Radiology
Showing 121-140 of 667 Results
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Jennifer Dionne
Professor of Materials Science and Engineering, Senior Fellow at the Precourt Institute for Energy and Professor, by courtesy, of Radiology (Molecular Imaging Program at Stanford)
BioJennifer (Jen) Dionne is a Professor of Materials Science and Engineering and, by courtesy, of Radiology at Stanford. She is also a Chan Zuckerberg Biohub Investigator, deputy director of Q-NEXT (a DOE National Quantum Initiative), and co-founder of Pumpkinseed, a company developing quantum sensors to understand and optimize the immune system. From 2020-2023, Jen served as Stanford’s Inaugural Vice Provost of Shared Facilities, raising capital to modernize instrumentation, fund experiential education, foster staff development, and support new and existing users of the shared facilities. Jen received her B.S. degrees in Physics and Systems Science and Mathematics from Washington University in St. Louis, her Ph. D. in Applied Physics at the California Institute of Technology in 2009, and her postdoctoral training in Chemistry at Berkeley. As a pioneer of nanophotonics, she is passionate about developing methods to observe and control chemical and biological processes as they unfold with nanometer scale resolution, emphasizing critical challenges in global health and sustainability. Her research has developed culture-free methods to detect pathogens and their antibiotic susceptibility; amplification-free methods to detect and sequence nucleic acids and proteins; and new methods to image light-driven chemical reactions with atomic-scale resolution. Jen’s work has been featured in NPR, the Economist, Science, and Nature, and recognized with the NSF Alan T. Waterman Award, a NIH Director’s New Innovator Award, a Moore Inventor Fellowship, and the Presidential Early Career Award for Scientists and Engineers. She was also featured on Oprah’s list of “50 Things that will make you say ‘Wow’!”. She also perceives outreach as a critical component of her role and frequently collaborates with visual and performing artists to convey the beauty of science to the broader public.
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Bao Do
Clinical Professor, Radiology
BioBao Do is an expert in radiology informatics, computer vision, and quantitative musculoskeletal imaging. He has developed and validated deep-learning models for diagnostic interpretation, hardware recognition, and automated reporting across orthopedic and radiographic domains. His recent studies demonstrated high-performance CNNs for detecting perilunate and lunate dislocations on wrist radiographs (AUC = 0.986) 【Pridgen et al., Plast Reconstr Surg 2023; 10.1097/PRS.0000000000010928】 and improving clinician accuracy through machine-learning-assisted diagnosis in a multicenter reader study 【Luan et al., Hand (N Y)2025; 10.1177/15589447241308603】. He co-developed AI systems for automated classification of hip hardware achieving radiologist-level accuracy (AUC ≥ 0.99) 【Ma et al., J Imaging Informat Med 2024; 10.1007/s10278-024-01263-y】, scoliosis curvature measurement from 2,150 spine radiographs 【Ha et al., J Digit Imaging 2022; 10.1007/s10278-022-00595-x】, and fully automated leg-length analysis and reporting 【Larson et al., J Digit Imaging2022; 10.1007/s10278-022-00671-2】. Earlier work included Bayesian models for bone tumor diagnosis 【Do et al., J Digit Imaging 2017; 30:709-13】, semantic content-based image retrieval using relevance feedback 【Banerjee et al., J Biomed Inform 2018; 84:123-35】, and NLP-based uncertainty detection in radiology reports 【Callen et al., J Digit Imaging 2020; 33:1209-19】, demonstrating a career-long commitment to explainable, data-driven imaging analytics.
Interests: Musculoskeletal imaging AI, AI for workflow optimization, human-AI interaction in radiology, scalable education
www.stanford.edu/~baodo -
Robert Dodd, MD, PhD
Associate Professor of Neurosurgery, of Radiology and, by courtesy, of Otolaryngology - Head & Neck Surgery (OHNS)
Current Research and Scholarly InterestsDr. Dodd is involved in clinical trials using endovascular coils that have a fiber coating that help heal aneurysms of the neck and can prevent an aneurysm from reforming. He uses minimally invasive endoscopic techniques to treat brain tumors.
Dodd's research interests are in cerebral blood vessel reactivity and stroke. -
Gozde Durmus
Assistant Professor (Research) of Radiology (Molecular Imaging Program at Stanford)
Current Research and Scholarly InterestsDr. Durmus' research focuses on applying micro/nano-technologies to investigate cellular heterogeneity for single-cell analysis and personalized medicine. At Stanford, she is developing platform technologies for sorting and monitoring cells at the single-cell resolution. This magnetic levitation-based technology is used for wide range of applications in medicine, such as, label-free detection of circulating tumor cells (CTCs) from blood; high-throughput drug screening; and rapid detection and monitoring of antibiotic resistance in real-time. During her PhD, she has engineered nanoparticles and nanostructured surfaces to decrease antibiotic-resistant infections.
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Daniel Bruce Ennis
Professor of Radiology (Veterans Affairs) and, by courtesy, of Bioengineering
Current Research and Scholarly InterestsThe Cardiac MRI Group seeks to invent and validate methods to quantify cardiac performance. We develop methods to measure cardiac structure (DWI/DTI), function (tagging and DENSE), flow (PC-MRI), and remodeling (diffusion, T1-mapping, fat-water mapping) for pediatrics and adults.
Fundamental to our research is a set of tools for numerically optimizing gradient waveforms, Bloch simulations, and patient-specific 3D-printed cardiovascular structures connected to computer controlled flow pumps. -
Ahmet Görkem Er
Postdoctoral Scholar, Radiology
BioAhmet Görkem Er, M.D., Ph.D., is a physician-scientist and postdoctoral fellow in Integrative Biomedical Imaging Informatics (IBIIS) at Stanford University. He graduated from Istanbul University Faculty of Medicine and completed dual residency training in internal medicine and infectious diseases and clinical microbiology at Hacettepe University. He also has a Ph.D. in medical informatics from Middle East Technical University.
As a Fulbright Ph.D. Dissertation Research Grantee (2022–2023), Dr. Er conducted research at the Stanford Center for Biomedical Informatics Research, focusing on multimodal data integration in COVID-19 patients. This work resulted in a publication in NPJ Digital Medicine demonstrating the value of combining clinical, imaging, and viral genomic data for improved disease modeling. He returned to Stanford in 2024 as a visiting researcher and is currently a postdoctoral fellow, where he combines his clinical background with advanced computational methods.
Dr. Er’s research focuses on developing artificial intelligence and multimodal data fusion approaches for complex diseases. His work integrates a broad spectrum of inputs, including medical imaging, histopathology, clinical data, genomics, and spatial transcriptomics, to improve patient stratification and support data-driven clinical decision-making.
