School of Engineering
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Professor of Radiology (Integrative Biomedical Imaging Informatics) and, by courtesy, of Medicine (Medical Informatics) and of Electrical Engineering
Current Research and Scholarly InterestsMy research seeks to advance the clinical and basic sciences in radiology, while improving our understanding of biology and the manifestations of disease, by pioneering methods in the information sciences that integrate imaging, clinical and molecular data. A current focus is on content-based radiological image retrieval and integration of imaging features with clinical and molecular data for diagnostic, prognostic, and therapy planning decision support.
Professor of Medicine (Cardiovascular Medicine)On Partial Leave from 09/05/2023 To 06/30/2024
Current Research and Scholarly InterestsDr. Narayan directs the Computational Arrhythmia Research Laboratory, whose goal is to define the mechanisms underlying complex human heart rhythm disorders, to develop bioengineering-focused solutions to improve therapy that will be tested in clinical trials. The laboratory has been funded continuously since 2001 by the National Institutes of Health, AHA and ACC, and interlinks a disease-focused group of clinicians, computational physicists, bioengineers and trialists.
Professor of Mechanical Engineering
BioResearch involves development of improved methods for predicting the fatigue life of engineering materials, incuding the effects of manufacturing processes, and investigation of new approaches in the field of experimental mechanics, such as determination of residual stresses using optical methods.
2013 - 2018 : Stanford : Lecturer : Visual Thinking, ME115C: Design and Business Factors
2018 - Present : Stanford : Lead Lecturer : Design 161 Capstone
2004 - 2007 : Azud : VP Product
2007 - Present : Daylight Design : Partner
Juan Carlos Niebles
Sr Research Engineer, Computer Science
Current Research and Scholarly InterestsThe goal of my research is to enable computers and robots to perceive the visual world by developing novel computer vision algorithms for automatic analysis of images and videos. We tackle fundamental open problems in computer vision research related to the visual recognition and understanding of human actions and activities, objects, scenes, and events. We also develop systems that solve practical world problems by introducing cutting-edge computer vision technologies into new domains.