Olaya González-Campos

Olaya González-Campos is a first-year PhD student in the Department of Statistics and Operations Research at Universidad de Oviedo (Spain) and the Department of Data Analysis and Mathematical Modeling at Ghent University (Belgium), supervised by Raúl Pérez-Fernández and Bernard de Baets, respectively. She holds a BSc in Mathematics (2025) from Universidad de Oviedo and an MSc in Statistics for Data Science from Universidad Carlos III de Madrid (2026).

Her doctoral research, titled «Clustering under Imprecision and Uncertainty», focuses on analyzing how unsupervised learning methodologies are affected by imprecise data and extending traditional algorithms through the mathematical framework of random sets. In many practical applications, real-world data is inherently imprecise due to limited measurement precision, sensor noise, or subjective expert evaluations, rendering classical clustering techniques that assume exact attribute vectors artificially precise. Her project addresses this limitation by adapting fundamental methods, such as k-means and hierarchical clustering, to separate intrinsic data variability from observation uncertainty, ultimately delivering more robust and realistic analytical tools for complex domains like bioscience engineering.