IFIP CIIA 2018

Title:
Plagiarizing Nature for Engineering Analysis and Design

Abstract:
Systems composed of multiple integrated processors and sensors, with the ability to autonomously satisfy their energy needs and intelligently adapt to their environment are becoming a reality. This example of system complexity brought forth by current technological advances has created analysis and design problems that were either marginal or ignored in the past. Given the increasingly shorter design cycle and lifespan of the end products, the current formal tools for system design and analysis are often overwhelmed by these new problems, when not out of scope. This is not the case in Nature where complex systems are common and have been dealt with successfully by an approach on pragmatism and self-preservation, as opposed to logic and/or analytical models. This very slow process at the human scale has produced remarkable results in Nature, although often offering suboptimal solutions and limited explanatory capacities in comparison to formal approaches. After discussing the limitations of current formal thinking with respect to complexity, the talk with outline today's computational intelligence paradigms, followed by illustrative applications using neural networks, fuzzy logic and evolutionary algorithms.

Short Bio:
Mounir Boukadoum is professor of microelectronics engineering at The University of Quebec at Montreal (UQAM), Canada. He studied physics in Algeria before switching to electrical engineering in the United States, with an emphasis on biomedical applications. He holds a PhD degree in Electrical Engineering degree from The University of Houston, Texas. His current research covers the applications of artificial intelligence and nature-inspired techniques to solve analysis and design problems, particularly in relation to biomedical outcomes. Pr. Boukadoum is currently director of the Design and Fabrication of Microsystems research laboratory at UQAM (COFAMIC), president of the IEEE Computational Intelligence Society's chapter in Montreal and executive member of the Quebec Strategic Alliance for Microsystems research consortium (ReSMIQ). He is an active member of IEEE and member of three IEEE CAS conferences steering committees. He is also a cofounder of the IEEE NEWCAS conference and Co-Chair of the 2018 edition in Montreal.

Title:
Model Based Software Management

Abstract:
Model Driven Engineering (MDE) is becoming a widely accepted paradigm for software development. However, very little has been achieved in software management, like software configuration, dynamic reconfiguration, upgrade, etc. In this presentation we will introduce and discuss the challenges of software configuration, dynamic reconfiguration, upgrade, especially under the constraint of high availability, a common requirement for carrier grade services. We discuss how model driven methods can help in tackling these challenges.

Short Bio:
Ferhat Khendek received his PhD from University of Montreal, Canada. He is a full professor in the department of Electrical and Computer Engineering of Concordia University where he also holds since 2011 the NSERC/Ericsson Senior Industrial Research Chair in Model Based Software Management, a major collaboration between Ericsson and Concordia University. Ferhat Khendek's research interests are in model based software systems engineering and management, formal methods, validation and testing, and service engineering and architectures

Title:
Advanced Technology and Social Media Influence on Research, Industry and Community

Abstract:
The rapid development in technology and social media has gradually shifted the focus in research, industry and community from traditional into dynamic environments where creativity and innovation dominate various aspects of the daily life. This facilitated the automated collection and storage of huge amount of data which is necessary for effective decision making. The value of data is increasingly realized and there is a tremendous need for effective techniques to maintain and handle the collected data starting from storage to processing and analysis leading to knowledge discovery. This talk will focus on techniques and structures which could maximize the benefit from data beyond what is traditionally supported. We emphasize data intensive domains which require developing and utilizing advance computational techniques for informative discoveries. We describe some of our accomplishments, ongoing research and future research plans. The notion of big data will be addressed to show how it is possible to process incrementally available big data using limited computing resources. The benefit of various data mining and network modeling mechanisms for data analysis and prediction will be addressed with emphasize on some practical applications ranging from forums and reviews to social media as effective means for communication, sharing and discussion leading to collaborative decision making and shaping of future plans.

Short Bio:
Reda Alhajj is a professor in the Department of Computer Science at the University of Calgary. He published over 500 papers in refereed international journals, conferences and edited books. He served on the program committee of several international conferences. He is founding editor in chief of the Springer premier journal "Social Networks Analysis and Mining", founding editor-in-chief of Springer Series "Lecture Notes on Social Networks", founding editor-in-chief of Springer journal "Network Modeling Analysis in Health Informatics and Bioinformatics", founding co-editor-in-chief of Springer "Encyclopedia on Social Networks Analysis and Mining", founding steering chair of the flagship conference "IEEE/ACM International Conference on Advances in Social Network Analysis and Mining", and three accompanying symposiums FAB, FOSINT-SI and HI-BI-BI. He is member of the editorial board of the Journal of Information Assurance and Security, Journal of Data Mining and Bioinformatics, Journal of Data Mining, Modeling and Management; he has been guest editor of a number of special issues and edited a number of conference proceedings. Dr. Alhajj's primary work and research interests focus on various aspects of data science and big data with emphasis on areas like: (1) scalable techniques and structures for data management and mining, (2) social network analysis with applications in computational biology and bioinformatics, homeland security, etc., (3) sequence analysis with emphasis on domains like financial, weather, traffic, energy, etc., (4) XML, schema integration and re-engineering. He currently leads a large research group of PhD and MSc candidates. He received best graduate supervision award and community service award at the University of Calgary. He recently mentored a number of successful teams, including SANO who ranked first in the Microsoft Imagine Cup Competition in Canada and received KFC Innovation Award in the World Finals held in Russia, TRAK who ranked in the top 15 teams in the open data analysis competition in Canada, Go2There who ranked first in the Imagine Camp competition organized by Microsoft Canada, Funiverse who ranked first in Microsoft Imagine Cup Competition in Canada.