Invited Speakers

 

Assoc. Prof. Teresa A. Oliveira
Universidade Aberta

Teresa A. Oliveira is Associate Professor with Habilitation in Mathematics-Statistics, at DCeT-UAb, in Lisbon, Portugal. She obtained MSc and doctoral degrees in Statistics and Operations Research at the University of Lisbon and is a senior member of the CEAUL, http://ceaul.org/o-centro/membros-ceaul/. Her research interests include Experimental Design, Statistical Quality Control, Risk Analysis, Statistical Modeling, Computational Statistics, Stochastic Models, Data Analysis, and e-Learning Methodologies. She actively participated in many Erasmus+ Bilateral and Teaching Programs and was selected by the National Agency as an evaluator for Erasmus+ during 2021/2027. She is the Chair of the ISI-CRA International Statistical Institute - Committee on Risk Analysis, and was appointed as a founding member of the ISI Working Group on Data Science. With extensive editorial experience, she is Associate Editor of JAS - Journal of Applied Statistics and MPS - Mathematical Population Studies, as well as of other prestigious Journal Editorial Boards. She has publications in several peer-reviewed international and national papers, books, special issues, and proceedings, and her main research results were presented in many conferences worldwide. Her contributions to Mathematics-Statistics continue to inspire new research and innovation, which is clearly reflected in theses and dissertations under her supervision, in various courses, and in several universities.

Dr. Clara Cordeiro
University of the Algarve

Clara Cordeiro holds a PhD in Mathematics and Statistics from the Technical University of Lisbon, specialising in forecasting time series with Bootstrap. She is an Assistant Professor in the Department of Mathematics at the University of the Algarve. Clara is also a member of the Research and Development unit - Centre of Statistics and Applications (CEAUL) at the University of Lisbon. Her scientific interests are bootstrap for dependent data, exponential smoothing methods, and forecasting time series. Additionally, she has developed statistical models and algorithms to address scientific inquiries across various scientific domains. Recently, her research has been driven by collaborative projects with non-academic partners.


 

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