Unity in Embedded System Design and Robotics: A Step-by-Step Guide (Chapman & Hall/CRC Artificial Intelligence and Robotics Series) Papeback - 2015

Dr Ata Jahangir Moshayedi is an associate professor at Jiangxi University of Science and Technology, China. He received his PhD in Electronic Science from Savitribai Phule Pune University, India. He is a member of IEEE, a life member of the Instrument Society of India (ISI) and Speed Society of India (SSI), and various conferences and journals. His research interest includes Robotics and Automation, Sensor Modelling, Bio-inspired robots, Mobile Robots, Embedded System, Machine Vision-based Systems, Virtual Reality, and Artificial Intelligence. He has published several papers in various journals and conferences and registered two patents so far in robotic and machine vision.

Dr Amin Kolahdooz received his PhD from BNUT in January 2015. He works as a Lecturer (Assistant Professor) at the school of Engineering and Sustainable Development, De Montfort University, UK. His research interests are mechanics and manufacturing engineering focused on Materials Processes, Machine Learning, VR, and AR in Manufacturing, Finite Element, and optimization methods. He registered one national patent, and published six books, and more than 70 articles in various world-renowned journals so far.

Leifa Liao is a professor at Jiangxi University of Science and Technology, a visiting scholar at Rochester University of Technology, a PhD in Management Science and Engineering from Xi'an Jiaotong University, and a key young and middle-aged teacher Jiangxi Province. He won the second prize for the 14th outstanding social science achievement in Jiangxi Province in 2011. Third Prize of the 15th Provincial Outstanding Achievement in Social Science of the Province. In 2015, he was the top ten teachers of Jiangxi University of Science and Technology. He published 50 papers and presided over 4 National Natural Science Foundations on the research of the Relationship between Organizational Learning and Knowledge Level Based on Multi-Agent Simulation.