Dr. Alan Yuille is a distinguished Bloomberg Distinguished Professor holding joint primary appointments in the Departments of Cognitive Science and Computer Science at Johns Hopkins University. After earning his BA in mathematics from the University of Cambridge in 1976 he completed his PhD in theoretical physics under the supervision of Professor S.W. Hawking in 1981. His academic journey includes significant roles as a research scientist at MIT's Artificial Intelligence Laboratory and Harvard's Division of Applied Sciences from 1982 to 1988 followed by faculty positions at Harvard University until 1996. He subsequently served as a senior research scientist at the Smith-Kettlewell Eye Research Institute and joined UCLA as a full professor with joint appointments across multiple departments before moving to Johns Hopkins in 2016.
Dr. Yuille has established himself as a leading authority in developing computational models that bridge biological vision and artificial intelligence systems. His research program spans computational models of vision mathematical theories of cognition and advanced neural network approaches to medical image analysis with over 300 publications and more than 111000 citations reflected in his substantial scholarly impact. He directs the influential Computational Cognition Vision and Learning research group which develops frameworks enabling computers to reconstruct three-dimensional structures from visual inputs creating artificial vision systems with applications for assisting individuals with visual impairments. His current Felix Project represents a significant translational effort to develop computer programs that can detect early signs of pancreatic cancer in CT scans with greater accuracy than human experts potentially revolutionizing diagnostic approaches in oncology.
Beyond his technical contributions Professor Yuille plays a pivotal role in advancing interdisciplinary research through his affiliation with the Center for Brains Minds and Machines and the NSF Expeditions-in-Computing project Visual Cortex on Silicon. His teaching portfolio includes advanced courses such as Probabilistic Models of the Visual Cortex and Vision as Bayesian Inference where he trains the next generation of researchers in cutting-edge computational approaches. He previously co-directed the UCLA Center for Cognition Vision and Learning demonstrating his longstanding commitment to fostering collaborative research environments that bridge traditional disciplinary boundaries. Dr. Yuille continues to push the frontiers of vision science and artificial intelligence with his ongoing work focused on creating more robust and biologically plausible models that deepen our understanding of both human cognition and machine perception capabilities.
