Prof. Wanyang Dai

Nanjing University, China

Biography: Wanyang Dai is a Distinguished Professor at Nanjing University and Chief Scientist at Su Xia Control Technology. He is the current President and CEO of the U.S.-based (blockchain and quantum computing) SIR Forum, President of the Jiangsu Probability and Statistical Society, and Chairman of the Jiangsu BigData-Blockchain and Smart Information Special Committee. He received his Ph.D. in mathematics, systems, and industrial engineering from the Georgia Institute of Technology in the USA. He was an MTS and principal investigator at U.S.-based AT&T Bell Labs (currently Nokia Bell Labs) with a project called “Technology Transfer,” now called a cloud system. He was the Chief Scientist at the DepthsData Digital Economic Research Institute. He published numerous influential papers in big-name journals, including Quantum Information Processing, Operations Research, Operational Research, Queueing Systems, Computers and Mathematics with Applications, Communications in Mathematical Sciences, and the Journal of Computational and Applied Mathematics. He has received various academic awards and has presented over 50 keynote and plenary speeches at IEEE/ACM, big data and cloud computing, quantum computing and communication technology, computational and applied mathematics, biomedical engineering, mathematics and statistics, and other international conferences. He has been serving as IEEE/ACM conference chairs, editors-in-chief, and editorial board members for various international journals ranging from artificial intelligence, machine learning, data science, wireless communication, pure mathematics, and statistics to their applications.

Prof. Xiangjie Kong

Zhejiang University of Technology, China

Biography: Dr. Xiangjie Kong is currently a Full Professor in the College of Computer Science & Technology, Zhejiang University of Technology (ZJUT), China. Previously, he was an Associate Professor in School of Software, Dalian University of Technology (DUT), China, where he was the Head of the Department of Cyber Engineering. He is the Founding Director of City Science of Social Computing Lab (The CSSC Lab) (http://www.cssclab.cn). He is/was on the Editorial Boards of 6 International journals. He has served as the General Co-Chair, Workshop Chair, Publicity Chair or Program Committee Member of over 30 conferences. Dr. Kong has authored/co-authored over 140 scientific papers in international journals and conferences including IEEE TKDE, ACM TKDD, IEEE TNSE, IEEE TII, IEEE TITS, IEEE NETW, IEEE COMMUN MAG, IEEE TVT, IEEE IOJ, IEEE TSMC, IEEE TETC, IEEE TASE, IEEE TCSS, WWWJ, etc.. 5 of his papers is selected as ESI- Hot Paper (Top 1‰), and 16 papers are ESI-Highly Cited Papers (Top 1%).  His research has been reported by Nature Index and other medias. He has been invited as Reviewers for numerous prestigious journals including IEEE TKDE, IEEE TMC, IEEE TNNLS, IEEE TNSE, IEEE TII, IEEE IOTJ, IEEE COMMUN MAG, IEEE NETW, IEEE TITS, TCJ, JASIST, etc.. Dr. Kong has authored/co-authored three books (in Chinese). He has contributed to the development of 14 copyrighted software systems and 20 filed patents. He has an h-index of 42 and i10-index of 104, and a total of more than 6200 citations to his work according to Google Scholar. He is named in the 2019 and 2020 world’s top 2% of Scientists List published by Stanford University. Dr. Kong received IEEE Vehicular Technology Society 2020 Best Land Transportation Paper Award, and The Natural Science Fund of Zhejiang Province for Distinguished Young Scholars. He has been invited as Keynote Speaker at 2 international conferences, and delivered a number of Invited Talks at international conferences and many universities worldwide.  His research interests include big data, network science, and computational social science. He is a Distinguished Member of CCF, a Senior Member of IEEE, a Full Member of Sigma Xi, and a Member of ACM.

Speech Title: Mobile Crowdsourcing: From Urban Big Data to Smart Cities

Abstract: Leveraging new communication technologies and Internet of Things (IoT) applications, multi-sourced urban big data can be collected. Local administrations and governments aim at managing the city infrastructures and optimize the public services in an efficient and sustainable manner. Furthermore, they adopt intelligent and cost-effective mobile applications to deal with natural disasters, such as pollution and traffic congestion. Mobile crowdsourcing (MCS) is an emerging paradigm for enabling smart cities, which integrates the wisdom of dynamic crowds with ubiquitous mobile devices to provide decentralized applications and services. Using MCS solutions, residents play the role of an active worker to generate a wealth of crowdsourced data which can significantly promote the development of smart cities. This talk highlight research challenges in computing and analyzing mobile crowdsourced data generated by large amount of participants/devices, and fusing multi-sourced and heterogeneous urban big data to facilitate applications towards smart cities.