PhD Thesis

To this end, a cell deconvolution tool is designed using Deep Learning (DL) techniques, capable of decomposing the composition of ADP samples from transcriptomic data. After identifying the cellular proportions, the aim is to stratify patients with this disease according to their molecular characteristics, in order to find detectable markers in routine clinical practice.

    • PhD candidate:  Alba Lomas Redondo.
    • Directors: Prof. Dr. D. Álvaro José García Tejedor and Prof. Dr. D. Víctor Sánchez-Arévalo Lobo.
    • Presented at: Universidad Francisco de Vitoria (en curso).

 

Search for a biomarker for early diagnosis and staging of Parkinson's disease by means of Deep Learning techniques applied to electroencephalograms (EEG) of patients. For this purpose, connectivity analysis is performed by means of graph theory and GCNN type deep networks (modeling EEGs as graphs) and time series analysis by means of PLN techniques (performing a text-EEG equivalence).

    • PhD candidate:  Ana María Maitín López.
    • Directors: Prof. Dr. D. Álvaro José García Tejedor and Prof. Dr. D. Juan Pablo Romero Muñoz.
    • Presented at: Universidad Francisco de Vitoria el 9/Octubre/2023 con calificación Sobresaliente Cum Laude.
    • PDF link: https://www.educacion.gob.es/teseo/mostrarRef.do?ref=458769

 

Search for a biomarker for early diagnosis and staging of Parkinson's disease by means of Deep Learning techniques applied to electroencephalograms (EEG) of patients. For this purpose, connectivity analysis is performed by means of graph theory and GCNN type deep networks (modeling EEGs as graphs) and time series analysis by means of PLN techniques (performing a text-EEG equivalence).

    • PhD candidate:  Ana María Maitín López.
    • Directors: Prof. Dr. D. Álvaro José García Tejedor and Prof. Dr. D. Juan Pablo Romero Muñoz.
    • Presented at: Universidad Francisco de Vitoria el 9/Octubre/2023 con calificación Sobresaliente Cum Laude.
    • PDF link: https://www.educacion.gob.es/teseo/mostrarRef.do?ref=458769

 

Mechanisms to improve energy efficiency in cities and buildings through the application of soft computing techniques in high consumption systems, increasing the quality of services in terms of welfare and comfort of people in a sustainable way. The study focuses on two urban systems of high consumption: air conditioning of buildings and street lighting.

    • PhD candidate:  Alberto Garcés Jiménez.
    • Directors:  Prof. Dr. D. Álvaro José García Tejedor and Prof. Dr. D. José Manuel Gómez Pulido.
    • Presented at: Universidad de Alcalá on 25/September/2020. Sobresaliente Cum Laude and Doctorate Extraordinary Award.
    • PDF link: https://www.educacion.gob.es/teseo/mostrarRef.do?ref=458769

 

Proposal of a validation process for the design of educational video games created for people with intellectual disabilities using a cycle that covers the phases of design, development, testing, data capture and subsequent analysis. The method has been tested in a specific case with a complex video game, but it is generalizable and applicable to other developments aimed at this type of users.