Keynote Speakers

Speaker: Prof. Ljiljana Trajkovic, Simon Fraser University, Burnaby, British Columbia, Canada

Title of Talk: Detecting network anomalies and intrusions

Biography: Ljiljana Trajkovic received the Dipl. Ing. degree from University of Pristina, Yugoslavia, in 1974, the M.Sc. degrees in electrical engineering and computer engineering from Syracuse University, Syracuse, NY, in 1979 and 1981, respectively, and the Ph.D. degree in electrical engineering from University of California at Los Angeles, in 1986.
She is currently a Professor in the School of Engineering Science at Simon Fraser University, Burnaby, British Columbia, Canada. From 1995 to 1997, she was a National Science Foundation (NSF) Visiting Professor in the Electrical Engineering and Computer Sciences Department, University of California, Berkeley. She was a Research Scientist at Bell Communications Research, Morristown, NJ, from 1990 to 1997, and a Member of the Technical Staff at AT&T Bell Laboratories, Murray Hill, NJ, from 1988 to 1990. Her research interests include high-performance communication networks, control of communication systems, computer-aided circuit analysis and design, and theory of nonlinear circuits and dynamical systems.
Dr. Trajkovic serves as IEEE Division X Delegate/Director (2019-2020) and served as IEEE Division X Delegate-Elect/Director-Elect (2018). She served as Senior Past President (2018-2019), Junior Past President (2016-2017), President (2014-2015), President-Elect (2013), Vice President Publications (2012-2013, 2010-2011), Vice President Long-Range Planning and Finance (2008-2009), and a Member at Large of the Board of Governors (2004-2006) of the IEEE Systems, Man, and Cybernetics Society. She served as 2007 President of the IEEE Circuits and Systems Society and a member of its Board of Governors (2004-2005, 2001-2003). She is Chair of the IEEE Circuits and Systems Society joint Chapter of the Vancouver/Victoria Sections. She was Chair of the IEEE Technical Committee on Nonlinear Circuits and Systems (1998). She is General Co-Chair of SMC 2020 and SMC 2020 Workshop on BMI Systems and served as General Co-Chair of SMC 2019 and SMC 2018 Workshops on BMI Systems, SMC 2016, and HPSR 2014, Special Sessions Co-Chair of SMC 2017, Technical Program Chair of SMC 2017 and SMC 2016 Workshops on BMI Systems, Technical Program Co-Chair of ISCAS 2005, and Technical Program Chair and Vice General Co-Chair of ISCAS 2004. She served as an Associate Editor of the IEEE Transactions on Circuits and Systems (Part I) (2004-2005, 1993-1995), the IEEE Transactions on Circuits and Systems (Part II) (2018, 2002-2003, 1999-2001), and the IEEE Circuits and Systems Magazine (2001-2003). She is a Distinguished Lecturer of the IEEE Systems, Man, and Cybernetics Society (2020-2021) and the IEEE Circuits and Systems Society (2010-2011, 2002-2003). She is a Professional Member of IEEE-HKN and a Life Fellow of the IEEE.

Talk description: The Internet, social networks, power grids, gene regulatory networks, neuronal systems, food webs, social systems, and networks emanating from augmented and virtual reality platforms are all examples of complex networks. Collection and analysis of data from these networks is essential for their understanding. Traffic traces collected from various deployed communication networks and the Internet have been used to characterize and model network traffic, analyze network topologies, and classify network anomalies. Data mining and statistical analysis of network data have been employed to determine traffic loads, analyze patterns of users' behavior, and predict future network traffic while spectral graph theory has been applied to analyze network topologies and capture historical trends in their development. Machine learning techniques have proved valuable for predicting anomalous traffic behavior and for classifying anomalies and intrusions in communication networks. Applications of these tools help understand the underlying mechanisms that affect behavior, performance, and security of computer networks.

Speaker: Dr. Juan Manuel Corchado, Director - European IoT Digital Innovation Hub, Director- BISITE Research Group, University of Salamanca & President of the Air Institute, Spain

Title of Talk: Efficient Deployment of DeepTech AI Models in Engineering Solutions

Biography: Juan Manuel Corchado (born May 15, 1971 in Salamanca, Spain). He is Full Professor with Chair at the University of Salamanca. He was Vice President for Research and Technology Transfer from December 2013 to December 2017 and the Director of the Science Park of the University of Salamanca, Director of the Doctoral School of the University until December 2017 and also, he has been elected twice as the Dean of the Faculty of Science at the University of Salamanca. In addition to a PhD in Computer Sciences from the University of Salamanca, he holds a PhD in Artificial Intelligence from the University of the West of Scotland. Juan Manuel Corchado is Visiting Professor at Osaka Institute of Technology since January 2015 and Visiting Professor at the Universiti Malaysia Kelantan.
Corchado is the Director of the European IoT Digital Innovation Hub and of the BISITE (Bioinformatics, Intelligent Systems and Educational Technology) Research Group, which he created in the year 2000, President of the AIR Institute, Academic Director of the Institute of Digital Art and Animation of the University of Salamanca and has been President of the IEEE Systems, Man and Cybernetics Spanish Chapter. He also oversees the Master´s programs in Digital Animation, Security, Blockchain, IoT, Mobile Technology, Information Systems Management and Agile Project Management at the University of Salamanca.
Corchado has supervised more than 25 PhD theses, is author of over 800 research peer review papers and books, has chaired the scientific committee of more than 30 international conferences, and is also Editor-in-Chief of Specialized Journals like ADCAIJ (Advances in Distributed Computing and Artificial Intelligence Journal) and OJCST (Oriental Journal of Computer Science and Technology).

