Keynote Speakers
Keynote Speaker I
Prof. Alex Thomo
University of Victoria, British Columbia, Canada
Title: Mining of Cohesive Groups in Massive Social and Web Graphs
Abstract
Mining dense subgraphs and discovering hierarchical relations between them is a fundamental problem in graph analysis tasks. For instance, it can be used in visualizing complex networks, finding correlated genes and motifs in biological networks, detecting communities in social and web graphs, summarizing text, and revealing new research subjects in citation networks. Core, truss, and nucleus decompositions are popular tools for finding dense subgraphs. A k-core is a maximal subgraph in which each vertex has at least k-neighbors, and a k-truss is a maximal subgraph whose edges are contained in at least k-triangles. Core and truss decompositions have been extensively studied in both deterministic as well as probabilistic graphs. A more recent notion of dense subgraphs is nucleus decomposition which is a generalization of core and truss decompositions that uses higher-order structures to detect dense regions in the graph. In this talk, I will first motivate and illustrate core, truss, and nucleus decompositions for mining dense hierarchical regions in large graphs. Next, I will describe algorithms for computing these decompositions and outline avenues for further research.
Biography
Alex Thomo is a professor of Computer Science at the University of Victoria, British Columbia, Canada. He has over 18 years of research expertise in computer science research and education and is internationally recognized as an expert in Databases, Data Mining, and Distributed Computing. He has authored or co-authored over 100 journal and conference articles. He is Associate Editor of Social Network Analysis and Mining, Springer and has also served as a program committee member for numerous prestigious conferences, including VLDB, SIGKDD, ICDE, CIKM, EDBT, etc. He received the BSc degree from the University of Piraeus, Athens, in 1996, and the MSc and PhD degrees from Concordia University in 2001 and 2003, respectively. His recent research interests include algorithms for big data, large-scale data mining and machine learning, social network analytics, and data privacy.
Keynote Speaker II
Prof. Lidia Dominika Ogiela
AGH University of Science and Technology, Krakow, Poland
Title: Human centered approaches in transformative computing applications
Abstract
Human centered systems are now recognized as one of the most important solutions in artificial intelligence. Their advantage over other results from the fact that they still adapt their operation to changing and unpredictable tasks and functions. The variability of the human analysis process, which is the basis for the operation of such systems, means that the developed IT solutions are constantly evolving, and their development is a determinant of various external factors – independent of humans and those that depend on them. Human centered systems allow for the implementation of tasks of deep, meaningful analysis and interpretation of various data sets. Their special advantage is the possibility of incorporating features characteristic of the human perception processes of automatic data prediction. In human centered systems, transformative computing processes are also carried out, giving the possibility of implementing analysis steps at various levels of inference. The differentiation of the levels, at which the interpretation and inference processes are carried out is characteristic of complex data management structures.
Biography
Lidia Ogiela is a professor at AGH University of Science and Technology in Krakow, Poland. She received Master of Science in mathematics and Master of Business Administration both in 2000. In 2005 she was awarded the title of Doctor of Computer Science and Engineering at the Faculty of Electrical, Automatic Control, Computer Science and Electronic Engineering of the AGH University of Science and Technology, for thesis and research on cognitive informatics and its application in intelligent information systems. In 2016 she received Habilitation in Computer Science at the Faculty of Electrical Engineering and Computer Science at VŠB – Technical University of Ostrava in Czech Republic. In 2018 she received title of Doctor in Computer Science and Telecommunication at Hosei University, in Tokyo, Japan, for thesis and research on human centered computing for future generation computer systems. She is an author of more than 230 scientific international publications on cognitive informatics, information systems, and computational intelligence methods. Author of recognized monographs in the field of cognitive informatics, IT systems and author of a cognitive approaches to knowledge extraction and data analysis. She is a Guest Editor on Concurrency and Computation: Practice and Experience, Cognitive Systems Research, Sensors, Mobile Information Systems, Neural Computing and Applications, and she has also worked as a program committee member 70 international conferences. She received three best paper awards on international conferences and one best presentation award, additionally top cited and top downloads paper awards in 2018-2019 both in Wiley. She is a Member of TOP 2% of scientists in the world 2019, 2020, 2021 by Mendeley Data Citation metrics. She is a Lifetime Fellow Member of prestigious international scientific society SPIE, and member of other societies: IEEE Senior Member, SIAM, ACM, OSA, CSS and Information Processing Society of Japan.