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Dr. Akshay Chaudhari is an Associate Professor (Research) of Radiology (Integrative Biomedical Imaging Informatics at Stanford) and of Biomedical Data Science at Stanford University. He serves as the Interim Division Chief of the Imaging Informatics research section at Stanford Radiology, Co-Director of Clinical AI at Stanford Radiology, and Associate Director of Research and Education at the Stanford AIMI Center. He leads the Machine Intelligence in Medical Imaging research group, with research interests focused on the application of artificial intelligence techniques to medical imaging, including representation learning, evaluation techniques, and large-scale multi-modal deep learning models in healthcare that integrate vision, language, and medical records data. His work has been published in Nature, Nature Medicine, Nature Biomedical Engineering, and other venues, and is funded by the NIH, ARPA-H, and industry partners. He is also a co-founder of Cognita Imaging.
Dr. Chaudhari earned a B.S. in Bioengineering with honors from the University of California, San Diego in 2012 and a Ph.D. in Bioengineering from Stanford University in 2017, where his doctoral work centered on novel MRI methods for musculoskeletal imaging and was supported by the National Science Foundation Graduate Research Fellowship, the Whitaker Fellowship, and the Siebel Fellowship. He completed postdoctoral training in Radiology at Stanford University. Among his honors are the W.S. Moore Young Investigator Award, the Junior Fellow Award, and the Outstanding Teacher Award from the International Society for Magnetic Resonance in Medicine, along with multiple additional young investigator awards. He holds additional appointments as a member of Bio-X, the Cardiovascular Institute, the Institute for Human-Centered Artificial Intelligence, the Wu Tsai Human Performance Alliance, and the Wu Tsai Neurosciences Institute, and serves on the internal advisory board of the Precision Health and Integrated Diagnostics Center.
Explore how Stanford researchers' NIH-funded Merlin AI model revolutionizes abdominal CT analysis for early chronic disease detection, addressing radiologist shortages and advancing precision medicine.
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