Invited Speakers


Assoc. Prof. Adelaide Freitas
University of Aveiro, Portugal

Adelaide Freitas has a bachelor's degree in Mathematics (University of Aveiro, UA), a master's degree in Probability and Statistics (University of Lisbon) and a PhD in Mathematics (UA). She is currently an Associate Professor in the Department of Mathematics at UA, and serves as the scientific leader of the Probability and Statistics Group at the Center for Research & Development in Mathematics and Applications (CIDMA, UA). Her research interests include Multivariate Statistics (Dimensionality reduction, Analysis of compositional data and Analysis of other multidimensional complex data), Extreme Value Theory, and Teaching Probability and Statistics. She holds over 35 publications indexed in SCOPUS. Presented over 50 communications at international conferences. Served on the local organizing committee for one national and two international conferences in Statistics, as well as recently serving as president of the scientific committee for a national congress. Realized teaching mobility missions (Erasmus, 6). Adelaide Freitas has supervised master's dissertations (28 completed), curricular internships (6 completed), and doctoral theses (1 in Education and 2 in Mathematics). Currently she is supervising 2 PhD students and 3 master students.

Speech Title: "Comparing Ordinary and Robust Decompositions of the Trajectory Matrix to Explore Features of Univariate Time Series"

Abstract: The Singular Spectrum Analysis (SSA) method is a powerful technique for time series analysis. In the basic version of SSA, the trajectory of the original univariate time series is mapped into a Hankel-type matrix. We obtain the decomposition of this matrix using two different approaches of the NIPALS algorithm: one approach is classical (based on L2-norm) and the other is robust (based on L1-norm). Then, the difference matrix is computed. In this talk, we explore the interpretation of this difference matrix and discuss how it can be advantageous for detecting temporal patterns and facilitating clustering tasks in time series analysis. (It is a joint work with Alberto Silva (CIDMA, UA) and Filipa Santana (CIDMA, UA))

Asst. Prof. Flora Ferreira
University of Minho, Portugal

Flora Ferreira holds positions as an Invited Assistant Professor in the Department of Mathematics and a researcher at the Centre of Mathematics at the University of Minho, along with serving as a Data Analyst at BERD - Bridge Engineering Research & Design. She completed her Ph.D. in Mathematics at the University of Minho in 2014. Her research focuses on mathematical modeling, dynamical systems, data analysis, and machine learning, driven by practical inquiries and multidisciplinary collaborations. She has contributed to numerous collaborative research projects and has publications in various peer-reviewed international journals, book series, and proceedings. Her primary research findings have been presented at numerous meetings and conferences worldwide, garnering recognition through awards and distinctions. Additionally, she has served on the review boards of several scientific journals and on the program committees of international conferences.

Speech Title: "Statistical and Machine Learning Approaches in Gait Data Analysis for Disease Diagnosis and Monitoring"

Abstract: This talk showcases the outcomes of employing different approaches utilizing statistical and machine learning techniques for disease classification based on gait data. Gait analysis is increasingly recognized as a valuable tool for diagnosing and monitoring various neurological disorders. By harnessing statistical methods and machine learning algorithms, we explore the intricacies of interpreting gait data and emphasize the effectiveness of different methodologies in accurately classifying diseases. From conventional statistical techniques to cutting-edge machine learning methods, we examine how these tools can be customized and refined to improve disease classification precision, thereby facilitating early detection and personalized treatment strategies. The talk will also address lingering questions in the field, fostering discussion and exploration of future research directions.


Previous 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.

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.

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.

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: