The authors posit that big networks will be the main approach to the next generation of robotic research, with the explosive number of networks models and increasing computational power of computers significantly extending the number of potential applications for robotic technologies while also bringing new challenges to the networking community.
Dr. Predrag S. Stanimirović received the Ph.D. degree from the Faculty of Philosophy, University of Niš, Niš, Serbia, in 1996. He is currently working as a Full Professor with the Department of Computer Science, Faculty of Sciences and Mathematics, University of Niš. He has authored over 260 publications in various scientific journals, including six research monographs. His current research interests include research encompasses diverse fields of mathematics, applied mathematics, and computer science, which span multiple branches of numerical linear algebra, recurrent neural networks, symbolic computation, and operations research.
Dr. Yudong Zhang is a professor at the School of Computing and Mathematical Sciences, University of Leicester, UK. His research interests include deep learning and medical image analysis. He is the Fellow of IET, Fellow of EAI, and Fellow of BCS. He is the Senior Member of IEEE, IES, and ACM. He is the Distinguished Speaker of ACM. He was the 2019 & 2021 recipient of Clarivate Highly Cited Researcher. He has (co)authored over 400 peer-reviewed articles. There are more than 50 ESI Highly Cited Papers and 5 ESI Hot Papers in his (co)authored publications. His citation reached 22817 in Google Scholar (h-index 84). He has conducted many successful industrial projects and academic grants from NIH, Royal Society, GCRF, EPSRC, MRC, Hope, British Council, and NSFC. He has served as (Co-)Chair for more than 60 international conferences and workshops (including more than 10 IEEE or ACM conferences). More than 50 news presses have reported his research outputs, such as Reuters, BBC, Telegraph, Physics World, UK Today News, etc.
Dr. Dunhui Xiao is a professor at Tongji University (Shanghai, China). He obtained his PhD from Imperial College London where he did his Post-doc. His research interests include numerical modelling with a focus on non-intrusive reduced-order modellingof Navier-Stokes equations, fluid-structure interactions, and multiphase flows in porous media. He is also interested in data-driven modelling, data science, physical data combined machine learning and optimisation. He is a PI of a number of grants including EPSRC. He sits on the editorial boards for a number of journals and he is the reviewer for many journals and the EPSRC grants.
Dr. Xinwei Cao received the bachelor's degree from Shandong University, Jinan, China, 2009, the master's degree from Tongji University, Shanghai, China, in 2012, and the Ph.D. degree from Fudan University, Shanghai, China, in 2017, all in management. She is currently a full Professor with Jiangnan University, Wuxi, China. Her research interests include operations research, operational management, computational and quantitative finance, empirical asset pricing, and financial market.
