CCCI 2023 Keynote Speakers

Bio

Dr. Tie Qiu is currently a Full Professor at School of Computer Science and Technology, Tianjin University, China. Prior to this position, he held assistant professor in 2008 and associate professor in 2013 at School of Software, Dalian University of Technology. He was a visiting professor at department of electrical and computer engineering of Iowa State University in U.S. (2014-2015).

He serves as an associate editor of IEEE/ACM Transactions on Networking (ToN), IEEE Transactions on Network Science and Engineering (TNSE) and IEEE Transactions on Systems, Man, and Cybernetics: Systems, area editor of Ad Hoc Networks (Elsevier), associate editor of Computers and Electrical Engineering (Elsevier), Human-centric Computing and Information Sciences (Springer), a guest editor of Future Generation Computer Systems. He serves as General Chair, Program Chair, Workshop Chair, Publicity Chair, Publication Chair or TPC Member of a number of international conferences.

He has authored/co-authored 10 books, over 200 scientific papers in international journals and conference proceedings, such as IEEE/ACM Transactions on Networking, IEEE Transactions on Mobile Computing, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Industrial Informatics, IEEE Communications Surveys & Tutorials, IEEE Communications, INFOCOM, GLOBECOM etc. There are 18 papers listed as ESI highly cited papers. He has contributed to the development of 6 copyrighted software systems and invented 20 patents. He is a distinguished member of China Computer Federation (CCF) and a Senior Member of IEEE and ACM.

Abstract

Industrial Internet of Things (IIoT) includes large scale networks, such as Industrial wire networks, wireless networks, ad hoc networks and other communication networks, the conventional self-organization strategies are difficult to adapt the dynamic Industrial scenarios. This talk combines the population state with the evolutionary process and proposes an adaptive robustness evolution algorithm for scale-free IIoT topologies. Finally, the future trends for smart IIoT will be discussed.

Bio

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 200 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 18 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 47 and i10-index of 115, and a total of more than 7200 citations to his work according to Google Scholar. He is named in the 2019 - 2021 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 over 20 international conferences and delivered a number of Invited Talks at international conferences and many universities worldwide. His research interests include urban computing, network science, and mobile computing. He is a Distinguished Member of CCF, a Senior Member of IEEE, a Full Member of Sigma Xi, and a Member of ACM.

Abstract

A modern city is a ternary space that contains the physical world, human society, and information space. Urban spatial-temporal data is the foundation of urban travel intelligence. Based on urban spatial-temporal data, the accurate description of travel information in cities is the premise of forecasting/warning and decision-making assistance. Spatio-temporal graph learning having been extensively used in intelligent transportation systems in recent years, proves effective for many tasks in real-world applications, such as regression, classification, clustering, matching, and ranking. Spatio-temporal graph learning brings new idea to solve the challenges for smart transportation, improve the efficiency of urban resource utilization, optimize urban management and services, and improve residents' lives quality towards smart cities. This report will explore the research frontiers of spatio-temporal graph learning-based traffic data mining and analysis and its application in intelligent transportation systems and introduce some related work.

Bio

Prof. Jalel Ben-Othman received his B.Sc. and M.Sc. degrees both in Computer Science from the University of Pierre et Marie Curie, (Paris 6) France in 1992, and 1994 respectively. He received his PhD degree from the University of Versailles, France, in 1998. He is currently full professor at the University of Paris 13 since 2011 and member of L2S lab at CentraleSupélec. Dr. Ben-Othman's research interests are in the area of wireless ad hoc and sensor networks, VANETs, IoT, performance evaluation and security in wireless networks in general. He was the recipient of the IEEE COMSOC Communication Software technical committee Recognition Award in 2016, the IEEE computer society Meritorious Service Award in 2016, and he is a Golden Core Member of IEEE Computer Society, AHSN Exceptional Service and Contribution Award in 2018 and the VEHCOM Fabio Neri award in 2018. He has served as steering committee member of IEEE Transaction on Mobile computing (IEEE TMC), he is currently Area Editor of IEEE communication letters (IEEE COMML) an editorial board member of several journals (IEEE Networks, IEEE IoT journal, JCN, IJCS, SPY, Sensors, ...). He has also served as TPC Co-Chair for IEEE Globecom and ICC conferences and other conferences as (WCNC, IWCMC, VTC, ComComAp, ICNC, WCSP, Q2SWinet, P2MNET, WLN, ...). He was the chair of the IEEE Ad Hoc and sensor networks technical committee January 2016-2018, he was previously the vice chair and secretary for this committee. He has been appointed as IEEE COMSOC distinguished lecturer from 2015 to 2018 and IEEE VTS distinguished lecturer from 2020 to 2023 where he did several tours all around the world.

