Keynote Speakers(Alphabetize by Last Name)

Prof. Mohamed-Slim Alouini

King Abdullah University of Science and Technology (KAUST), Saudi Arabia

IEEE Fellow


Mohamed-Slim Alouini was born in Tunis, Tunisia. He received the Ph.D. degree in Electrical Engineering from the California Institute of Technology (Caltech) in 1998. He served as a faculty member at the University of Minnesota then in the Texas A&M University at Qatar before joining in 2009 the King Abdullah University of Science and Technology (KAUST) where he is now the Al-Khawarizmi Distinguished Professor of Electrical and Computer Engineering. Prof. Alouini is a Fellow of the IEEE and OPTICA (Formerly the Optical Society of America (OSA)). He is currently particularly interested in addressing the technical challenges associated with the uneven distribution, access to, and use of information and communication technologies in rural, low-income, disaster, and/or hard-to-reach areas.
Title: Towards Connecting the Remaining 3+ Billion

Prof. Wanyang Dai

Nanjing University, China


Wanyang Dai is a Distinguished Professor in Mathematics Department of Nanjing University, Chief Scientist at Su Xia Control Technology, President and CEO of U.S. based (blochchain and quantum computing) SIR Forum (Industial 6.0 Forum), a Special Guest Expert in Jiangsu FinTech Research Center, President of Jiangsu Probability & Statistics Society, Chairman of Jiangsu Big Data-Blockchain and Smart Information Special Committee, Chief Scientist at Depths Digital Economy Research Institute, and Editor-in-Chief of Journal of Advances in Applied Mathematics, where his research includes stochastic processes related optimization and optimal control, admission/scheduling/routing protocols and performance analysis/optimization for various projects in BigData-Blockchain oriented quantum-cloud computing and the next generation of wireless and wireline communication systems, forward/backward stochastic (ordinary/partial) differential equations and their applications to queueing systems, stochastic differential games, communication networks, Internet of Things, financial engineering, energy and power engineering, etc. His “influential” achievements are published in “big name” journals including Quantum Information Processing, Operational Research, Operations Research, Computers & Mathematics with Applications, Communications in Mathematical Sciences, Journal of Computational and Applied Mathematics, Queueing Systems, Mathematical and Computer Modeling of Dynamical Systems, etc. His researches are awarded as outstanding papers by various academic societies, e.g., IEEE Top Conference Series, etc.. He received his Ph.D degree in applied mathematics jointly with industrial engineering and systems engineering from Georgia Institute of Technology, Atlanta, GA, U.S.A., in 1996, where he worked on stochastics and applied probability concerning network performance modeling and analysis, algorithm design and implementation via stochastic diffusion approximation. The breakthrough results and methodologies developed in his thesis were cited, used, and claimed as “contemporaneous and independent” achievements by some other subsequent breakthrough papers that were presented as “45 minute invited talk in probability and statistics” in International Congress of Mathematicians (ICM) 1998, which is the most privilege honor in the mathematical society. The designed finite element-Galerkin algorithm to compute the stationary distributions of reflecting Brownian motions (weak solutions of general dimensional partial differential equations) is also well-known to the related fields.

Prof. Zhu Han

University of Houston, USA

IEEE Fellow, AAAS Fellow


Zhu Han received the B.S. degree in electronic engineering from Tsinghua University, in 1997, and the M.S. and Ph.D. degrees in electrical and computer engineering from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2002, he was an R&D Engineer of JDSU, Germantown, Maryland. From 2003 to 2006, he was a Research Associate at the University of Maryland. From 2006 to 2008, he was an assistant professor at Boise State University, Idaho. Currently, he is a John and Rebecca Moores Professor in the Electrical and Computer Engineering Department as well as the Computer Science Department at the University of Houston, Texas. Dr. Han is an NSF CAREER award recipient of 2010, and the winner of the 2021 IEEE Kiyo Tomiyasu Award. He has been an IEEE fellow since 2014, an AAAS fellow since 2020, an IEEE Distinguished Lecturer from 2015 to 2018, and an ACM Distinguished Speaker from 2022-2025. Dr. Han is also a 1% highly cited researcher since 2017.

