Prof. Zhengtao Ding (IEEE Senior Member)
The University of Manchester, UK
Biography: Prof. Zhengtao Ding graduated with BEng from Tsinghua University, Beijing, China. He then studied control engineering in the Control Systems Centre, UMIST, with MSc in systems and control and PhD in control systems. He joined as a lecturer in School of Engineering, University of Manchester in September 2003 after having been a lecturer in Ngee Ann Polytechnic, Singapore, for ten years. He joined the Control Systems Centre, School of Electrical and Electronic Engineering in 2004, after the merger of the UMIST and Victoria University of Manchester, and he is now Professor of Control Systems in The University of Manchester. His research interests were initially focused on nonlinear and adaptive control theory, and more recently are focused on distributed optimization and control of network-connected dynamic systems, distributed learning and AI applications. His research projects cover various industrial applications, such as distributed optimization in micro grids, formation control of mobile robots and UAVs etc., He has published over 300 research papers, and authored/co-authored three books, including a book entitled “Nonlinear and Adaptive Control Systems” published by IET in 2013. He is a fellow of The Alan Turing Institute, the UK’s national institute for data science and artificial intelligence. He serves as the Editor-in-Chief for Drones and Autonomous Vehicles, and the Specialty Chief Editor for Nonlinear Control for Frontiers in Control Engineering, and he also serves as, or has been, an associate editor for IEEE Transactions on Automatic Control, IEEE Control Systems Letters, IEEE Transactions on Circuit and Systems II, Journal of Franklin Institute and several other journals.
Prof. Guojian Cheng
Xi'an Shiyou University, China; Xijing University, China
Biography: He has long been engaged in teaching and research in artificial intelligence and machine learning. The main research topics involve the application of artificial intelligence and machine learning in geoscience and petroleum engineering. His research interests include artificial intelligence, machine learning, data science, big data technology, pattern recognition, data mining, image processing, and intelligent reservoir engineering. He has published more than 200 articles in related academic research fields and international conferences, and more than 20 books in the fields of artificial intelligence, big data and machine learning. He is a member of CCF of China Computer Society, a member of Microelectronics Committee of CCF of Shaanxi Province, a director of Computer Education Society of Shaanxi Province, a member of SPE of International Society of Petroleum Engineers; a member of European Geophysical Society; an editorial board member of Journal of Xi'an University of Petroleum (Natural Science Edition); and an assessor of National Natural Science Foundation of China. He has been the leader of the master's program of Software Engineering and Theory in the School of Computer Science of Xi'an Petroleum University, the director of the Institute of Intelligent Digital Oilfield, and was honored with the title of Outstanding Returned Scholar in Shaanxi Province in 2009.
Prof. Akash Saxena (IEEE Senior Member)
School of Engg. & Technology Central University of Haryana, Mahendergarh, India
Biography: Dr. Akash received the Bachelor of Technology in Engineering with honors in Electrical Engineering from the Department of Electrical Engineering, Engineering College Kota, Kota Rajasthan, India in 2001,Master of Technology with honors in Power System Engineering from the Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, India in 2008 and Ph.D. degree in Power System Dynamics from the Malaviya National Institute of Technology, India in 2015. Dr. Akash has presented research work at national/international conferences in India and abroad. His work has been published in leading journals in the form of short communication/letters /articles/research papers. He is associated with many professional organizations as an editor, reviewer and adviser. His research interests are the Computational Intelligence, Application of Artificial Intelligence in the power system, Control theory, smart grid, signal processing and Metaheuristics.
Prof. Zeashan Hameed Khan (IEEE Senior Member)
IRC-IMR, King Fahd University of Petroleum and Minerals, Saudi Arabia
Biography: Zeashan Hameed Khan is currently working as a Senior researcher at IRC-IMR, King Fahd University of Petroleum and Minerals, Saudi Arabia. He obtained his MS and PhD in Automation and Computer Integrated manufacturing from University of Grenoble in 2007 and 2010 respectively. He is a leading expert in robotics, AI, and advanced manufacturing systems, with a strong focus on the diagnosis and fault tolerant control, AI-driven decision making, and additive manufacturing. Dr Khan’s work continuously bridges academic knowledge with practical applications in smart manufacturing and autonomous systems. He has authored more than 70 journal and conference papers. He is serving as an editorial member in several leading journals. He is a Senior member of IEEE.