Steven Zucker is the David and Lucille Packard Professor of Computer Science and Biomedical Engineering at Yale University. He is responsible for many advances in how computers can be programmed to understand images, from detecting the edges of objects to recovering their three dimensional shape.
Zucker and his colleagues bring powerful ideas from pure mathematics to bear on these problems, and he has been one of the key figures in building bridges that reach from practical computer vision to the basic science of how the brain interprets the visual world. He often uses artwork to illustrate his ideas, connecting theories of how we process images to the artist's talent for manipulating our perceptions.
His lecture invites us to think about what makes drawings beautiful, and about what makes theories beautiful.
Bio
Steven W. Zucker
Steven W. Zucker is the David and Lucile Packard Professor of Computer Science and Electrical Engineering at Yale University. Before moving to Yale in 1996, he was Professor of Electrical Engineering at McGill University, Director of the Program in Artificial Intelligence and Robotics of the Canadian Institute for Advanced Research, and the Co-Director of the Computer Vision and Robotics Laboratory in the McGill Research Center for Intelligent Machines. He was elected a Fellow of the Canadian Institute for Advanced Research, a Fellow of the IEEE, and (by)Fellow of Churchill College, Cambridge.
Dr. Zucker has authored or co-authored papers on computational vision, biological perception, artificial intelligence, and robotics, and serves on the editorial boards of 8 journals.
Study of computers, their design (seecomputer architecture), and their uses for computation, data processing, and systems control, including design and development of computer hardware and software, and programming. The field encompasses theory, mathematical activities such as design and analysis of algorithms, performance studies of systems and their components, and estimation of reliability and availability of systems by probabilistic techniques. Because computer systems are often too large and complicated for failure or success of a design to be predicted without testing, experimentation is built into the development cycle.
A potentially very interesting lecture about visual perception -- how frustrating that the camera failed to capture fully half of the visual slides (at least as far as I had the patience to watch it.)