This Integrative Graduate Education and Research Training (IGERT) award supports a new graduate training program at Rutgers University in perceptual science. The past decade of growth in perceptual technologies (automated recognition systems; usable virtual environments) has created the need for a new generation of realistic, comprehensive and innovative perceptual models, applicable to humans and implemented in machines. This IGERT will train students to develop and apply such models by integrating formal and experimental approaches to human and machine perception, bridging the gaps in language, perspective and knowledge that divide technically and behaviorally oriented disciplines. Training is organized around a new core curriculum in perceptual science that begins with foundational coursework in human perception and computer science, including bootstrapping courses to fill in gaps in undergraduate backgrounds. A cornerstone is a new one-year laboratory course, Integrative Methods in Perceptual Science, in which students learn to integrate human and computer perception by working on realistic projects in small teams with faculty mentors in a specialized multi-faceted teaching laboratory. Students will carry out integrative doctoral research, co-advised by faculty in human and computer perception, in one of 6 cross-cutting areas: animate vision, multi-modal cues for perceiving and grasping 3D objects, scanning and searching, visual-auditory integration, visual language, and visual communication. Broader impacts include development of novel perceptual devices and technologies usable in home, educational, clinical or industrial settings. IGERT is an NSF-wide program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the interdisciplinary background, deep knowledge in a chosen discipline, and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing innovative new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries.
