School of Medicine
Showing 601-620 of 684 Results
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Henk van Voorst
Postdoctoral Scholar, Radiology
BioDr. van Voorst is a postdoctoral scholar in Radiology studying the interfaces of artificial intelligence and neuroradiological imaging in stroke. Originally educated as an MD, Dr. van Voorst gained additional degrees in Finance and Data Science. As a PhD student, Dr. van Voorst focused on cost-effectiveness modeling and developed machine learning and deep learning algorithms with applications in acute ischemic stroke imaging. In his current research, Dr. van Voorst develops artificial intelligence algorithms to automatically extract information from arteries and veins in radiological stroke imaging.
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Minal Vasanawala
Clinical Associate Professor (Affiliated), Rad/Nuclear Medicine
Staff, Radiology - Diagnostic RadiologyCurrent Research and Scholarly InterestsPET/MRI, PETCT, and SPECT/CT applications in neuroimaging
Cardiac SPECT/CT and PET/CTA -
Shreyas Vasanawala, MD/PhD
William R. Brody Professor of Pediatric Radiology and Child Health
Current Research and Scholarly InterestsOur group is focused on developing new fast and quantitative MRI techniques.
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Manuela Vasquez
Administrative Associate, Radiology
BioAs an Administrative Associate, I am dedicated to keeping scientists organized, prioritized and less stressed. I practice a streamlined and intuitive approach to assistance.
I am open-arms to opportunities that will broaden my horizon. A team player, willing to lead or follow, eager to learn and is self-motivated. Committed to excellence in service.
My philosophy centers around what role I can play in helping others find solutions. Enthusiastic and personable, my passion is to contribute, support, and make a difference. -
Jaqueline Velazquez
Senior Administrative Associate, Radiology
Current Role at StanfordSupporting RSL Faculty:
Dr. Ennis, PhD
Dr. Setsompop, PhD
Dr. McNab, PhD -
Alexander Michael Vezeridis, MD, PhD
Assistant Professor of Radiology (Interventional Radiology)
BioAlexander Vezeridis MD, PhD is an Assistant Professor of Radiology at Stanford University School of Medicine, and a physician-scientist specializing in Interventional Radiology. His clinical expertise includes interventional oncology, biliary disease and endoscopy, venous disease, portal hypertension, urologic interventions, women’s and men’s health interventions, and general vascular/interventional radiology.
Dr. Vezeridis is an active researcher with expertise in translational techniques in engineering to make image-guided interventions safer and more effective for patients.
Dr. Vezeridis obtained his undergraduate, MD, and PhD degrees from Boston University. He completed a two year post-doctoral training at UC San Diego in ultrasound molecular imaging under the auspices of the Cancer Researchers in Nanotechnology (CRIN) R25T, followed by residency and fellowship at UC San Diego.
Dr. Vezeridis is highly committed to training the next generation, including students, residents, fellows, and engineering graduate students through co-directing Bio301B.
Dr. Vezeridis has a strong interest in medical device development and commercialization, and completed the Stanford Biodesign Faculty Fellowship. -
Davis Vigneault
Clinical Instructor, Radiology
BioDr. Vigneault is a fellow in cardiovascular imaging at Stanford, where he also completed his residency (including a year as chief resident) in diagnostic radiology. Previously, he received his medical degree from Tufts University School of Medicine and his DPhil in Biomedical Engineering from the University of Oxford through the NIH-Oxford Scholars and Medical Scientist Training Programs. For his graduate degree, Dr. Vigneault worked on novel algorithms for measuring regional cardiac function from cardiac CT and MR, publishing in Radiology, Medical Image Analysis, and the Journal of Cardiovascular Magnetic Resonance, among others. In addition to cardiovascular imaging and deep learning, Dr. Vigneault has a strong interest in open science, having been a frequent contributor of software to large open-source libraries such as ITK and related packages.
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Shannon Walters
Executive Technical Director, Radiology - Diagnostic Radiology
Current Role at StanfordI consider myself an innovation enabler and workflow optimization enthusiast. At Stanford 3D and Quantitative Imaging Lab, I work closely with healthcare providers, researchers, and educators to enable effective health visualization. Recent innovations are of particular interest to me; such as 3D Printing, immersive volumetric visualization, clinical implementation of validated AI algorithms, and the general concept of reporting concise changes over time.
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Adam Wang
Assistant Professor of Radiology (Radiological Sciences Laboratory) and, by courtesy, of Electrical Engineering
BioMy research group develops technologies for advanced x-ray and CT imaging, including artificial intelligence for CT acquisition, reconstruction, and image processing; spectral imaging, including photon counting CT (PCCT) and dual-layer flat-panel detectors; novel system and detector designs; and their applications in diagnostic imaging and image-guided procedures. I am also the Director of the Photon Counting CT Lab, Zeego Lab, and Tabletop X-Ray Lab.
I completed my PhD in Electrical Engineering at Stanford, developing strategies for maximizing the information content of dual energy CT and photon counting detectors. I then pursued a postdoctoral fellowship at Johns Hopkins in the I-STAR Lab, developing reconstruction and registration methods for x-ray based image-guided surgery. I was then a Senior Scientist at Varian Medical Systems, developing x-ray/CT methods for image-guided radiation therapy, before returning to Stanford in 2018, where I now lead a comprehensive research program in advanced x-ray and CT imaging systems and methods, with funding from NIH, DOD, DOE, and industry partners. -
Chong Wang
Postdoctoral Scholar, Radiology
BioI am currently a Postdoctoral Scholar in the Department of Radiology at Stanford University School of Medicine, affiliated with the Center for Artificial Intelligence in Medicine and Imaging (AIMI). My research mainly focuses on AI and foundation models in healthcare, with an emphasis on developing trustworthy, robust, and efficient AI solutions for medical imaging. I earned my Ph.D degree, honored with the Doctoral Research Medal, in Computer Science from the Australian Institute for Machine Learning (AIML), The University of Adelaide.
