报告题目: A Synergistic Ocean Observing System in Monterey Bay 

报告人:      MIT Dr. Yanwu  Zhang

          Senior Member IEEE/  Senior Research Specialist

          Monterey Bay Aquarium Research Institute
报告时间: 3月6日（周日）下午3：00

报告地点: 信电系微电子三楼多媒体教室

报告摘要：

The Monterey Accelerated Research System (MARS) is a deep-sea cabled observatory developed by the Monterey Bay Aquarium Research Institute (MBARI) in collaboration with WHOI, UW APL, NASA JPL, with funding from the National Science Foundation (NSF). We will present representative science experiments that have been run on the MARS observatory. Then we will introduce the state-of-the-art of autonomous underwater vehicles (AUVs) and adaptive sampling techniques we have recently developed. Ocean observatories and AUVs comprise a synergistic system that enables sustainable ocean observation and fast response to oceanographic events.

报告人简介:

Yanwu Zhang received the B.S. degree in Electrical Engineering and the M.S. degree in Underwater Acoustics Engineering from Northwestern Polytechnic University, Xi'an, China, in 1989 and 1991, respectively. He received the M.S. degree in Electrical Engineering and Computer Science from MIT, the M.S. degree and the Ph.D. degree in Oceanographic Engineering from the MIT/WHOI Joint Program,in 1998 and  2000, respectively. Now, he is  a Senior Research Specialist of the Monterey Bay Aquarium Research Institute.  Dr. Zhang is a Senior Member of IEEE since 2005， a member of AGU, and a member of Sigma Xi.

He works on developing and field-testing adaptive sampling algorithms for autonomous underwater vehicles (AUVs), designing sampling strategy for ocean observatories comprising AUVs and moorings, and developing a long-range AUV Tethys. Dr. Zhang's current research interests are mainly in spatio-temporal signal processing and its applications to AUV's sampling of oceanographic processes. He has published 15 peer-reviewed journal papers and as many conference papers. He served as a reviewer for IEEE Journal of Oceanic Engineering, IEEE Transactions on Neural Networks, Journal of Atmospheric and Oceanic Technology, Journal of Geophysical Research (Oceans), Deep-Sea Research, Ocean Engineering (Elsevier), and International Journal of Neural Systems, as well as for National Science Foundation (NSF) and National Oceanic and Atmospheric Administration (NOAA) proposals.