Keynote Speakers

Bin Jiang

Computing the structural beauty that exists in the underlying living structure of space or big data

Living structure is a physical phenomenon that exists pervasively in our surroundings or in any part of space. Mathematically it is defined as a structure that consists of numerous substructures with an inherent hierarchy. Across different levels of the hierarchy there are far more small substructures than large ones, whereas on each level of the hierarchy substructures are more or less similar. Living structure is to beauty what temperature is to warmth. Through the underlying living structure, the livingness of space (L) or structural beauty can be measured by the number of substructures (S) and their inherent hierarchy (H), that is, L = S * H. This formula implies that the more substructures the more living or more structurally beautiful, and the higher hierarchy of the substructures, the more living or more structurally beautiful.

In this presentation, I will begin with an introduction to the scientific maverick Christopher Alexander (1936–2022), who devoted his entire life to establishing a scientific foundation of architecture on living structure and on the third view of space: space is neither lifeless nor neutral but a living structure capable of being more living or less living. I will defend his argument that the statement of good architecture is true or false rather than only a matter of opinion. I will present the computation of structural beauty of space through paintings, building facades, city plans, nighttime imagery, and ordinary images or big data in general. In the end I will discuss implications of structural beauty in terms of mechanical and organic world views, effect of living structure on human emotional well-being and healing, and even relationship between mind and matter.

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http://giscience.hig.se/binjiang/
Dr. Bin Jiang is Professor of GeoInformatics at the University of Gävle, Sweden. His research interests center on geospatial analysis and modeling, for example, topological analysis and scaling hierarchy applied to buildings, streets, and cities, or geospatial big data in general. Over the past years, he has developed a series of novel concepts, methods, and tools, which are all complexity science oriented, such as natural cities, natural streets, head/tail breaks, ht-index, and scaling law, not only for better understanding city structure and dynamics, but also for effectively transforming cities and communities to become living or more living. He formulated three fundamental issues of urban science about a city: how it looks, how it works, and what it ought to be. In other words, urban science should study not only how cities are, but also – probably more importantly – what cities ought to be, that is, urban planning and design towards a sustainable society. Inspired by the great architect Christopher Alexander, he developed a mathematical model of beauty – or beautimeter – which helps address not only why a city is beautiful, but also how beautiful the city is. He is the primary developer of the software tool Axwoman for topological analysis of very large street networks. He is the founding chair of the International Cartographic Association (ICA) Commission on Geospatial Analysis and Modeling, and co-founding chair of ICA Working Group on Digital Transformation. He used to be Associate Editor of the international journal Computer, Environment and Urban Systems (2009–2014), and is currently Associate Editor of some international journals such as Cartographica, and Computational Urban Science.

 


D. Frank Hsu

Combinatorial Fusion: Ranking and Scoring for Computational Learning and Modeling

Ranking and rank aggregation have been widely used in science, technology, engineering, society, and cyberspace. However, they are relatively less considered in computational learning and modeling due to insufficient knowledge about the structure of the rank space and the representation of ranking, in particular rankings with ties.

In this presentation, I will cover the following. 

Combinatorial fusion algorithm (CFA), with the rank-score characteristic (RSC) function (Hsu, Shapiro, and Taksa; DIMACS TR-80, 2002), which considers both score and rank

Applications of CFA to a variety of domains including biomedicine, virtual screening with drug discovery, target tracking, wireless network selection, cognitive neuroscience, and business analytics

Discussion of the Kemeny rank space as a viable information geometry for multi-layer combinatorial fusion (MCF), including model fusion of multiple ML/AI models, and deep reinforcement learning

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D. Frank Hsu is Clavius Distinguished Professor of Science and Professor of Computer and Information Science at Fordham University, New York, NY. He was visiting faculty/scholar at Keio University (as IBM Chair Professor) and JAIST (as Komatsu Chair Professor) (Tokyo and Kanazawa, Japan), MIT (Cambridge, MA), Taiwan University (Taipei, Taiwan), and University of Paris-Sud and CNRS (Paris, France). Hsu's research interests include: combinatorics and graph theory, network interconnection and communications, combinatorial fusion and information geometry, and computational learning and modeling (including ML/AI). He is a frequent speaker on these subjects and has given over 450 presentations. He has published 40 books or book chapters, edited/coedited 27 special issues in conference proceedings, and over 200 papers in journals and conferences. He has served on many editorial boards. Currently he is on the editorial board of: Cyber Security: A Peer-Reviewed Journal (Henry Steward Publications); Health Information Science Book Series (Springer); Journal of Advanced Mathematics and Applications (American Scientific Publisher); and Journal of Interconnection Networks (World Scientific Publishing). Hsu received his B.S. from Cheng Kung University (Tainan, Taiwan), M.S. from the University of Texas at El Paso (El Paso, Texas), and Ph.D. from the University of Michigan (Ann Arbor, MI). Among the honors he received are: Foundation Fellow (Institute of Combinatorics and Applications), Fellow (New York Academy of Sciences), Fellow (Institute of Cognitive Informatics and Cognitive Computing), IBM Faculty Award, and Gold Nugget Award (UTEP and College of Science). He is a Senior member of the IEEE.

 


Prof. Javier Lopez

Digital Twin: double insecurity?

Industry 4.0 is having an increasingly positive impact on the value chain by modernizing and optimizing the production and distribution processes. Digital twin (DT) is one of most cutting-edge technologies, providing simulation capabilities to forecast, optimize and estimate states and configurations. These technological capabilities are encouraging industrial stakeholders to invest in the new paradigm. However, an increased focus on the risks involved is really needed before further progressing. The reason is that the deployment of a DT, which is based on a confluence of technologies (IIoT, edge computing, AI, big data, etc.), together with the implicit interaction with the physical counterpart in the real world may generate multiple and unexpected security threats. In this talk, we will analyse that particular DT context and the potential associated threats, and will also present some security recommendations to improve trustworthiness on this new technology.

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https://www.nics.uma.es/jlm
Javier Lopez is a Full Professor at the University of Malaga and Head on NICS Lab research group. His research activities mainly focus on network security, security protocols and critical information infrastructures protection. He has published about one hundred research papers in journals with impact factor. As Head of NICS Lab he has lead more than 50 research projects, among then over a dozen funded by the European Commissio, and has been (co)supervisor of 17 PhD thesis. Actually, he is President of the Spanish Excellence Network on Cybersecurity (RENIC), and President of the Spanish standardization subcommittee on Data Protection, Privacy and Identity Management (UNE CTN320/SC5). He is a member of the Editorial Boards of, amongst others, IEEE Wireless Communications, IEEE Trans on Dependable and Secure Computing, Computers & Security, and Journal of Computer Security, and has been Co-Editor in Chief of International Journal of Information Security (2004-2021). In the past he was member of the international Cybersecurity Advisory Board of HUWAEI (2015-2019), as well as the Spanish representative in the IFIP Technical Committee on Security and Privacy (2003-2018). Also was Chair of the ERCIM Working Group on Security and Trust Management (2009-2012) and Chair of the IFIP Working Group 11.11 on Trust Management (2006-2009).

Prof. Panos Pardalos

Computational approaches for solving systems of nonlinear equations

Finding one or more solutions to a system of nonlinear equations (SNE) is a computationally hard problem with many applications in sciences and engineering.First, we will briefly discuss classical approaches for addressing (SNE). Then, we will discuss the various ways that a SNE can be transformed
into an optimization problem, and we will introduce techniques that can be utilized to search for solutions to the global optimization problem that arises when the most common reformulation is performed. In addition, we will present computational results using different heuristics. 



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www.ise.ufl.edu/pardalos
Panos Pardalos is Distinguished emeritus professor at the Department of Industrial and Systems Engeneering, Univeristy of Floriada.
Panos was born in Drosato (Mezilo) Argitheas in 1954 and graduated from Athens University (Department of Mathematics). He received his PhD (Computer and Information Sciences) from the University of Minnesota. He is a Distinguished Emeritus Professor in the Department of Industrial and Systems Engineering at the University of Florida, and an affiliated faculty of Biomedical Engineering and Computer Science & Information & Engineering departments. Panos Pardalos is a world-renowned leader in Global Optimization, Mathematical Modeling, Energy Systems, Financial applications, and Data Sciences. He published over 600 journal papers, and edited/authored over 200 books. He is one of the most cited authors and has supervised 71 PhD students. He is an editor in chief of numerous journals. He received numerous prizes and awards among which the prestigious Humboldt Research Award (2018-2019). The Humboldt Research Award is granted in recognition of a researcher’s entire achievements to date fundamental discoveries, new theories, insights that have had significant impact on their discipline.