent publications demonstrate interdisciplinary collaboration across oncology, agriculture, and energy systems, reflecting broad applications of materials science principles. Research trends show increased focus on biomedical materials and sustainable technologies alongside core corrosion studies. Professor Singh advises graduate students including Abdullah Alzubail, Yousif Al Rabie, Sai Shreeya, Yara, and Sean Li. He directs the Corrosion and Materials Reliability Laboratory (CMCRL), which partners with industry to solve practical engineering challenges related to material performance.

• Corrosion Science
• Electrochemistry
• Metals and Alloys
• +5 more

Prof. Dr. Raphael Sznitman serves as Director of the ARTORG Center for Biomedical Engineering Research and Head of the Artificial Intelligence in Medical Imaging group at the University of Bern, Switzerland, holding a Full Professor position in AI for Medical Imaging since 2015. Education: PhD in Computer Science, Johns Hopkins University (2011) MSc in Computer Science, Johns Hopkins University (2009) BSc in Cognitive Systems, University of British Columbia (2007) Research Interests: Sznitman's work centers on computational vision , probabilistic methods , and statistical learning applied to medical imaging challenges. His group develops AI algorithms for ophthalmic diagnostics, surgical robotics, and medical image analysis, with emphasis on OCT, surgical phase recognition, and domain adaptation techniques. Key application areas include retinal disease detection and cataract surgery automation. Publication Trends: His 2021-2025 publications reveal concentrated efforts in deep learning for medical imaging , particularly in ophthalmology (OCT analysis) and surgical video understanding. Emerging themes include LLM applications for clinical monitoring, unsupervised out-of-distribution detection for surgical safety, and physics-informed AI for multimodal medical data fusion. Research Leadership: As ARTORG Center Director, Sznitman oversees interdisciplinary research bridging computer science and clinical medicine. His group collaborates extensively with Bern University Hospital clinicians on translational projects, securing funding for AI-driven diagnostic tools and surgical assistance systems. Current initiatives focus on real-time intraoperative guidance and spaceflight ophthalmology applications. Laboratory: The Artificial Intelligence in Medical Imaging group operates within ARTORG's dedicated facilities, maintaining partnerships with surgical robotics labs and ophthalmology departments for clinical validation of AI systems. Their work integrates multimodal data streams including OCT, VR perimetry, and surgical video feeds.

• Computer Vision
• Probabilistic Methods
• Statistical Learning
• +2 more

Clinical Associate Professor Keith Ong is affiliated with the University of Sydney’s Northern Clinical School, specifically within the Department of Clinical Ophthalmology & Eye Health. His clinical specialty is Ophthalmology, with a focus on corneal endothelial health, glaucoma surgery outcomes, and cataract surgical techniques. His research addresses critical areas such as postoperative ocular toxicity, intraocular lens calculations, and infection control in eye surgeries. Dr. Ong’s publications (2011–2023) consistently explore topics like corneal endothelial changes post-trabeculectomy, refractive error management post-cataract surgery, and antibiotic prophylaxis strategies. Recent work emphasizes optimizing surgical techniques to reduce complications, such as BAK-induced corneal toxicity and IOL power calculation accuracy in LASIK patients. His work demonstrates a focus on improving surgical safety and precision, with studies evaluating alternative antibiotic delivery methods and laser therapy impacts. No awards or grants are explicitly noted in the provided text, but his contributions to clinical practice and surgical protocols are evident through his publication record.

• Ophthalmology
• Corneal Endothelial Health
• Cataract Surgery Outcomes
• +3 more

Dr. Ian Wilson is a researcher at Newcastle University with a focus on medical genetics, nephrology, and genomic analysis. His work spans genetic determinants of kidney diseases, mitochondrial disorders, and biomarker development. Notable contributions include studies on uromodulin genetics in African populations, copy-number variations in rare diseases, and kidney ciliopathies. He has collaborated extensively on projects involving genome sequencing, mitochondrial replacement therapy, and muscular dystrophy biomarkers. Wilson's research integrates computational tools like machine learning for predictive modeling in urolithiasis and employs advanced imaging techniques for disease progression monitoring. Key areas: Genetic epidemiology, renal genomics, mitochondrial DNA analysis Focus on translational applications: Biomarker development for kidney stones and muscular dystrophies Interdisciplinary collaborations in ophthalmology and orthopedics His publications reflect a commitment to advancing diagnostic accuracy and understanding complex genetic disorders through multi-omics approaches.

