Invited Speakers

The speakers of FSDM 2024 are from these countries and areas listed as below:
Dr. T.M.G Ahsanullah, Professor

Dr. T.M.G Ahsanullah, Professor

Department of Mathematics, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
Speech Title: Quantal-valued tolerance structures and some of their applications

Abstract: The idea of tolerance relation attributed to Zeeman is based on two fundamental concepts: reflexivity and symmetric relation. Although tolerance relations are used to study indiscernibility or indistinguishability phenomena, it has wide range of applications; recent trend has witnessed its application in the field of information system and image analysis. We have recently identified tolerance spaces in the context of quantale-valued convergence spaces, showing that the category of quantale-valued tolerance spaces is isomorphic to the category of quantale-valued convergence spaces.
In this talk, we look at function spaces of tolerance spaces and convergence spaces, the role of the degree of transitivity in relation to quantale-valued convergence groups, and their related categorical aspects. Furthermore, we investigate monad and its Eilenberg-Moore category from the perspective of quantale-valued tolerance groups, and convergence groups.
Keywords: Tolerance space, convergence space, probabilistic convergence space, transitive relation, grade of trasitivity, closure operator, function space, group, category theory, monad, Eilenberg-Moore category



Dr. Renying Zeng, Professor

Dr. Renying Zeng, Professor

Key Laboratory of Optimization and Control—Chinese Ministry of Education, China, Chongqing Key Laboratory of Operations Research and System Engineering, China; Saskatchewan Polytechnic, Canada
Speech Title: Proximal Analytic Center Cutting Plane Algorithms for Variational Inequalities and Nash Equilibrium

Abstract: Nash equilibrium is a concept in game theory where the game reaches an optimal outcome. It is a situation in which every player in a competitive game may maximize their result depending on the choices made by the other players. This is a state that gives individual players no incentive to deviate from their initial strategy. The players know their opponent’s strategy and still will not deviate from their initial chosen strategies because it remains the optimal strategy for each player. Someone can receive no incremental benefit from changing actions, assuming that other players remain constant in their strategies. A game may have multiple Nash equilibria or none at all.
Nash equilibrium helps economists understand how decisions that are good for the individual can be terrible for the group.
Nash economic equilibrium itself may not be part of data science. However, it talks about marketing and prices, etc. and does provide big data.
(John Forbes Nash, Jr. (June 13, 1928 – May 23, 2015), known and published as John Nash, was an American mathematician. In 1950, John Nash contributed a remarkable one-page PNAS article that defined and characterized a notion of equilibrium for n-person game. This notion, now called the “Nash equilibrium”. Nash was awarded the 1994 Nobel Prize in Economics.)
Recently, S. Y. Balaman used cutting plane methods to solve problems in management of biomass-based production chains; V. Franc, S. Sonnenburg and T. Werner as well as Y. Makarychev et. al discussed the applications of cutting-plane methods or other iterative algorithms in machine learning; Y. Wang, T. van Bremen, J. Pu, Y. Wang & On. Kuzelka used iterative algorithms in artificial intelligence.
The speaker is the first one to use proximal analytic center cutting plane algorithms to solve Nash equilibrium problems.



Dr. Dimiter Velev, Professor

Dr. Dimiter Velev, Professor

Department of Informatics, University of National and World Economy (UNWE), Sofia, Bulgaria
Speech Title: Challenges of Merging Generative AI with Metaverse for Next-Gen Education

Abstract: The integration of Generative AI with the Metaverse presents a transformative approach to education, which promises to create immersive, personalized learning experiences that transcends the traditional classroom practices. However, this integration also introduces a complex array of challenges that must be addressed to unleash its full potential. The speech explores the different aspects of merging Generative AI with the Metaverse for next-generation education with a focus on technological, pedagogical and ethical aspects.



Dr. Sayan Kaennakham, Associate Professpr

Dr. Sayan Kaennakham, Associate Professpr

Institute of Science, Suranaree University of Technology, Thailand
Speech Title: To be updated

Abstract: To be updated



More speakers will be updated soon...