Invited Speakers

Invited Speaker I

Dr. Chris G. Antonopoulos
University of Essex, UK

Dr. Antonopoulos obtained his BSc in Mathematics from the University of Crete, Greece in 1999. Later that year, he joined the Department of Mathematics at the University of Patras, Greece, where he obtained his MSc degree in Applied Mathematics in 2002 and his PhD in the stability of multi-dimensional Hamiltonian systems in 2007. His PhD work involved analytical and numerical studies on the stability and chaos in Hamiltonian systems of many degrees of freedom and on the transition of said systems from classical to Statistical Mechanics. Dr Antonopoulos is the author of 52 publications in peer reviewed journals, 2 editorials and, has 9 publications in conference proceedings and book chapters. He delivered 55 talks in international conferences, Universities, and academic institutes (18 invited). His h-index is 21 and has 2085 citations to his work (Google Scholar). He has successfully supervised 1 MSc and 1 PhD student and is currently supervising 4 PhD students. He is member of the LMS and IMA mathematical societies. He has also been IMA Representative for the Department of Mathematical Sciences, University of Essex since July 2020.

Speech Title: "Modelling the Brain: From Dynamical Complexity to Neural Synchronisation, Chimera-like States and Information Flow Capacity"

Abstract: In this talk, I will present a review of my recent work on the study of the brain, aiming to reveal relations between neural synchronisation patterns and information flow capacity, namely the largest amount of information per time unit that can be transmitted between different parts of the brain networks considered. I will start by discussing that brains might evolve based on the principle of the maximisation of their internal information flow capacity. In this regard, we have found that synchronous behaviour and information flow capacity of the evolved networks reproduce well the same behaviours observed in the brain dynamical networks of the Caenorhabditis elegans (C. elegans) soil worm and humans. Finally, I will present results on a spectacular neural synchronisation phenomenon observed in modular neural networks such as in the C. elegans brain network, called chimera-like states. I will show that, under some assumptions, neurons of different communities of the brain network of the C. elegans soil worm equipped with HR dynamics are able to synchronise with themselves whereas others, belonging to other communities, remain essentially desynchronised, a situation that changes dynamically in time.

Invited Speaker II

Assist. Prof. Paola Lecca
Free University of Bozen-Bolzano, Italy

Paola Lecca is Assistant Professor at the Faculty of Engineering of the Free University of Bolzano-Bozen (Italy), where she is carrying on her research activity of graph theory, dynamical networks modelling and analysis, statistical inference, parallel computing. Paola Lecca has experience in applying these conceptual and algorithmic tools to bioinformatics and computational biology. She is also carrying on an intense activity at the Smart Data Factory (SDF), the Technology Transfer Laboratory of the Computer Science Competences of the Faculty of Engineering of the Free University of Bozen-Bolzano. The SDF Laboratory works to promote knowledge and technology from the academic world to the industrial world. Paola Lecca is Senior Professional Member of Association for Computing Machinery, New York USA, where she contributes to the development and dissemination of artificial intelligence techniques and numerical methods for high performing software for complex dynamical network simulation. Paola Lecca is also member of the advisory board of the AIR Institute (International Research Institute Foundation for Artificial Intelligence and Computer), Salamanca Spain, and is author of more than one hundred publications in the field of biophysics, computational biology, applied mathematics and applied physics.

Speech Title: "The Determination of the Latent Geometry of a Network and its Structural and Dynamical Implications"

Abstract: A network represented by a graph is typically a finite metric space where distance is determined by the number of edges of the shortest route between two nodes in mathematical models and their real-world applications. This might not, however, be the geometry of the hidden metric space that underlies how the network structure is organized and how its dynamics evolves. When modelling processes, it's common to impose one geometry on the network without taking into account the possibility that the network may have a different one defined by the node and edge properties, which, respectively, represent the actors and the relationships between them in the physical processes of which the network is a model. Determining a network's actual geometry and using that geometry to create an accurate model of the network's static and dynamic properties are therefore crucial. With this as my inspiration, I present and discuss techniques to determine whether a network's latent geometry is curved or flat, and I will highlight the static and dynamic properties that result from the different geometries. I will refer to examples taken from biological networks.