Abstract

Vehicular ad hoc network (VANET) has been researched and achieved by several organizations to develop the intelligent transportation system (ITS). VANETs represent a distinct instance within the realm of mobile ad hoc networks (MANETs), where the nodes are vehicles themselves. The aim of establishing a VANET network is to ensure its safety and dependability. Hence, the development of VANET aims to improve transportation reliability, optimize driving and navigation, and enhance the vehicle user’s safety. Vehicles can self - react in order to avoid accidents by preventing the proximity location and transporting them to the conductor. Communications in the VANET are very challenging and existing solutions, for instance, from which the Ad Hoc networking field are not adapted. Some solutions have been proposed and researched for security in the VANET. However, they have not resolved strictly VANET communication problems. This is due to some special features of the VANET, including the high speed of vehicles, mobility patterns of vehicles. New efforts at different levels of the communications systems are required to be present at the MAC, routing, and security levels. In this talk we tackle the problems of security in those networks. Existing problems/solutions are showed, issues and perspectives will be exposed as well.

Bio

Laurence T. Yang got his BE in Computer Science and Technology and BSc in Applied Physics both from Tsinghua University, China and Ph.D in Computer Science from University of Victoria, Canada. He is the Academic Vice-President and Dean of School of Computer Science and Technology, Hainan University, China. His research includes Cyber-Physical-Social Intelligence. He has published 300+ papers in the above area on top IEEE/ACM Transactions with total citations of 36691 and H-index of 96 including 8 and 40 papers as top 0.1% and top 1% highly cited ESI papers, respectively.

His recent honors and awards include the member of Academia Europaea, the Academy of Europe (2021), the John B. Stirling Medal (2021) from Engineering Institute of Canada, IEEE Sensor Council Technical Achievement Award (2020), IEEE Canada C. C. Gotlieb Computer Medal (2020), Clarivate Analytics (Web of Science Group) Highly Cited Researcher (2019, 2020, 2022), Fellow of Institution of Engineering and Technology (2020), Fellow of Institute of Electrical and Electronics Engineers (2020), Fellow of Engineering Institute of Canada (2019), Fellow of Canadian Academy of Engineering (2017).

Abstract

The booming growth and rapid development in embedded systems, wireless communications, sensing techniques and emerging support for cloud computing and social networks have enabled researchers and practitioners to create a wide variety of Cyber-Physical-Social Systems (CPSS) that reason intelligently, act autonomously, and respond to the users’ needs in a context and situation-aware manner, namely Cyber-Physical-Social Intelligence. It is the integration of computation, communication and control with the physical world, human knowledge, and sociocultural elements. It is a novel emerging computing paradigm and has attracted wide concerns from both industry and academia in recent years.

This talk will present our latest research on Cyber-Physical-Social Intelligence. Corresponding case studies in some typical applications will be shown to demonstrate the feasibility and flexibility.

