CAREER: Biologically Inspired Learning Algorithms for Artificial Sensorimotor Systems

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This project will investigate biologically-inspired methodologies and algorithms for several important problems in machine learning and AI: unsupervised feature learning, multi-modal integration of sensory data, and learning for real-time robotic systems with embedded sensors and actuators. The project will pursue both theoretical investigations of nonlinear properties of neurons and synapses and their role in processing of perceptual (visual, auditory, olfactory) stimuli, as well as the applications of such properties to the design of novel algorithms and architectures for processing of multi-modal perceptual stimuli. This research will integrate advances in the understanding of biological systems by building more advanced artificial sensorimotor systems. This project integrates research and an educational agenda that includes teaching and participation of students from the broader community in activities related to the overall goals of this research.