Prof. Simon Yang
2528
ACIT'2024 will be held in Zarqa University, December 10-12, 2024 -Zarqa, Jordan
2528
Head of the Advanced Robotics and Intelligent Systems (ARIS) Laboratory, he will address the title:
Biologically inspired Intelligent Systems with Applications to Information Technology.
Prof. Yang received the B.Sc.
degree in engineering physics from Beijing University, China, in 1987, the first of his two M.Sc. degrees in biophysics from Chinese Academy of
Sciences, Beijing, China, in 1990, the second M.Sc. degree in electrical
engineering from the University of Houston, USA, in 1996, and the Ph.D. degree in electrical and computer
engineering from the University of Alberta, Edmonton, Canada, in 1999. He joined
the University of Guelph in Canada in August 1999. Currently he is a Professor and the Head of the Advanced Robotics and Intelligent Systems
(ARIS) Laboratory at the University
of Guelph. Prof. Yang’s research expertise is in the area of intelligent
systems, robotics, sensors and
measurements, multi-sensor fusion, wireless sensor networks, intelligent
control, and computational neuroscience. Dr. Yang has served as an Associate Editor of IEEE Transactions on Neural Networks, IEEE Transactions on Systems, Man, and
Cybernetics, Part B, International Journal of Robotics and Automation, and several
other international journals. He is an Associate Editor-in-Chief of International Arab Journal of Information
Technology. Dr. Yang has involved in the organization of many international
conferences. He is the General Chair of 2006 International Conference of
Sensing, Computing and Automation, and 2011 IEEE International Conference of
Automation and Logistics.
More information will be found on professor Yang webpage: http://www.uoguelph.ca/~syang/
Abstract
Studies of biologically inspired intelligent systems have made significant progress in both understanding the biological systems and applying to various information technologies. In this talk, I will start with a very brief introduction to biologically inspired intelligent system approaches, such as neurodynamics models and gated dipole models. Then, several bio-inspired intelligent systems for information technology applications will be presented, including intelligent real-time monitoring and control of livestock odors using novel electronic noses and wireless sensor networks; real-time sensing, path planning, tracking, control, and teleoperation of autonomous mobile robots; and intelligent real-time coordination and cooperation of multi-robot systems. Finally, some implemented intelligent information technologies to real mobile robotic applications such as harvesting robots and fire fighting robots will be presented.