Bio

Dr. Eirini Eleni Tsiropoulou is an Associate Professor, and Computer Engineering Area Chair at the Department of Electrical and Computer Engineering, University of New Mexico. She obtained her Diploma, MBA, and Ph.D. in Electrical and Computer Engineering from National Technical University of Athens in 2008, 2010, and 2014, respectively. Her main research interests lie in the area of cyber-physical social systems and wireless heterogeneous networks, with emphasis on network modeling and optimization, resource orchestration in interdependent systems, reinforcement learning, game theory, network economics, and Internet of Things. Five of her papers received the Best Paper Award at IEEE WCNC in 2012, ADHOCNETS in 2015, IEEE/IFIP WMNC 2019, INFOCOM 2019 by the IEEE ComSoc Technical Committee on Communications Systems Integration and Modeling, and IEEE/ACM BRAINS 2020. She was selected by the IEEE Communication Society - N2Women - as one of the top ten Rising Stars of 2017 in the communications and networking field. She received the NSF CRII Award in 2019, the Early Career Award from the IEEE Communications Society Internet Technical Committee in 2019, and the Junior Faculty Teaching Excellence Award, School of Engineering, University of New Mexico in 2018. Her research is mainly supported by the Department of Energy, National Science Foundation, and industry. She is an Associate Editor for IEEE Transactions on Green Communications and Networking, IEEE Transactions on Machine Learning in Communications and Networking, IEEE Networking Letters, IEEE Transactions on Network Science and Engineering, IEEE IT Professional, and IEEE Vehicular Technology Magazine.

Abstract

In the realm of critical infrastructure and advanced location-based services, the demand for precise Position, Navigation, and Timing (PNT) systems has ignited a quest for innovative alternatives. This keynote introduces a revolutionary response to the challenges faced by Global Navigation Satellite Systems (GNSS) when confronted with diverse conditions. The talk unveils an inventive PNT solution that hinges on Reconfigurable Intelligent Surfaces (RISs). The core of this innovation lies in a symbiotic game-theoretic framework, meticulously designed to elevate PNT accuracy and efficiency. We explore the orchestration and configuration of RISs. The synergy of Game Theory and Reinforcement Learning (RL) empowers us to tackle the complex challenge of enhancing PNT performance. Our novel Satisfaction Games empower targets to independently optimize the count of contributing RISs for PNT services, adapting to the environment. An advanced RL algorithm expertly selects the specific ensemble of RISs. We extend this approach to optimizing phase shifts within RISs, strategically enhancing signal strength through reflected signals. This optimization technique draws inspiration from mutualistic symbiotic relationships observed in biological systems. Collaborator nodes, supported by RISs and anchor nodes with known coordinates, form a strategic alliance with targets of unknown positions. This transforms the task of minimizing positioning and timing errors into a dynamic non-cooperative game, showcasing the presence of a Nash Equilibrium through potential game principles. Rigorous modeling and simulation underscore the effectiveness of the proposed methodology. In conclusion, this keynote emerges as a beacon of promise for fortified PNT solutions, adept at bridging the precision and dependability gaps prevalent in GNSS technology. This innovation stands poised to cater to sectors reliant on precise positioning, navigation, and timing, charting a course towards an era of unwavering reliability.

Bio

Prof. Chengchao Liang received a PhD. in Electrical and Computer Engineering from Carleton University, Canada in 2017 awarded the Senate Medal. He is currently a Professor with the School of Communication and Information Engineering and the Vice Dean of the Advanced Science Research Institution, Chongqing University of Posts and Telecommunications, Chongqing, China. Prior to this, He was a cross-appointed Postdoctoral Fellow in the Department of Systems and Computer Engineering, Carleton University as well as Huawei Ottawa Research & Development Centre from 2017 to 2019. He is in the Editorial Boards of EURASIP Journal on Wireless Communications and Networking, Transactions on Emerging Telecommunications Technologies, and Computer Communications. He has served as the reviewer and the TPC member for many IEEE journals and conferences. His research interests include wireless communications, satellite networks, Internet protocols and optimization theory.

Abstract

The integration of space, air, and ground is a central characteristic of the 6G network. This report provides a succinct overview of the space-air-ground integrated information network, considering aspects of system structure, protocols, networks, services, and end-user devices.

We begin by examining the development trajectory and fundamental framework of the integrated network, outlining how the amalgamation of terrestrial and aerial networks can achieve comprehensive three-dimensional global coverage. This network meets the pervasive coverage demands for all terrains and airspaces and facilitates on-demand connectivity for users at all times and locations. The report then delves into the primary technologies enabling the deep integration of space-based, air-based networks and ground mobile communication networks. Topics include multi-access integration for the 6G space-air-ground network and methods for delivering faster speeds, superior Quality of Service (QoS), and enhanced reliability via satellites. This ensures users receive reliable, uninterrupted communication services.