Stanford University
Showing 21-30 of 38 Results
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Joseph M. DeSimone
Sanjiv Sam Gambhir Professor of Translational Medicine, Professor of Chemical Engineering and, by courtesy, of Chemistry, of Materials Science and Engineering, and of Operations, Information and Technology at the Graduate School of Business
BioJoseph M. DeSimone is the Sanjiv Sam Gambhir Professor of Translational Medicine and Chemical Engineering at Stanford University. He holds appointments in the Departments of Radiology and Chemical Engineering with courtesy appointments in the Department of Chemistry and in Stanford’s Graduate School of Business.
The DeSimone laboratory's research efforts are focused on developing innovative, interdisciplinary solutions to complex problems centered around advanced polymer 3D fabrication methods. In Chemical Engineering and Materials Science, the lab is pursuing new capabilities in digital 3D printing, as well as the synthesis of new polymers for use in advanced additive technologies. In Translational Medicine, research is focused on exploiting 3D digital fabrication tools to engineer new vaccine platforms, enhanced drug delivery approaches, and improved medical devices for numerous conditions, with a current major focus in pediatrics. Complementing these research areas, the DeSimone group has a third focus in Entrepreneurship, Digital Transformation, and Manufacturing.
Before joining Stanford in 2020, DeSimone was a professor of chemistry at the University of North Carolina at Chapel Hill and of chemical engineering at North Carolina State University. He is also Co-founder, Board Chair, and former CEO (2014 - 2019) of the additive manufacturing company, Carbon. DeSimone is responsible for numerous breakthroughs in his career in areas including green chemistry, medical devices, nanomedicine, and 3D printing. He has published over 350 scientific articles and is a named inventor on over 200 issued patents. Additionally, he has mentored 80 students through Ph.D. completion in his career, half of whom are women and members of underrepresented groups in STEM.
In 2016 DeSimone was recognized by President Barack Obama with the National Medal of Technology and Innovation, the highest U.S. honor for achievement and leadership in advancing technological progress. He has received numerous other major awards in his career, including the U.S. Presidential Green Chemistry Challenge Award (1997); the American Chemical Society Award for Creative Invention (2005); the Lemelson-MIT Prize (2008); the NIH Director’s Pioneer Award (2009); the AAAS Mentor Award (2010); the Heinz Award for Technology, the Economy and Employment (2017); the Wilhelm Exner Medal (2019); the EY Entrepreneur of the Year Award (2019 U.S. Overall National Winner); and the Harvey Prize in Science and Technology (2020). He is one of only 25 individuals elected to all three branches of the U.S. National Academies (Sciences, Medicine, Engineering). DeSimone received his B.S. in Chemistry in 1986 from Ursinus College and his Ph.D. in Chemistry in 1990 from Virginia Tech. -
Terry Desser
Professor of Radiology (Abdominal Imaging), Emerita
Current Research and Scholarly InterestsImaging of gastrointestinal tract cancer
Ultrasound
Simulated learning environment -
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.