Prof. Ljiljana Trajkovic

Simon Fraser University, Canada

IEEE Fellow


Ljiljana Trajkovic received the Dipl. Ing. degree from University of Pristina, Yugoslavia, the M.Sc. degrees in electrical engineering and computer engineering from Syracuse University, Syracuse, NY, and the Ph.D. degree in electrical engineering from University of California at Los Angeles. She is currently a professor in the School of Engineering Science, Simon Fraser University, Burnaby, British Columbia, Canada. Her research interests include communication networks and dynamical systems. She served as IEEE Division X Delegate/Director, President of the IEEE Systems, Man, and Cybernetics Society, and President of the IEEE Circuits and Systems Society. Dr. Trajkovic serves as Editor-in-Chief of the IEEE Transactions on Human-Machine Systems and Associate Editor-in-Chief of the IEEE Open Journal of Systems Engineering. She served as a Distinguished Lecturer of the IEEE Circuits and System Society and a Distinguished Lecturer of the IEEE Systems, Man, and Cybernetics Society. She is a Fellow of the IEEE.
Title: Machine Learning for Detecting Internet Traffic Anomalies
Abstract: Border Gateway Protocol (BGP) enables the Internet data routing. BGP anomalies may affect the Internet connectivity and cause routing disconnections, route flaps, and oscillations. Hence, detection of anomalous BGP routing dynamics is a topic of great interest in cybersecurity. Various anomaly and intrusion detection approaches based on machine learning have been employed to analyze BGP update messages collected from RIPE and Route Views collection sites. Survey of supervised and semi-supervised machine learning algorithms for detecting BGP anomalies and intrusions is presented. Deep learning, broad learning, gradient boosting decision tree, and reservoir computing algorithms are evaluated by developing models based on collected datasets that contain Internet worms, power outages, and ransomware events.

Prof. Ming Xie

Nanyang Technological University, Singapore

Associate Editor of IEEE Transaction on Autonomous Mental Development


Xie Ming is holding the positions of Associate Professor at Nanyang Technological University, Editor-in-Chief of International Journal of Humanoid Robotics (Indexed by SCI/SCIE), Associate Editor of IEEE Transaction on Autonomous Mental Development, and Director of private companies. He has served as technical consultants to Asia Electronics Pte Ltd in 1994, Port of Singapore Authority in 1994, Delphi Automotive Systems Pte Ltd in 2001, ST Aerospace Ltd in 2006, Murata Electronics Pte Ltd in 2007, and Sony Electronics Pte Ltd in 2007. He has also worked with Renault Automation (Paris/France) in 1986, INRIA Sophia-Antipolis (Nice/France) between 1990 and 1993, and Singapore-MIT Alliance between 2000 and 2004. In addition, Xie Ming has served as the General Chair of International Conference on Climbing and Walking Robots in 2007, and International Conference on Intelligent Robotics and Applications in 2009. Xie Ming obtained his B.Eng in control and automation in 1984. At the same year, he was selected as one of Chinese government’s overseas scholars. Thereafter, he obtained the Master degree in industrial automation from the University of Valenciennes (France) in 1986, and the Ph.D degree in informatics from the University of Rennes (France) in 1989. He has published one best-selling book in robotics in 2003, and over 100 research papers so far. Xie Ming has taught a number of university courses such as Applied Machine Vision, Robotics, Computer Graphics, Statistical Process Control, and Physics. Xie Ming’s research strengths are in machine intelligence, humanoid robotics and autonomous vehicles. In total, he has won two scientific competition awards, and two best conference paper awards.
Title: Key Steps Toward Development of Humanoid Robots
Abstract: Humanoid robots are biped walking robots which are similar to human beings. As a result, the public has a lot of interests in seeing the advances in the development of humanoid robotics. So far, the most impressive versions of humanoid robots are Honda’s ASIMO, Sony’s QRIO, KAIST’s HUBO, and Boston Dynamics’s Atlas. The new addition to the list is expected to be Tesla’s humanoid robots. Therefore, it would be interesting for us to share our experiences gained from the development of Singapore’s humanoid robots since 2008. In this talk, I will adopt a pedagogic way of outlining the key steps toward the development of advanced humanoid robots. Particularly, I will explain the details from the viewpoints of energy flow, signal flow, motion flow, and knowledge flow inside humanoid robots.

Prof. Xi Zhang

Texas A&M University, College Station, USA

IEEE Fellow


Xi Zhang received his Ph.D. degree in Electrical Engineering and Computer Science (Electrical Engi-neering-Systems) from The University of Michigan, Ann Arbor, MI, USA. He is currently a Full Professor and the Founding Director of the Networking and Information Systems Laboratory, Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA. He is an IEEE Fellow for contributions to statistical quality of services (QoS) theory in mobile wireless networks. Professor Zhang has published more than 400 research articles. He received the U.S. National Science Foundation CAREER Award in 2004 and six IEEE Best Paper Awards from IEEE flagship conferences. One of his IEEE Journal on Selected Areas in Communications papers has been listed as the IEEE Best Readings Paper. He is an IEEE Distinguished Lecturer for both IEEE ComSoc and IEEE VTC. He is serving and has served as Editors for a large number of IEEE Transactions and Journals and as General and TPC Chairs for numerous IEEE Conferences and Symposia.

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