Carlo Sguera is a postdoctoral researcher at Universidad Carlos III de Madrid-Banco Santander Institute on Financial Big Data. His areas of research are Functional Data Analysis, Statistical Depth, Classification and Outlier Detection. He is presently working in Statistical Network Analysis and Big Data.
From 2010 to 2014, under the supervision of Professors Pedro Galeano and Rosa Lillo, he developed his PhD thesis named “Spatial Depth-Based Methods for Functional Data” at the Department of Statistics of Universidad Carlos III de Madrid. During the development of his thesis he spent 4 months as visiting researcher at the Biostatistics Department of Columbia University where he collaborated with Professors Sara López-Pintado and Jeff Goldsmith. He has also attended to several conferences and workshops such as ICORS, ERCIM, COMPSTAT and SEIO.
As a PhD student, he focused on a last generation area of statistics known as Functional Data Analysis, that is, the collection of statistical techniques that allow to analyze those data sets composed of curves. In particular, he considered topics such as functional depth analysis, classification and outlier detection. Furthermore, the quality of his research has been already recognized and he succeeded in publishing the main results of his thesis in two different articles in international journals: the first in TEST in 2014, the second in Stochastic Environmental Research and Risk Assessment in 2015.
During his stay at the UC3M’s Department of Statistics he has been Teaching Assistant, Coordinating Assistant and Lecturer of several courses such as Statistics I and II, Statistical Inference and Multivariate Analysis I and II. He is also a promoter of UC3M among high school students and he was one of the speakers at the UC3M educational show “Stat Wars”.