Regional Statistics Conference 2026

Regional Statistics Conference 2026

Showcasing Technical Research by Women in Statistical Science in Portugal

Organiser

VL
Dr Vanda Lourenco

Participants

  • SL
    Suhwon Lee
    (Chair)

  • VL
    Dr Vanda Lourenco
    (Presenter/Speaker)
  • Toward Robust Tree-Based Ensemble Learning for Genomic Prediction

  • RM
    Prof. Raquel Menezes
    (Presenter/Speaker)
  • Spatio-temporal modelling of fish species distribution

  • LH
    Lígia Henriques-Rodrigues
    (Presenter/Speaker)
  • Bias-Reduction frameworks for generalized Hill estimators

  • EM
    Elsa Moreira
    (Presenter/Speaker)
  • Prediction and Analysis of Groundwater Drought Class Transitions using loglinear models applied to southern Portugal

  • Proposal Description

    The Caucus for Women in Statistics and Data Science (CWS) is an international professional society that promotes the education, employment, and advancement of women in statistics. Its mission is to advance the careers of women statisticians through advocacy, the provision of resources and learning opportunities, increased professional participation and visibility, and the promotion and evaluation of research that impacts women in statistics.

    The Portuguese Statistical Society (SPE) aims to promote, cultivate, and develop the study of statistics, its applications, and related sciences in Portugal. It also seeks to bring together all statisticians and connect people working in different areas of statistics — in universities, the private sector, and public administration.

    This invited session intends to showcase Portuguese women and their contributions to the field of statistics and its applications. The session comprises four women researchers working in diverse areas of statistical applications, representing institutions from multiple regions of Portugal, including Península de Setúbal in the Lisbon area, the North, and Alentejo, along with Suhwon Lee, President-Elect of the Caucus for Women in Statistics and Data Science (CWS), serving as the session chair.

    The presentations highlight recent developments in statistical research and applications that are likely to have broad appeal to the audience, including spatio-temporal modelling in fisheries, robust machine learning for genomic prediction in plant and animal breeding, log-linear models for probabilistic, site-specific groundwater drought forecasting, and extreme value theory for environmental and hydrological applications.