AINA-2024-1AINA-2024-2AINA-2024-3


Keynotes

1st | 2nd


Prof. Fatos Xhafa

Department of Computer Science, Universitat Polit├Ęcnica de Catalunya (UPC), Barcelona, Spain
 

Agile Edge: Harnessing the Power of the Intelligent Edge by Agile Optimization

The Digital Cloud Ecosystem comprises various degrees of computing granularity from large Cloud servers and Data Centers to IoT devices, leading to the Cloud-to-thing continuum computing paradigm. In this context, the Intelligent Edge aims at placing intelligence to the end devices, at the edges of the Internet. The premise is that collective intelligence from the IoT data deluge can be achieved and used at the edges of the Internet, offloading the computation burden from the Cloud systems and leveraging real time intelligence. This, however, comes with the challenges of processing and analyzing the IoT data streams in real time. In this talk, we will address how agile optimization can be useful to harnessing the power of the intelligent edge. Agile optimization is a powerful and promising solution, which differently from traditional optimization methods, is able to find optimized and scalable solutions under real-time requirements. We will bring real-life problems and case studies from Smart City Open Data Repositories to illustrate the approach. Research challenges and emerging vision on the agile intelligent edge will be discussed.


Biography of Fatos Xhafa

Fatos Xhafa , PhD in Computer Science, is Full Professor at the Technical University of Catalonia (UPC), Barcelona, Spain. He has held various tenured and visiting professorship positions. He was a Visiting Professor at the University of Surrey, UK (2019/2020), Visiting Professor at the Birkbeck College, University of London, UK (2009/2010) and a Research Associate at Drexel University, Philadelphia, USA (2004/2005). Prof. Xhafa has widely published in peer reviewed international journals, conferences/workshops, book chapters, edited books and proceedings in the field (H-index 61). Prof. Xhafa has an extensive editorial service. He is founder and Editor-In-Chief of Internet of Things - Journal - Elsevier (Scopus and Clarivate WoS Science Citation Index) and of International Journal of Grid and Utility Computing, (Emerging Sources Citation Index), and AE/EB Member of several indexed Int'l Journals. Prof. Xhafa is a member of IEEE Communications Society, IEEE Systems, Man & Cybernetics Society and Founder Member of Emerging Technical Subcommittee of Internet of Things. His research interests include IoT and Cloud-to-thing continuum computing, massive data processing and collective intelligence, optimization, security and trustworthy computing and machine learning, among others. He can be reached at fatos@cs.upc.edu. Please visit also http://www.cs.upc.edu/~fatos/ and at http://dblp.uni-trier.de/pers/hd/x/Xhafa:Fatos

 

Juggapong Natwichai

Faculty of Engineering, Chiang Mai University, Thailand
 

Challenges in Entity Matching in AI Era

Entity Matching (EM) is to identify and link entities originating from various sources that correspond to identical real-world entities, thereby constituting a foundational component within the realm of data integration. For example, in order to counter-fraud detection, the datasets from sellers, financial services providers, or even IT infrastructure service providers might be in need for data integration, and hence, the EM is highly important here. This matching process is also recognized for its pivotal role in data augmenting to improve the precision and dependability of subsequent tasks within the domain of data analytics. Traditionally, the EM procedure composes of two integral phases, namely, blocking and matching. The blocking phase associates with the generation of candidate pairs, and could affect the size and complexity of the data. Meanwhile, the matching phase will need to trade-off between the accuracy and the efficiency. In this talk, the challenges of both components are thoroughly explored, particularly with the aids of AI techniques. In addition, the preliminary experiment results to explore some important factors which affect the performance are to be presented.


Biography of Juggapong Natwicha

Dr. Juggapong Natwichai is an Associate Professor at the Department of Computer Engineering, Faculty of Engineering, Chiang Mai University, Thailand. He received his BEng in Computer Engineering from Chiang Mai University in 1999, and his Ph.D. in Computer Science from The University of Queensland in 2007. At the moment, he serves as the IT Director and Data Science Consortium Chairman of Chiang Mai University. His research interests include privacy preservation, and database systems.