Machine learning and artificial intelligence may benefit from neuromorphic circuits and systems that are biologically-inspired. In this talk we will highlight the hardware-software synergy, memristor-based electronics and applications for emulation of neuronal behaviors, synaptic interconnects, and neuromorphic computing. Historical perspective including Moore’s law, More than Moores, the current state-of-the-art in nanoelectronics, and future challenges in the era of the fourth industrial revolution will be also discussed.
Sung-Mo “Steve” Kang is a Distinguished Chair Professor of the Jack Baskin School of Engineering, UC Santa Cruz, and Chancellor Emeritus of UC Merced and President Emeritus of KAIST. He received his B.S. degree from Fairleigh Dickinson University, Teaneck, New Jersey in 1970, M.S. degree from the State University of New York at Buffalo in 1972, and Ph.D. degree from the University of California at Berkeley in 1975, all in electrical engineering. He holds 16 patents, published over 500 papers, and co-authored ten books. He was a Visiting Professor at the University of Karlsruhe in 1997, the Technical University of Munich in 1998, KAIST in 2003, and the Swiss Federal Institute of Technology, Lausanne in 1989, 2006 and 2012. Dr. Kang is a Fellow of the IEEE, the Association for Computing Machinery (ACM), and the American Association for the Advancement of Science (AAAS). His research interest includes modeling and simulation of semiconductor devices; memristors and resistive memories, low-power VLSI circuit design, nano-bioelectronic circuits, and neuromorphic computing.