• Medical Genetics
• Nephrology
• Genomics
• +3 more

Jeffrey Glassberg, MD, is a Professor in both the Department of Emergency Medicine and the Division of Hematology and Medical Oncology at the Icahn School of Medicine at Mount Sinai. His clinical and research focus centers on hematology and emergency medicine, with particular attention to sickle cell disease and its complications. Education MD, Washington University Internship and Residency in Emergency Medicine, Bellevue Hospital Center Research Focus Dr. Glassberg's work explores the intersection of emergency care and hematological disorders, particularly sickle cell disease. His research includes epidemiological studies of ICU utilization and advanced imaging techniques to assess retinal blood flow abnormalities in sickle cell patients. Publications Recent work published in Chest and Ophthalmic Surgery Lasers and Imaging Retina focuses on clinical outcomes and vascular complications in sickle cell disease. Contact Information Phone: 212-824-8074 Address: One Gustave L. Levy Place, Box 1620, New York, NY 10029

• Emergency Medicine
• Hematology
• Medical Oncology
• +1 more

Dr. James Kempton is an Associate Professor of Ophthalmology & Visual Science at Yale School of Medicine , where he has served since 2009. He also directs Eye Care Services at the West Haven Veterans Administration and co-leads Yale's Vitreoretinal Fellowship Program and Ophthalmology Residency Program. Double Board-Certified in Internal Medicine & Ophthalmology Specializes in Retinal Surgery and Trauma-Associated Vitreoretinal Diseases Research Focus: Clinical management of Diabetic Retinopathy , Macular Degeneration , and Retinal Detachment , combined with innovative Systems Approaches in Medical Education . Education MD, Ohio State University (1997) Internship: Combined Internal Medicine/Pediatrics at Medical College of Virginia Residency: Yale Internal Medicine Primary Care Chief Residency: Hospital of Saint Raphael Ophthalmology Residency & Fellowship: Yale University Honors Recipient of the prestigious Marvin L. Sears Award for Clinical Excellence Clinical Expertise includes laser treatments and surgical interventions for retinal disorders, with a focus on Diabetic Retinopathy , Macular Degeneration , and Retinal Trauma . He serves as Associate Program Director for both Yale's Ophthalmology Residency and Vitreoretinal Fellowship programs.

• Diabetic Retinopathy
• Macular Degeneration
• Retinal Detachment
• +3 more

Dr. Guangyao Li is a Research Fellow in the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge, affiliated with the Quantum Fluids research group. His work focuses on theoretical and computational studies of quantum fluids, particularly exciton-polaritons in semiconductor microcavities and their interactions with electrons and photons. His research bridges condensed matter physics, quantum optics, and nanotechnology. Dr. Li's interdisciplinary interests also extend to pharmacology and clinical medicine, evidenced by collaborative studies on drug efficacy, drug-related problems in hospital settings, and guidelines for off-label drug use in ophthalmology. These studies address topics such as glucocorticoid therapy complications, proton pump inhibitor utilization, and anti-vascular endothelial growth factor treatments for ocular diseases. His quantum physics publications explore polariton scattering, Bose-Einstein condensates, and chiral edge states in quantum fluids. Recent medical studies analyze drug safety, self-monitoring in diabetes, and inappropriate medication use in elderly cardiac patients. These works highlight his dual contribution to fundamental physics research and applied clinical pharmacology. No academic awards or grants are explicitly stated in available records. He advises no known students but collaborates across disciplines in Cambridge and Chinese medical institutions. His research is conducted within the Quantum Fluids group at DAMTP, leveraging advanced theoretical models and computational simulations.