Talk description: Artificial Intelligence revived in the last decade. The need for progress, the growing processing capacity and the low cost of the Cloud have facilitated the development of new, powerful algorithms. The efficiency of these algorithms in Big Data processing, Deep Learning and Convolutional Networks is transforming the way we work and is opening new horizons. Thanks to them, we can now analyse data and obtain unimaginable solutions to today’s problems. Nevertheless, our success is not entirely based on algorithms, it also comes from our ability to follow our “gut” when choosing the best combination of algorithms for an intelligent artefact. It's about approaching engineering with a lot of knowledge and tact. This involves the use of both connectionist and symbolic systems, and of having a full understanding of the algorithms used. Moreover, to address today’s problems we must work with both historical and real-time data. We must fully comprehend the problem, its time evolution, as well as the relevance and implications of each piece of data, etc.It is also important to consider development time, costs and the ability to create systems that will interact with their environment, will connect with the objects that surround them and will manage the data they obtain in a reliable manner.

In this keynote, the evolution of intelligent computer systems will be examined. The need for human capital will be emphasised, as well as the need to follow one’s “gut instinct” in problem-solving. We will look at the benefits of combining information and knowledge to solve complex problems and will examine how knowledge engineering facilitates the integration of different algorithms. Furthermore, we will analyse the importance of complementary technologies such as IoT and Blockchain in the development of intelligent systems.It will be shown how tools like "Deep Intelligence" make it possible to create computer systems efficiently and effectively."Smart" infrastructures need to incorporate all added-valueresources so they can offer useful services to the society, while reducing costs, ensuring reliability and improving the quality of life of the citizens. The combination of AI with IoT and with blockchain offers a world of possibilities and opportunities.

The use of edge platforms or fog computing helps increase efficiency, reduce network latency, improve security and bring intelligence to the edge of the network;close to the sensors, users and to the medium used.

This keynote will present success stories regarding biotechnology, smart cities, industry 4.0, the economy, and others. All these fields require the development of interactive, reliable and secure systems which we are capable of building thanks to current advances.Several use cases of intelligent systems will be presented and it will be analysedhow the different processeshave been optimized by means of tools that facilitate decision-making.

Speaker: Dr. El-Sayed El-Alfy, King Fahd University of Petroleum and Minerals, Saudi Arabia

Title of Talk: Learning from Class-Imbalanced Data: Challenges,Methods and Applications

Biography: El-Sayed M. El-Alfy, Professor King Fahd Univ. of Petroleum and Minerals (KFUPM). He has 25+ years of experience in industry and academia involving research, teaching, supervision, curriculum design, program assessment and quality assurance. He is an active researcher in machine learning and nature-inspired computing and applications to data science and cyber analytics, pattern recognition, multimedia forensics, and security systems. He published numerously in peer-reviewed int’l journals and conferences, edited a number of books, contributed to organization of many int’l conferences, served as guest editor for a number of special issues, and been in editorial board of a number of premium journals including IEEE/CAA Journal of AutomaticaSinica, IEEE Transactions on Neural Networks and Learning Systems, International Journal on Trust Management in Computing and Communications, and Journal of Emerging Technologies in Web Intelligence (JETWI). He co-founded and coordinated a research group on Intelligent Systems at KFUPM. He is a member of IEEE Computational Intelligence Society, and x-member of ACM and IEEE Computer Society. His work has been internationally recognized and received several awards.

Talk description: Nowadays, machine learning and intelligent systems are gaining increasing importance in this era of digital transformation.As more data is generated, the advances in this field present new opportunities in a wide spectrum of domains such as healthcare, finance, social media, cybersecurity, industrial systems, and sensor networks. However, some events or classes are rare and not equally represented in data for many real-world applications. This imposes several challenges for standard machine learning classification algorithms. Though several approaches have been proposed over the past decades, there are open issues that need further investigation. In this talk, we review major research challenges and state-of-the-art solutions with examples for handling imbalanced datasets in order to build more effective models.

Speaker: Dr. Marcin Paprzycki, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

Title of Talk: Towards edge-fog-cloud continuum

Biography: Dr. Marcin PAPRZYCKI has an MS degree from the Adam Mickiewicz University in Pozna?, Poland, a Ph.D. from the Southern Methodist University in Dallas, Texas, USA, and a Doctor of Science degree from the Bulgarian Academy of Sciences, Sofia, Bulgaria. He is a Senior Member of IEEE, a Senior Member of ACM, a Senior Fulbright Lecturer, and was an IEEE CS Distinguished Visitor. His original research interests were in the area of high performance computing / parallel computing / computational mathematics. Over time they shifted towards intelligent systems, software agents and agent systems, and application of semantic technologies, among others. Currently he serves as Vice Chair of the IEEE Poland Section. He has contributed to more than 500 publications, and was invited to the program committees of over 800 international conferences. He is on the editorial boards of 12 journals.

Talk description: Over time, two trends have been observed in the "world of computing". One of them was a push from centralized towards decentralized solutions. The second was the move in the opposite direction. These seem to be similar to the thesis and antithesis in Hegel's philosophy. Interestingly, similarly to Hegel's synthesis, we are approaching a unified model of edge-fog-cloud continuum. My talk will reflect on the journey and outline the proposed way forward.