Prof. Xiangjie Kong
Academic Vice Dean
Zhejiang University of Technology, China
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://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 36 and i10-index of 87, and a total of more than 4200 citations to his work according to Google Scholar. He is named in the2019 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.
Prof. Xinwei Yao
Zhejiang University of Technology, China
Xinwei Yao, Ph.D., currently serves as a professor and doctoral supervisor at the School of Computer Science and Technology at Zhejiang University of Technology. He is also the Vice President of the Frontier Cross Science Research Institute at Zhejiang University of Technology, a renowned youth in Zhejiang Province, and one of the top ten young technology talents in Hangzhou. The main research areas are the basic theories, core technologies, and comprehensive solutions of intelligent Internet of Things, swarm intelligence perception and collaboration, and intelligent robots. The scientific research achievements have won 7 provincial and ministerial level awards, including the National Wu Wenjun Artificial Intelligence Excellent Youth Award (the first recipient in Zhejiang Province), the Wu Wenjun Artificial Intelligence Technology Progress First Prize, the Second Prize for Technological Invention, the Second Prize for Technological Invention in Zhejiang Province, and the Second Prize for Science and Technology of the China Coal Industry Association, Published over 80 academic papers, including over 30 TOP journals such as IEEE TMC, IEEE TNNLS, IEEE IoT-J, IEEE TCAD, etc. One paper is highly cited in the journal, with three English monographs and three chapters published, and one Chinese work published. We have obtained over 20 national invention patents and over 10 software copyrights. Hosted more than 30 scientific research projects, including the National Natural Science Foundation of China (Youth Project, General Project), Zhejiang Provincial Outstanding Youth Science Fund, Zhejiang Provincial "Top Soldier" and "Leading Wild Goose" Projects, and Zhejiang Provincial "Unveiling and Leading" Major Enterprise Entrusted Projects. Serve as editor or guest editor for multiple international journals, chairman or committee member of multiple international conferences; Served as reviewers for over 50 top international academic journals and international academic conferences. At the same time, I have hosted multiple major horizontal projects such as the "Intelligent Internet of Things Integrated Platform" and "Intelligent Robot System", and have successfully applied them in practical scenarios such as State Grid, Hangzhou Urban Brain, and Future Community, generating significant economic benefits and social value.
Prof. Xin Yang
Beijing Jiaotong University, China
Xin Yang, professor and doctoral supervisor of the State Key Laboratory of Rail Transit Control and Safety, Beijing Jiaotong University. Main research directions: Systems Science, Transportation Planning and Management, Intelligent Control and Optimization of Transportation, Safety and Reliability of Rail Transit Systems, Control Engineering, Transportation (Professional Degree), Artificial Intelligence, etc. He has undertaken many projects of the National Natural Science Foundation of China and State Key Laboratory. At present, more than 50 academic papers have been published in well-known domestic and international journals such as the Transportation Research series, IEEE Transactions series, China Management Science, and Railway Journal. Among them, 5 papers (4 first authors and 1 corresponding author) have been selected as highly cited papers by ESI (the top 1% globally), and 1 paper has been included in the database of major technological innovation achievements in transportation.
Prof. Ran Tao
China Agricultural University, China
Professor Ran Tao is a doctoral fellow jointly trained by China Agricultural University and the Swiss Federal Institute of Technology in Lausanne. He is a postdoctoral fellow at Tsinghua University and a visiting scholar at the University of Tokyo. The main research areas are: 1. Research on efficient, green, and stable operation of pumped storage pump turbines; 2. Research on big data and intelligence of hydropower and pumped storage.