I hold a PhD/MSc in Mathematical and Applied Statistics from the University of Granada and a PhD in Art Science from Ghent University. I develop statistical methods and algorithms for preprocessing and analyzing data from neurophysiological monitoring techniques (e.g., EEG, MEG, MRI, pupillometry), integrating elements of infinite-dimensional and high-dimensional data analysis. Below, you can download my CV and view some of my recent research projects.
🎓 Research Interests: Functional data analysis · Factor analysis · High-dimensional data · Independent component analysis · Music neuroscience · Neuroimaging preprocessing methods · Probability theory · Semi- and non-parametric methods
Vidal, M., Aguilera, A. M. Wavelet thresholding on independent subspace factorizations of spatially indexed wide functional data for robust estimation of cortical activity. To appear in: Mathematics and Computers in Simulation.
Vidal, M., Leman, M., Aguilera, A. M. Functional independent component analysis by choice of norm: a framework for near-perfect classification. To appear in: Advances in Data Analysis and Classification. Arxiv
Vidal, M., Onderdijk, K. E., Aguilera, A. M., Six, J., Maes, P-J., Fritz, T. H., Leman, M. Cholinergic-related pupil activity reflects level of emotionality during motor performance. European Journal of Neuroscience, 59(9):2193–2207. DOI | Code
Moura, N., Vidal, M., Aguilera, A. M., Vilas-Boas, J.P., Serra, S., Leman, M. Knee flexion of saxophone players anticipates tonal context of music. npj Science of Learning, 8(22). DOI
Vidal, M., Aguilera, A. M. Novel whitening approaches in functional settings. Stat,12(1):e516. DOI | Corregidum | Code
Vidal, M., Rosso, M., Aguilera, A. M. Bi-smoothed functional independent component analysis for EEG artifact removal. Mathematics, 9(11):1243. DOI | Updated version