• Quantum Physics
• Condensed Matter Physics
• Theoretical Physics
• +4 more

Albert M. Lai, PhD, is a Professor of Medicine and Computer Science & Engineering at Washington University in St. Louis, serving as Chief Research Information Officer (CRIO) for the School of Medicine and Deputy Director of the Institute for Informatics, Data Science and Biostatistics (I²DB). He leads WashU Medicine's data warehousing and informatics services, driving innovation in clinical research infrastructure. His expertise spans biomedical informatics, natural language processing (NLP), and telemedicine. Dr. Lai is also Deputy Faculty Lead for WashU’s Digital Transformation initiative, focusing on secure AI integration with sensitive healthcare data. He holds affiliations with the Institute for Public Health, Siteman Cancer Center, and the Center for Applied Health Informatics (CAHI). Research Interests: Dr. Lai develops informatics infrastructure to support clinical trial prescreening, leveraging NLP and machine learning for phenotype extraction from EHR data. He also explores telemedicine, mobile health applications, and EHR-driven cardiovascular health interventions for cancer survivors. His recent work addresses AI ethics in healthcare, including responsible data sharing and bias mitigation in generative AI models. Key Contributions: Over 77 peer-reviewed publications across clinical informatics, AI in healthcare, and pandemic response strategies. His projects include EHR-based cardiovascular health tools, SARS-CoV-2 surveillance in schools, and machine learning models for predicting transplant outcomes. Active mentorship of PhD/MSTP students in translational informatics and data science. Labs/Teams: Leads the Informatics Services Core and collaborates with the CRITICAL consortium for intensive care analytics. Engages in multi-institutional initiatives like the Greater Plains Collaborative for cancer data integration.

• Biomedical Informatics
• Clinical Research Informatics
• Consumer Health Informatics
• +5 more

Guojun Chen is an Assistant Professor at the Department of Biomedical Engineering and a member of the Rosalind & Morris Goodman Cancer Institute (GCI) at McGill University . His research focuses on engineering intelligent biomaterials for precision medicine , with emphasis on non-viral genome editing , cold atmospheric plasma (CAP) therapy , and biomaterials-mediated immunotherapy . The lab operates in a multidisciplinary environment , integrating principles from materials science , chemistry , biology , and health sciences . Education : Ph.D. from University of Wisconsin-Madison (2017), Postdoc at UCLA (2020) Research Themes : Genome Editing Delivery : Designing non-viral vectors for efficient CRISPR/Cas9 delivery in vivo. CAP-mediated Immunotherapy : Developing portable cold plasma devices to synergize with immune checkpoint blockade and study CAP’s immunological mechanisms. Biomaterials-based Immunotherapy : Reprogramming tumor microenvironments using bioresponsive materials to enhance immune responses. Publication Trends : Recent work spans responsive nanomaterials , genomic editing systems , and plasma oncology , with a focus on cancer immunotherapy , diabetes diagnostics , and bioinspired medical devices . Scientific Awards : Canada Research Chair (2024, 2025) McGill's President's Prize for Emerging Researchers (2025) FRQS Chercheurs-boursiers (2022) Chinese Association for Biomaterials Young Investigator Award (2022) NSERC Discovery Grant (2021) Advising & Grants : Supervises 14 current graduate and undergraduate students. Secured $5M+ in funding from CIHR , NSERC , CCS , and CFI , including multi-institutional collaborations with Dr. Morag Park , Dr. Réjean Lapointe , and Dr. Ian Watson .

