Data:
13 maio 2024 (2ª feira) | 14h00 – 17h30
Duração: 3h30m
Local:
Ciências ULisboa. Room 6.4.35
Formadores:
Ben Stevenson, University of Auckland, New Zealand
Ben Stevenson is a Senior Lecturer in the Department of Statistics at the University of Auckland, New Zealand. An alumnus of the same institution, earned both a BSc (Hons) and an MSc before pursuing a PhD at the University of St Andrews, United Kingdom, graduating in 2016. Joined the University of Auckland’s faculty in January 2017.
His research primarily focuses on developing statistical methods and software aimed at estimating ecological parameters, often concerning animal abundance or density. His expertise also extends to spatial statistics, statistical computing, and applied statistics, with a strong emphasis on ecological applications. His interdisciplinary research interests have also led to contributions in medicine and veterinary sciences.
Programa:
Ben Stevenson is a statistician based at the University of Aukland and is visiting CEAUL until the 15th of May on a sabbatical. Spatial-capture recapture (SCR) is a technique that is only 20 years old but which is now widely applied worldwide to estimate density of wildlife. Ben has been working on various aspects of SCR for several years on a range of different methods developments and applications. While Ben’s seminar focus is on acoustic data, SCR methods are widely used also under different settings for which animals, or something they might produce like sounds, might be detected at multiple “traps”. Come and learn more about it if you are interested on the methods from either a practical or a methodological perspective. If you are interested in SCR, you will be interested in knowing that Ben will also deliver a SCR related CEAUL seminar on Wednesday 8th of May under the title “Penalised regression splines for spatial capture-recapture”.
Preço:
Gratuito
A inscrição é gratuita mas obrigatória, devendo ser efetuada até dia 12 de maio através do formulário.
Projeto UIDB/00006/2020
DOI: 10.54499/UIDB/00006/2020 maioi