Prof. Kin K. Leung, Imperial College, UK (IEEE Fellow)

Biography: Kin K. Leung received his B.S. degree from the Chinese University of Hong Kong, and his M.S. and Ph.D. degrees from University of California, Los Angeles.He worked at AT&T Bell Labs and its successor companies in New Jersey from 1986 to 2004. Since 2004, he has been the Tanaka Chair Professor at Imperial College in London. His current research focuses on machine learning and optimization for communication, computer and sensor networks. He also works on multi-antenna systems for wireless networks.
He was elected Fellow of Royal Academy of Engineering (2022), IEEE Fellow (2001), member of Academia Europaea (2012), and IET Fellow (2021). He received the Royal Society Wolfson Research Merits Award (2004-09) and the Distinguished Member of Technical Staff Award (1994) from AT&T Bell Labs.  Jointly with his collaborators, he received the IEEE ComSoc Leonard G. Abraham Prize (2021), IEEE ComSoc Best Survey Paper Award (2022), U.S.-UK Science and Technology Stocktake Award (2021), Lanchester Prize Honorable Mention Award (1997), and several best conference paper awards. He currently serves as the IEEE ComSoc Distinguished Lecturer (2022-23). He chaired the IEEE Fellow Evaluation Committee for ComSoc (2012-15) and the Steering Committee for the IEEE Transactions on Mobile Computing (2020-22). He has served as an editor for ten IEEE and ACM journals. Currently, he is an editor for the ACM Computing Survey and International Journal on Sensor Networks.

Speech Title: TBD

Abstract: TBD

Prof. Igor Kotenko, St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS)/ITMO University/ St. Petersburg Bonch-Bruevich State University of Telecommunications, Russia (IEEE/ACM Senior Member)

Biography: Igor Kotenko is a Chief Scientist and Head of Research Laboratory of Computer Security Problems of the St. Petersburg Federal Research Center of the Russian Academy of Sciences. He is also Professor of ITMO University, St. Petersburg, Russia, and Bonch-Bruevich Saint-Petersburg State University of Telecommunications. He is the Honored Scientist of the Russian Federation, IEEE Senior member, member of many Editorial Boards of Russian and International Journals, and the author of more than 800 refereed publications, including 25 books and monographs. Main research results are in artificial intelligence, telecommunication, cyber security, including network intrusion detection, modeling and simulation of network attacks, vulnerability assessment, security information and event management, verification and validation of security policy. Igor Kotenko was a project leader in the research projects from the European Office of Aerospace Research and Development, EU FP7 and FP6 Projects, HP, Intel, F-Secure, Huawei, etc. The research results of Igor Kotenko were tested and implemented in multitude of Russian research and development projects, including grants of Russian Science Foundation, Russian Foundation of Basic Research and multitude of State contracts. He has been a keynote and invited speaker on multitude of international conferences and workshops, as well as chaired many international conferences.

Speech Title: Artificial intelligence for cyber security: key areas of research and development 

Abstract: Artificial intelligence (AI) has become one of the main approaches to processing huge amounts of heterogeneous data and performing various cyber security tasks, including vulnerability management and security assessment, security monitoring, distributed access control. AI is changing the way computers are programmed and how they are used. In cyber security, AI methods provided the opportunity to create advanced cyber security tools, but also allowed attackers to significantly improve the cyber attacks. The evolution of attack and defense tools took place mainly in the form of an arms race, which in its essence was asymmetric and beneficial to attackers. Cybercriminals can launch targeted attacks at unprecedented speed and scale, while bypassing traditional detection mechanisms. The talk shows the current state of AI in cyber security. The key areas of focus at the intersection of AI and cyber security are analyzed: enhancing cyber security with AI, AI for cyber attacks, the vulnerability of AI systems to attacks, and the use of AI in malicious information operations. The own research in the field of intelligent monitoring of cyber security and detection of cyber attacks is presented.

