Jiangzhou Wang (Fellow, IEEE) has been a Professor with the University of Kent, U.K., since 2005. He has published over 400 papers and four books in the areas of wireless communications. He was a recipient of the Best Paper Award from the IEEE GLOBECOM 2012. He was an IEEE Distinguished Lecturer from 2013 to 2014. He was the Technical Program Chair of the 2019 IEEE International Conference on Communications, Shanghai, the Executive Chair of the IEEE ICC 2015, London, and the Technical Program Chair of the IEEE WCNC 2013. He has served as an Editor for a number of international journals, including IEEE Transactions on Communications from 1998 to 2013. He is a Fellow of the Royal Academy of Engineering, U.K., and IET.
Prof. Taik A. Rashid
Principal Fellow for the Higher Education Authority (PFHEA-UK), University of Kurdistan Hewlêr (UKH), Iraq
Dr. Tarik Ahmed Rashid is a Principal Fellow for the Higher Education Authority (PFHEA-UK) and a professor in the Department of Computer Science and Engineering at the University of Kurdistan Hewlêr (UKH), Iraq. His areas of research cover the fields of Artificial Intelligence, Nature Inspired Algorithms, Swarm Intelligence, Computational Intelligence, Machine Learning, and Data Mining. He is a member of (IEEE, Machine Intelligence Research Labs). He has journal editorial experience as an editor/board member and acted as a Keynote conference speaker in several conferences, conference chairing, conference program committee member, etc.
His research work spans mainly three areas:
The first research area is optimization. Optimization means trying to select the best solution for a specific problem among many alternative solutions. The objective can be minimization, such as minimizing cost or time, or it can be maximization, such as maximizing profit or production. There are two main methods for optimization: deterministic and stochastic. Our focus is on the second type. Metaheuristics algorithms are of stochastic types, which are inspired by nature. It is proven that when the number of possible solutions is large enough which makes it infeasible for the deterministic algorithms to be used, metaheuristic algorithms come to play their important role by providing decent solutions during an acceptable time. It is worth mentioning that our team has designed a number of single and multi-objective optimization algorithms, such as FDO, CDDO, DSO, ANA, FOX, LPB, ECA*, and iECA*.