García Rasines, Daniel

Quantitative Methods

PhD: Imperial College London

BIO

Daniel García Rasines has a BSc in Mathematics from the University of Santiago de Compostela (2016), and an MSc and a PhD in Statistics from Imperial College London (2017, 2021). After his doctoral studies, he joined the DataLab research group of the Mathematical Sciences Institute (2021–2022). Later, he returned to Imperial College as a Chapman Fellow (2022–2024). His research interests revolve around the development of inferential methods and decision-making policies in complex scenarios, mainly in the areas of selective inference and adversarial risk analysis. A full list of his published work is available at https://scholar.google.es/citations?user=zvBwc4EAAAAJ&hl=en

Publications in Scientific Journals

García Rasines, Daniel; Young, Alastair: “Splitting strategies for post-selection inference”, Biometrika, 110(3), 597-614, 2023.

García Rasines, Daniel; Young, Alastair: “Empirical Bayes and selective inference”, Journal of the Indian Institute of Science, 102, 1205-1217, 2022.

Ríos Insua, David; Couce Vieira, Aitor; Rubio, José Antonio; Pieters, Wolter; Labunets, Katsiaryna; García Rasines, Daniel: “An adversarial risk analysis framework for cybersecurity”, Risk Analysis, 41(1), 16-36, 2021.

Ríos Insua, David; Ruggeri, Fabrizio; Soyer, Refik; García Rasines, Daniel: “Adversarial issues in reliability”, European Journal of Operational Research, 266(3), 1113-1119, 2018.

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