• Biomaterials
• Nanomedicine
• Tissue Engineering
• +5 more

Professor Emanuele (Manuel) Trucco is the NRP Chair of Computational Vision in the Department of Computing, School of Science and Engineering, at the University of Dundee. He holds additional roles as an Honorary Clinical Researcher at NHS Tayside and formerly served as an Adjunct Professor at the Chinese Academy of Sciences from 2018 to 2021. He earned his MSc and PhD in Electronic Engineering from the University of Genoa, Italy, in 1984 and 1990, respectively. His research focuses on medical image and data analysis, particularly in retinal imaging, using machine and deep learning techniques. He is co-director of VAMPIRE, a major international initiative in retinal image analysis, which supports biomarker studies in cardiovascular disease, diabetes, dementia, and neurodegenerative disorders. His recent work includes AI-driven tools for predicting dementia from brain scans and cardiovascular risk from retinal images. The latest publications reflect strong trends in applying deep learning to retinal and brain imaging for early disease detection, with themes centered on AI in healthcare, precision medicine, and non-invasive diagnostics. FRSA (Fellow of the Royal Society of Arts) FIAPR (Fellow of the International Association for Pattern Recognition) Professor Trucco has led and co-led significant research projects funded by EPSRC, NIHR, and EU programs. He has supervised PhD students through industry-sponsored studentships (e.g., OPTOS, NIDEK, Toshiba) and collaborated with institutions such as the Universities of Edinburgh and Liverpool. His research is supported by extensive industrial partnerships including Canon Medical, Epipole plc, and NIDEK. He is a key member of the UK Biobank Eye and Vision Consortium and co-director of the VAMPIRE initiative, a collaborative effort between the Universities of Dundee and Edinburgh focused on retinal image analysis. His work also involves participation in major research networks such as the Academic Health Science Partnership in Tayside.

• Computer Vision
• Medical Image Analysis
• Retinal Image Analysis
• +7 more

David R. Williams is the William G. Allyn Professor of Medical Optics at the University of Rochester's Institute of Optics. He holds joint appointments in Ophthalmology, Biomedical Engineering, and Brain & Cognitive Sciences. His research focuses on advancing retinal imaging techniques, particularly using adaptive optics, to study vision mechanisms and disorders. Williams directs the Center for Visual Science, an interdisciplinary initiative with over 40 faculty members. Education: B.S. from Denison University (1975), Ph.D. from University of California, San Diego (1979), postdoctoral fellowship at Bell Labs (1980). Research Interests: Adaptive optics for high-resolution retinal imaging Retinal physiology and photoreceptor function Optogenetic therapies for vision restoration Pathological mechanisms in macular diseases Publications Highlight: His work spans foundational studies in retinal ganglion cells, optogenetic therapies, and innovations in adaptive optics systems. Recent trends focus on in vivo imaging of photoreceptors and neural activity restoration. Scientific Awards: Champalimaud Vision Award (2012) National Academy of Sciences Membership (2014) David F. Weeks Award (2020) Advising & Grants: As director of the Center for Visual Science, he oversees interdisciplinary grants and mentorship in vision science. His lab collaborates with leading institutions globally to advance translational research in ophthalmology and neurobiology. Labs/Teams: Core leader of the Center for Visual Science, with teams specializing in adaptive optics, retinal imaging, and optogenetic therapies.

• Medical Optics
• Vision Science
• Adaptive Optics Technology
• +4 more

Craig Jones is an Assistant Professor of Computer Science at Johns Hopkins University's Whiting School of Engineering. He is affiliated with the Malone Center for Engineering in Healthcare and contributes to the Precision Medicine Analytics Platform's Imaging and Data Science Subcommittees. BSc in Computer Science and Mathematics from Simon Fraser University MSc in Medical Biophysics from the University of Western Ontario PhD in Physics from the University of British Columbia His research focuses on applying artificial intelligence and neural networks to medical image processing, particularly for MRI, CT, optical coherence tomography (OCT), and ultrasound datasets. Key areas include 2D/3D image processing, anomaly detection, segmentation, and uncertainty quantification, with clinical applications in neurosurgery, ophthalmology, and oncology. Projects span robotic imaging, neuroendoscopic guidance, and cancer boundary detection. Recent publications highlight advancements in vision-language models for 3D medical imaging, automated segmentation of venous malformations, and AI-guided neurosurgical tools. Articles emphasize multimodal data fusion, self-supervised learning, and federated learning for rare cancer analytics. He received a $310,000 Department of Defense grant in 2022 to develop AI-guided treatments for venous malformations. His work bridges clinical imaging domains and computer vision as a member of the Radiology AI Lab (RAIL), a collaborative effort across Johns Hopkins Hospital, the Whiting School of Engineering, and the Applied Physics Laboratory.

