David G. Stork

July 11, 2009

Dr. David G. Stork is Chief Scientist of Ricoh Innovations and Consulting Professor of Statistics at Stanford University. The breadth of his interests and contributions is revealed through the academic departments and programs in which he has held faculty positions in leading liberal arts colleges and research universities: Physics, Mathematics, Electrical Engineering, Statistics, Computer Science, Neuroscience, Psychology, and Art and Art History. He is a Fellow of the International Association for Pattern Recognition, “For contributions to pattern recognition education, machine learning, speech recognition, and the application of computer vision to the study of art” and Chair of its Technical Committee on Computer Vision in Cultural Heritage Applications. He has published six books/proceedings volumes and another production, including “Seeing the Light: Optics in nature, photography, color, vision and holography” (Wiley), the leading textbook on optics in the arts, “Computer image analysis in the study of art” (SPIE), the first volume in this discipline, “Computer vision and image analysis in the study of art” (forthcoming), “Pattern Classification” (2nd ed., Wiley), the world’s all-time best-selling textbook in the field, translated into three languages and used in courses in over 250 universities worldwide, and “HAL’s Legacy: 2001′s computer as dream and reality” (MIT), the source of his PBS television documentary ’2001: HAL’s Legacy.’ A graduate in physics of the Massachusetts Institute of Technology and the University of Maryland at College Park, he also studied art history at Wellesley College and was Artist-in-Residence through the New York State Council of the Arts. He is a pioneer in the application of rigorous computer vision in the study of master paintings thus forming the foundation of the new discipline of computational art history. He was the founder of the Open Mind Initiative, one of the earliest systems for collecting data contributed over the internet for building AI systems. He holds 38 US patents and has published numerous technical papers on human and machine learning and perception of patterns, physiological optics, image understanding, concurrency theory, theoretical mechanics, optics, image processing. He has served on the editorial boards of five international journals and has delivered over 60 plenary, invited or distinguished lectures at universities and conferences (atop over 230 traditional invited colloquia and seminars).

See essays by this author:
Artificial Intelligence in the World Wide Web