Artificial Intelligence in China
Description
This book brings together papers presented at the International Conference on Artificial Intelligence in China (ChinaAI) 2019, which provided a venue for disseminating the latest advances and discussing the interactions and links between the various subfields of AI. Addressing topics that cover virtually all aspects of AI and the latest developments in China, the book is chiefly intended for undergraduate and graduate students in Electrical Engineering, Computer Science, and Mathematics, for researchers and engineers from academia and industry, and for government employees (e.g. at the NSF, DOD, and DOE).
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Persons
Dr. Qilian Liang is a Professor at the Department of Electrical Engineering, University of Texas at Arlington (UTA), USA, where he has been working since August 2002. Prior to this, he was a member of the technical staff at Hughes Network Systems Inc. in San Diego, California. Dr. Liang received his B.S. degree from Wuhan University, China, in 1993; his M.S. degree from Beijing University of Posts and Telecommunications, China in 1996; and a Ph.D. degree from the University of Southern California (USC), Los Angeles, USA in May 2000, all in Electrical Engineering. His research interests include communications, signal processing and fuzzy logic systems. Dr. Liang has published more than 270 journal and conference papers, 6 book chapters, and has 6 U.S. patents pending. He received 2002 IEEE Transactions on Fuzzy Systems Outstanding Paper Award; 2003 U.S. Office of Naval Research (ONR) Young Investigator Award; 2005 UTA College of Engineering Outstanding Young Faculty Award; 2007,2009, 2010 U.S. Air Force Summer Faculty Fellowship Program Award; 2012 UTA College of Engineering Excellence in Research Award; 2013 UTA Outstanding Research Achievement or Creative Activity Award; and was inducted into UTA Academy of Distinguished Scholars in 2015.
Content
Deep Learning and Neural Networks.- Machine Learning.- Computer Vision.- Knowledge Representation and Reasoning.- Probabilistic Reasoning.- Statistical Learning.- Reinforcement Learning.- Decision Making.- Fuzzy Systems.- Evolutionary Computing.- Inference and Prediction.- Human-Inspired Learning and Computing.- Autonomous Vehicle.- Data Mining.- Spoken Language Processing.- Pattern Analysis and Recognition.- Robotics.- AI for Sensing.- AI for Communications.- AI for Internet of Things.- AI for Signal Processing.- AI for Education.- AI for Healthcare.- AI for Other Applications.