Rubén Amorós Salvador, Graduate in Statistical Sciences and Techniques, Master in Research in Didactics, and PhD in Statistics from the Universitat de València, is currently a permanent lecturer at the Departament d’Estadística i Investigació Operativa of the Universitat de València.

He has conducted research at the FISABIO foundation, at the Universitat de València, and at the University of Edinburgh, among other institutions, in statistics applied to epidemiology, rare diseases, health and the environment, as well as disease detection; using Bayesian hierarchical statistical modelling, Markov chains, time series and GAM models. He has also taught university-level courses at the University of Edinburgh, the Universitat de València and the Fundació Universitària CEU San Pablo.

David Conesa has a PhD in Mathematics from the University of Valencia, where he has been working since October 1993. He conducts research in the area of ​​statistical modeling of situations in which uncertainty is present, and does so mainly from a Bayesian perspective. Thus, for example, he has worked on problems of queues, hierarchical models, efficiency analysis, animal survival models, and lately in species distribution models.

He is co-author of 100 publications, the majority indexed in journals of international impact, and more than 275 communications in national and international conferences. He has co-directed 10 theses and is currently co-directing four more.

He has carried out research and teaching stays at Duke University (USA), Lancaster University (UK), Statistical and Applied Mathematical Sciences Institute (USA), Université de Bordeaux (France), Università de Bergamo (Italy), Universidade do Minho (Portugal), Università Cattolica del Sacro Cuore (Italy) and several Spanish universities.

He was the President of the Spanish Region of the International Biometric Society during the years 2014 and 2015, and is currently the Editor-in-Chief of the journal Statistics and Operations Research Transactions (SORT).

He has taught Mathematics, Biostatistics, Design of Experiments, Spatio-Temporal Statistics, Mathematical Statistics, Statistical Modeling, Probability and Simulation, Bayesian Statistics, Computing and Programming in R, Generalized Linear Models, and Smoothing, Additive and Mixed Models.

Maria Grau Pérez has a degree in Mathematical Sciences (2010) with a Master in Biostatistics (2014), both from the University of Valencia. After a few years working as a Statistics Specialist first at Johns Hopkins University (Baltimore, 2014-2016) and then at Columbia University (New York, 2016-2018), she returned to Spain to complete her doctorate in Epidemiology and Public Health for the Autonomous University of Madrid (2022).

She currently has a position in the Department of Statistics and Operational Research of the University of Valencia and is a researcher at the Health Research Institute of the Clinical Hospital of Valencia (INCLIVA).

Her research focuses on evaluating the health effects of long-term environmental exposures (metals, tobacco or eating habits, among others), with special interest in the integration of genetics and the development of causal inference methods. For the last 10 years she has been working on research projects related to the environment in cohort studies that have led to more than 40 scientific articles published in high impact journals.

Elena Lázaro is an Agronomist Engineer from the Polytechnic University of Valencia (2008) and holds a PhD in Statistics and Optimization from the University of Valencia (UV, 2018). She is currently an Assistant Professor at the Department of Statistics and Operations Research at UV, where she teaches statistics, combining methodological and applied approaches for data analysis and interpretation, and participates in educational innovation projects. Between 2018 and 2023, she worked as a postdoctoral researcher at the Valencian Institute of Agricultural Research (IVIA).

She is a member of the VABAR research group (València Bayesian Research Group) and has participated in several European H2020 projects, such as XF-ACTORS and Pre-HLB. Her research focuses on the application and development of Bayesian methods for survival analysis and joint models, predictive modeling of plant pests and pathogens, optimization of plant health surveillance systems, and meta-analysis methodology applied to pathogen control policies. This work has been reflected in numerous publications in JCR journals and technical reports for EFSA (European Food Safety Authority).

[Biography, english version]