Invited Speaker III

Assoc. Prof. S. Joseph Antony
University of Leeds, UK

Dr S. Joseph Antony is an Associate Professor at the School of Chemical and Process Engineering, University of Leeds, U.K. His research expertise is in the area multi-scale modelling and experimental mechanics of materials in both discrete and continuum form. He has a strong expertise in materials modelling including MD, DEM, FEM and analytical methods. His experimental approaches include a wide variety of advanced characterising and stress sensor techniques including photonics (PSA), AFM, SEM, PSAT and IR tomography, and DPIV. He focuses on linking the effects of material properties at exceedingly small scales (molecular/nano/micro) to bulk scale mechanical, electrical and chemo-mechanical properties in a wide variety of engineering applications. Joseph has published over 150 papers in several reputed international journals and conference proceedings. He actively participates in the activities of particle technology community in U.K and abroad. He has won many awards, including the prestigious M.I.T Young Research Fellowship for Exemplary Research in Computational Mechanics and the Certificate of Merit as an Example of Outstanding Achievements in U.K Particle Science and Technology in 2002, PTSG, IChemE, U.K. He has served as a guest editor for the Jl. Granular Matter and the lead editor of the book ‘Granular Materials: Fundamentals and Applications’, published by the Royal Society of Chemistry, London in 2004. His research sponsors include EPSRC, Royal Society, DTI, ICI, BNFL, P&G, Pfizer, Borax Hosakawa Micron, Bridon International Ltd, Merck Sharp & Dohme and DuPont (U.K). More details on his research activities can be found in:

Speech Title: "Modelling the Spread of COVID-19 and its Impacts on the Construction Industry"

Abstract: During Covid-19, governments implemented measures to control the spread, safeguard public health, and prevent overwhelming healthcare systems. The spread control measures necessitated significant modifications in different economic sectors during the health emergency. Additionally, considerable public funds were directed towards supporting hospitals, businesses and households to resist the outbreak and its negative impacts. The construction industry, crucial for the global economy, declined during the initial stages of Covid-19. Project delays and cancellations were prevalent, and the industry required public financial support to address the challenges. As we transition into the post-pandemic period, it is imperative to draw upon the lessons learned from the Covid-19 crisis to effectively manage disruptions in the construction industry during potentially similar pandemics in future. In this study, we present a numerical framework aimed at safeguarding the economic stability of the construction industry in the face of extraordinary events, such as Covid-19. By identifying the causal epidemiological and financial factors that influenced the construction industry during the pandemic, we examine relevant information to model the extent to which spread control measures, government support, and macroeconomic instruments impacted the industry from the initial outbreak until the conclusion of the pandemic.


Previous Keynote Speakers

ASA Fellow, Prof. Ding-Geng Chen
University of North Carolina-Chapel Hill, USA

Professor (Din) Ding-Geng Chen is an elected fellow of the American Statistical Association (ASA) and an elected member of the International Statistics Institute (ISI). He is currently the executive director and professor in biostatistics at the College of Health Solutions, Arizona State University, USA. He is also the South Africa Research Chair Initiatives (SARChI) Tier-1 research chair in biostatistics established by the Department of Science and Technology (DST), National Research Foundation (NRF), and South Africa Medical Research Council (SAMRC), to lead the research, development and capacity building in biostatistics across Africa, an extraordinary professor at the Department of Statistics, University of Pretoria, South Africa, and an honorary professor at the School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, South Africa. Professor Chen served as a distinguished professor in biostatistics at the University of North Carolina-Chapel Hill, a biostatistics professor at the University of Rochester Medical Center, the Karl E. Peace endowed eminent scholar chair in biostatistics from the Jiann-Ping Hsu College of Public Health at the Georgia Southern University, and a professor in biostatistics at the South Dakota State University. His research has been funded by NIH/NSF with more than 200 professional publications and 33 co-authored/co-edited books on biostatistics clinical trials, biopharmaceutical statistics, interval-censored survival data analysis, meta-analysis, public health statistics, statistical causal inferences, statistical methods in big-data sciences, and Monte-Carlo simulation-based statistical modeling. He has been invited internationally to give scientific speeches, short courses, and tutorials at various scientific conferences.

Prof. Carlos A. Coelho
NOVA University of Lisbon, Portugal

Carlos A. Coelho is a Full Professor of Statistics at the Mathematics Department of Faculdade de Ciências e Tecnologia of NOVA University of Lisbon. He holds a Ph.D. in Biostatistics by The University of Michigan, Ann Arbor, MI, U.S.A., and his main areas of research are Mathematical Statistics and Distribution Theory, namely the derivation of Likelihood Ratio Tests for elaborate structures of covariance matrices and for MANOVA-like models under the assumption of elaborate covariance structures, as well as the study and development of exact and near-exact distributions for these and other likelihood ratio test statistics used in Multivariate Analysis. Other areas of interest are Estimation, Univariate and Multivariate Linear, Generalized Linear and Mixed Models, etc. Carlos A. Coelho is an Elected Member of the International Statistical Institute and has served as Associate Editor in the Editorial Boards of REVSTAT and Journal of Interdisciplinary Mathematics and currently serves in the Editorial Boards of Journal of Applied Statistics, Journal of Statistical Theory and Practice, American Journal of Mathematical and Management Sciences and Discussiones Mathematicae-Probability and Statistics and is Associate Editor of the Springer Book series “Emerging Topics in Statistics and Biostatistics”. Carlos A. Coelho, a Fulbrighter, is also vice-president of Fulbrighters Portugal – the Portuguese Fulbright Alumni Association.