• Medical Image Processing
• Artificial Intelligence
• Neural Networks
• +2 more

William Newman is a Professor in the Department of Earth, Planetary, and Space Sciences at the University of California, Los Angeles (UCLA), currently on sabbatical at the Institute for Advanced Study in Princeton. His primary academic home resides within UCLA's geoscience and planetary science division. His educational credentials include: B.Sc. (Hon.) in Physics from the University of Alberta, Canada (1971) M.Sc. in Physics from the University of Alberta, Canada (1972) M.S. in Astronomy and Space Science from Cornell University (1975) Ph.D. in Astronomy and Space Science from Cornell University (1979) Professor Newman applies theoretical physics and applied mathematics to solve critical real-world problems across multiple disciplines. His research spans statistical techniques for climate change assessment, earthquake hazard modeling, solar system evolution (including collision risks from trans-Jovian bodies), astrophysical jet dynamics, and pattern emergence in complex systems. This interdisciplinary work bridges geophysics, planetary science, and astrophysics through rigorous mathematical frameworks. His publication record (2024-2016) reveals three dominant research thrusts: (1) Semiconductor electron emission physics (GaAs nanotips, photoemission sources), (2) Solar system dynamics and celestial mechanics (N-body simulations, impact hazards), and (3) Complex systems analysis (earthquake patterns, statistical record-breaking events). These intersect physics, earth sciences, and computational mathematics through shared methodologies in statistical modeling and nonlinear dynamics. At UCLA, Newman developed innovative courses including a natural disasters undergraduate GE course (satisfying diversity requirements) and graduate-level planetary atmospheres and continuum mechanics curricula. His academic contributions include over 100 refereed papers and graduate textbooks published by Princeton and Cambridge University Presses, focusing on mathematical methods for geophysics and space physics.

• Geophysics
• Planetary Science
• Astrophysics
• +5 more

Nabil Simaan is a Professor of Mechanical Engineering at Vanderbilt University with secondary appointments in Computer Science and Otolaryngology . He leads the Advanced Robotics and Mechanism Applications (ARMA) laboratory, focusing on surgical robotics, continuum robots, and intelligent human-robot interaction. Education : Ph.D., M.Sci., and B.S. in Mechanical Engineering from the Technion—Israel Institute of Technology . Postdoctoral Research at Johns Hopkins University NSF ERC-CISST (2003-2004). Research Interests : Medical robotics for minimally invasive procedures Kinematic modeling and optimization of parallel/continuum robots Telemanipulation and semi-autonomous control Flexible mechanisms and actuation redundancy Article Trends : His recent work emphasizes subretinal surgical robots, continuum manipulators for transurethral operations, and multi-scale dexterity through mathematical synthesis using screw theory and algebraic geometry. Scientific Awards : NSF Career Award (2009) for intelligent surgical robots IEEE Senior Member (2013) for contributions to robotics Advising & Grants : Advises PhD/MSc students in robotics and mechanism design. NIH-funded work on OCT-guided retinal surgery robots. NSF grants for continuum robot kinematics and redundancy control. Labs & Collaborations : Leads the ARMA Lab , bridging engineering and clinical medicine. Collaborates with Vanderbilt Institute for Surgery and Engineering (VISE) and industry partners like AURIS Surgical Robotics. Translational focus through Titan Medical Inc. partnerships.

• Medical Robotics
• Surgical Robotics
• Continuum Robotics
• +7 more