Prof. Haibin Zhu, Nipissing University, Canada (IEEE/ACM Senior Member)

Biography: Dr. Haibin Zhu is a Full Professor and the Coordinator of the Computer Science Program, the Founding Director of the Collaborative Systems Laboratory, a member of Arts and Science Executive Committee, Nipissing University, Canada. He is an affiliate professor of Concordia Univ. and an adjunct professor of Laurentian Univ., Canada. He received his PhD degree in computer science from the National Univ. of Defense Tech. (NUDT), China. He was the chair of the Department of Computer Science and Mathematics, Nipissing University, Canada (2019-2021), a visiting professor and special lecturer in the College of Computing Sciences, New Jersey Institute of Technology, USA (1999-2002) and a lecturer, an associate professor and a full professor at NUDT (1988-2000). He has accomplished (published or in press) over 280+ research works including 46 IEEE Transactions articles, six books, five book chapters, four journal issues, and four conference proceedings. He is a fellow of I2CICC (International Institute of Cognitive Informatics and Cognitive Computing), a senior member of IEEE, a senior member of ACM, a full member of Sigma Xi, and a life member of CAST-USA (Chinese Association of Science and Technology, USA).
He is serving as Vice President, Systems Science and Engineering (SSE) (2023-), a member-at-large of the Board of Governors (2022-), and a co-chair (2006-) of the technical committee of Distributed Intelligent Systems of IEEE Systems, Man and Cybernetics (SMC) Society (SMCS), SMCS Primary Representative, IEEE Systems Council, Editor-in-Chief of IEEE SMC Magazine (2022), Associate Editor (AE) of IEEE Transactions on SMC: Systems (2018-), IEEE Transactions on Computational Social Systems(2018-), Frontiers of Computer Science (2021-), and IEEE Canada Review (2017-). He was AE of IEEE SMC Magazine (2015-2021), Associate Vice President (AVP), SSE (2021), IEEE SMCS, a Conference (Co-)Chair and Program (Co-)Chair for many international conferences, and a PC member for 150+ academic conferences. 
He is the founding researcher of Role-Based Collaboration and the creator of the E-CARGO model. His research monograph E-CARGO and Role-Based Collaboration can be found  https://www.amazon.com/CARGO-Role-Based-Collaboration-Modeling-Problems/dp/1119693063. The accompanying codes can be downloaded from GitHub: https://github.com/haibinnipissing/E-CARGO-Codes. He has offered 30 keynote and plenary speeches for international conferences and 80+ invited talks internationally. His research has been being sponsored by NSERC, IBM, DNDC, DRDC, and OPIC.
He is listed as “Most Influential Robotics Trailblazers, Making Wave in The Industry – 2024”, InsightsSuccess Magazine, the recipient of the best paper award in international collaboration from the 25th Int’l conf. on CSCWD, Hangzhou, China, 2022, the meritorious service award from IEEE SMC Society (2018), the chancellor’s award for excellence in research (2011) and two research achievement awards from Nipissing University (2006, 2012), the IBM Eclipse Innovation Grant Awards (2004, 2005), the Best Paper Award from the 11th ISPE Int’l Conf. on Concurrent Engineering (ISPE/CE2004), the Educator’s Fellowship of OOPSLA’03, a 2nd class National Award for Education Achievement (1997), and three 1st Class Ministerial Research Achievement Awards from China (1997, 1994, and 1991). 
His research interests include Collaboration Systems, Human-Machine Systems, Computational Social Systems, Collective Intelligence, Multi-Agent Systems, Software Engineering, and Distributed Intelligent Systems 

