AMMS

Dr. Gökhan Yıldırım is a faculty member at Bilkent University, Ankara, Türkiye. He earned his PhD in Applied Mathematics from the University of Southern California, USA. His research spans enumerative combinatorics, probability, statistical physics, and data science. Dr. Yıldırım has contributed to numerous collaborative research projects and published in prestigious peer-reviewed international journals, including Advances in Applied Mathematics, Nature Physics, Electronic Journal of Probability, and Electronic Journal of Combinatorics. His findings have been presented at leading international conferences and meetings worldwide. In addition to his research, Dr. Yıldırım is an experienced educator, regularly teaching courses in probability, statistics, discrete mathematics, and data science. He has also served on editorial and review boards of scientific journals and actively participated in program committees of international conferences.

Speech Title: "Sampling from Discrete Combinatorial Structures: Algorithms, Challenges, and Open Questions"

Abstract: Understanding the structure and properties of discrete combinatorial objects, such as pattern-avoiding permutations and inversion sequences, is a fundamental problem with applications across mathematics, statistical physics, and computer science. In this talk, I will explore sampling algorithms designed to efficiently generate these complex structures. Special emphasis will be placed on Markov Chain Monte Carlo (MCMC) methods, which have become indispensable tools for approximate sampling in high-dimensional combinatorial spaces. I will discuss the strengths and limitations of these algorithms, highlighting recent advancements and illustrating their practical performance. Additionally, several open questions will be presented, offering insight into ongoing challenges in the field and potential directions for future research. This talk aims to provide an accessible overview of the theoretical underpinnings, computational techniques, and open problems related to sampling from discrete combinatorial structures.

 

Dr Chris G. Antonopoulos
University of Essex, UK

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

Paola Lecca is a theoretical physicist with a PhD in Computer Science and Telecommunication. Dr. Lecca is Assistant Professor at the Faculty of Engineering of the Free University of Bozen-Bolzano (Italy), where she carries out research activities in the fields of graph theory, modelling and analysis of dynamic networks, statistical inference, parallel computing, mainly in the application domains of bioinformatics, computational biology, biophysics and drug development. Dr. Lecca’s interests and scientific contributions relate to the mathematical foundations of data analysis, artificial intelligence and modelling techniques for complex systems that can be represented as networks of dynamic interactions. A member of various national and international scientific associations, Paola Lecca has also authored over a hundred articles in international scientific journals and conference proceedings in computational biology, biophysics and applied mathematics.

Speech Title: "The Bayesian basis of Decision-Making in Artificial Intelligence: Does It Help to Determine the Level of Confidence in Artificial Intelligence Results?"

Abstract: Artificial Intelligence systems can explicitly model uncertainty thanks to Bayesian statistics. Bayesian models produce a probability distribution over potential outcomes rather than a single deterministic output. By capturing the inherent uncertainty in data and model projections, this probabilistic approach facilitates risk assessment and well-informed decision-making. Furthermore, Bayesian decision theory provides a structured framework for making optimal decisions under uncertainty. However, the uncertainty in the prior probability function and background knowledge cannot be handled or represented generally by the Bayesian approach. This is a significant theoretical and practical drawback of Bayesianism. These limitations of the Bayesian approach will be presented and discussed in the talk and some perspectives will be given on the need to go beyond traditional Bayesianism.

Assoc. Prof. Ahmad Lutfi Amri Ramli
Universiti Sains Malaysia, Malaysia

Assoc. Prof. Dr. Ahmad Lutfi Amri Ramli is an esteemed academic at the School of Mathematical Sciences, Universiti Sains Malaysia (USM). He holds a PhD from Durham University, an MSc from Brunel University, and a BSc in Mathematics from USM. Dr. Lutfi’s research expertise lies in applied mathematics, with a focus on motion planning for robots integrating the knowledge from computer aided geometrical design, curve and surface modelling, and computational methods. His interest also extends to gamification in education, leveraging innovative approaches to enhance student engagement in mathematical learning As an academic leader and researcher, Dr. Lutfi has been actively involved in advancing research, fostering student development, and innovating teaching practices, contributing to the growth of mathematics and applied sciences.

Speech Title: "CAGD and Its Application in Transportation Research"

CAGD is used in transportation research for road design, vehicle trajectory planning, speed estimation, and optimizing autonomous navigation paths. It also enables the creation of smooth and efficient road alignments while ensuring safety and comfort. This talk will highlight a few key applications, such as safe speed estimation using parametric curves derived from GPS data and travel time prediction based on circular arc curvature to estimate speed from road geometry. These techniques provide valuable insights for traffic management and infrastructure development. By applying CAGD techniques, transportation research can leverage mathematical models to improve accuracy while reducing costs.

 

 

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.

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.

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: http://www.spanglefish.com/drsjosephantony/.