AboutMachine learning allows machines to solve specific tasks without being explicitly programmed. In the recent past, it has seen a renaissance with successes of deep learning in image and speech recognition, natural language processing etc. However, most such success stories use power hungry supercomputer or GPU based implementations and do not respect real-time processing and learning constraints that are faced by biological organisms. Neuromorphic engineering, touted as one of the top 10 emerging technologies by the World Economic Forum 2015, aims to fill this gap by mimicking the structure and operation of the brain. It places emphasis on physical embodiment and aims to develop low-power silicon realizations of machine intelligence.
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General Chair
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Advisory CommiteeAsst. Prof. Shoushun Chen
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore |
Dr. Garrick Orchard Dept. of Electrical and Computer Engineering, National University of Singapore |
Local ArrangementsDr. Subhrajit Roy
Dr. Laxmi R. Iyer Centre for Bio Devices and Signal Analysis (VALENS) Nanyang Technological University |