Speech Title: E-CARGO and Role-Based Collaboration

Abstract: Role-Based Collaboration (RBC) is a computational methodology that uses roles as the primary underlying mechanism to facilitate collaboration activities. It consists of a set of concepts, principles, models, processes, and algorithms. 
RBC and its Environments - Classes, Agents, Roles, Groups, and Objects (E-CARGO) model have been developed to a powerful tool for investigating collaboration and complex systems. Related research has brought and will bring in exciting improvements to the development, evaluation, and management of systems including collaboration, services, clouds, productions, and administration systems. RBC and E-CARGO grow gradually into a strong fundamental methodology and model for exploring solutions to problems of complex systems including Collective Intelligence, Sensor Networking, Scheduling, Smart Cities, Internet of Things, Cyber-Physical Systems, and Social Simulation Systems.
E-CARGO assists scientists and engineering to formalize abstract problems, which originally are taken as complex problems, and finally points out solutions to such problems including programming. The E-CARGO model possesses all the preferred properties of a computational model. It has been verified by formalizing and solving significant problems in collaboration and complex systems, e.g., Group Role Assignment (GRA). With the help of E-CARGO, the methodology of RBC can be applied to solve various real-world problems. E-CARGO itself can be extended to formalize abstract problems as innovative investigations in research. On the other hand, the details of each E-CARGO component are still open for renovations for specific fields to make the model easily applied. For example, in programming, we need to specify the primitive elements for each component of E-CARGO. When these primitive elements are well-specified, a new type of modelling/programming language can be developed and applied to solve general problems with software design and implementations. 
In this talk, the speaker examines the requirement of research on collaboration systems and technologies, discusses RBC and its model E-CARGO; reviews the related research achievements on RBC and E-CARGO in the past years; illustrates those problems that have not yet been solved satisfactorily; presents the fundamental methods to conduct research related to RBC and E-CRAGO and discover related problems; and analyzes their connections with other cutting-edge fields. This talk aims at informing that E-CARGO is a well-developed model and has been investigated and applied in many ways. The speaker welcomes queries, reviews, studies, applications, and criticisms.
As case studies of E-CARGO, GRA and its related problem models are inspired by delving into the details of the E-CARGO components and the RBC process. GRA can help solve related collaboration problems with the help of programming and optimization platforms. All the related Java codes can be downloaded by GitHub: https://github.com/haibinnipissing/E-CARGO-Codes. The speaker welcomes interested researchers and practitioners to use these codes in their research and practice and contact the speaker if there are any questions about them.

Prof. Souhail Dhouib, University of Sfax, Tunisa

Biography: Souhail DHOUIB is acting as Full Professor at the University of Sfax(TUNISIA). His teaching and research interests are related to the areas of Computer Science, Decision Science and Management Science. He is the inventor of Dhouib-Matrix philosophical concept which gathers several several optimization methods:1) New heuristics (Dhouib-Matrix-TSP1, Dhouib-Matrix-AP1, Dhouib-Matrix-TP1, ...Etc.),2) Novel metaheuristics (Far-to-Near, Dhouib-Matrix-3, Dhouib-Matrix-4),3) Original optimal methods (Dhouib-Matrix-SPP, Dhouib-Matrix-MST, … Etc.).His publications have appeared in many international journals. He is an Artificial Intelligence developer and an Operations Research analyst. He also acted as an external expert to evaluate research projects for several universities. Hence, he is the former vice president of TORS (Tunisian Operation Research Society) and the former financial director of ATID (Tunisian Association of Engineering Decision). Moreover, he founded two companies specialized in the field of development of business software and he acted as a general manager.  

Speech Title: Innovative method to solve the minimum spanning tree problem: The Dhouib-Matrix-MSTP (DM-MSTP)

Abstract: The Minimum Spanning Tree problem aims to create a subset of a graph where all the vertices are connected with the minimum edge weights and with no cycle. In this field, an innovative method entitled Dhouib-Matrix-MSTP (DM-MSTP) is designed in this research work with a time complexity independently of the number of edges O(n*log(n)) where n is the number of vertices. DM-MSTP is a constructive algorithm based on a matrix navigation with two new lists (Min-Columns and MST-Path) in order to organize the steering flow. DM-MSTP is composed of four simple steps where the first and the fourth steps are repeated only once, whereas the second and third are reiterated (n-1). For more clarification, a step-by-step application of the proposed method is presented in details. Besides, the performance of DM-MSTP is proved through different examples from the literature including a graph with negative weighted edges and complete graphs from TSP-LIB. Moreover, with a simple modification (Min by Max) the DM-MSTP is tested on the Maximum (Largest) Spanning Tree Problem. Also, DM-MSTP is applied on eight case studies and compared to six methods developed in the literature. All these experimental results in the above different environments show that DM-MSTP can rapidly plan the shortest spanning tree with a stable performance and convivial representation of the optimal tree. Hence, DM-MSTP is developed under Python programming language using Matplotlib and Numpy standard libraries.

The Keynot Speaker list above is continuously updated.