Profesores e Investigadores

Departamentos

Curriculum Vitae

José Luis Rojo Álvarez
Catedrático/a de Universidad
Director/a Académico/a de Planificación Científica
4
Quinquenios
2020
5
Docentia
2020-21
3
Sexenios investigación
2016
1
Sexenios transferencia
2018

Centro

E. Ingeniería de Fuenlabrada

Departamento

Teoría de la Señal y Comunicaciones y Sistemas Telemáticos y Computación

Área

Teoría de la Señal y Comunicaciones

Grupo de investigación

Grupo de investigación de alto rendimiento en Ingeniería Biomédica y Ciencia de Datos en de la Universidad Rey Juan Carlos - Biomedical Engineering and Data Science Group of Universidad Rey Juan Carlos

Contacto

joseluis.rojo@urjc.es
Información general
Información general
Presentación

  • He received the Telecommunication Engineering Degree in 1996 from University of Vigo, Spain, and the PhD in Telecommunication Engineering in 2000 from the Polytechnical University of Madrid, Spain. Since 2016, he has been a Full Professor in the Department of Signal Theory and Communications, University Rey Juan Carlos, Madrid, Spain.

    He has published more than 100 papers in JCR journals and more than 160 (inter)national conference communications. He has participated in more than 55 projects (with public and private fundings), and directed more than 10 of them, including several actions in the National Plan for Research and Fundamental Science. He has been a Senior Researcher at the Prometeo program in Ecuador (Army University). Currently he is supporting a pioneer Degree Program on Biomedical Engineering, involving Hospitals and Companies in the electromedic and eHealth field.

    His main research interests include statistical learning theory, digital signal processing, and complex system modelling, with applications to digital communications and to cardiac signals and image processing. Also in the scope are Big Data analysis, Statistical Learning, Machine Learning and Health Data Processing.

    He joined Persei Vivarium, an eHealth company, as Chief Scientific Officer in 2015. In 2016 he received the Price to the Talented Researcher from Rey Juan Carlos University.      He joined the Center for Computational Simulation in 2017, a joint inter-university entity for cooperation on the analysis of large amounts of data and intensive simulations.
                                                          

Méritos
Docencia y asignaturas impartidas en el curso actual

  • Grado

    PLAN ASIGNATURA
    (2229) GRADO EN INGENIERIA BIOMEDICA (FUENLABRADA)FUNDAMENTOS BIOLECTRICOS
    (2229) GRADO EN INGENIERIA BIOMEDICA (FUENLABRADA)PRACTICAS EXTERNAS 1 (PRACTICAS CLINICAS)
    (2291) GRADO EN INGENIERIA BIOMEDICA (INGLES) (ALCORCON)BIOELECTRIC FUNDAMENTALS
    (2291) GRADO EN INGENIERIA BIOMEDICA (INGLES) (ALCORCON)EXTERNAL PRACTICES 1 (HOSPITALS AND HEALTH)
    (2291) GRADO EN INGENIERIA BIOMEDICA (INGLES) (ALCORCON)MASSIVE DATA PROCESSING
HISTÓRICO DOCENTE (ÚLTIMOS 10 CURSOS ACADÉMICOS)

Listado de proyectos (Últimos 10 años)
Códigos de investigador
Publicaciones


  • 1.       Vadillo-Valderrama, A, Goya-Esteban, R, Caulier, Raúl P., García-Alberola, A, JL Rojo-Álvarez. Differential Beat Accuracy for ECG Family Classification Using Machine Learning. IEEE Access 10:129362-81, 2022. 3.367 (94/273, Q2 Engineering, Electrical and Electronic).

    2.           Bote L, S Ruiz-Llorente, S Muñoz, M Yagüe-Fernández, A Barquin, I Garcia-Donas, JL Rojo-Álvarez. Multivariate Feature Selection and Autoencoder Embeddings of Ovarian Cancer Clinical and Genetic Data. Expert Systems with Applications (ESW) 206, 2022. 8.665 (23/276, Q1 Engineering, Electrical and Electronic)

    3.           Chaquet J, Gimeno-Blanes J, Moral S, Muñoz S, Rojo-Álvarez JL. On the Black-box Challenge for Fraud Detection using Machine Learning (II): Non-Linear Analysis through Interpretable Autoencoders. Applied Sciences 12(8):3568, 2022. 2.474 (67/148, Q2 Applied Physics)

    4.           Chaquet J, Gimeno-Blanes J, Moral-Rubio S, Muñoz S, Rojo-Álvarez JL. On the Black-box Challenge for Fraud Detection using Machine Learning (I): Linear Models and Informative Feature Selection. Applied Sciences 12(7): 3328, 2022. 2.474 (67/148, Q2 Applied Physics)

    5.           Melgarejo-Meseguer FM, E Everss, M Gutiérrez, S Muñoz-Romero, FJ Gimeno-Blanes, A García-Alberola, JL Rojo-Álvarez. Generalization and Regularization for Inverse Cardiac Estimators. IEEE Trans. Biomed. Eng., 2022. 4.491 (11/80, Q1 Biomedical Engineering).

    6.           Piles M, J Muñoz-Mari, A Guerrero, G Camps-Valls, JL Rojo-Álvarez. Autocorrelation Metrics to Estimate Persistence from Satellite Soil Moisture Time Series: Application to Semi-Arid Regions. Ref revista/libro: IEEE Transactions on Geoscience and Remote Sensing (TGRS) 60, 2022. 5.6 (35/273, Q1 Engineering, Electrical and Electronic).

    7.         Bote-Curiel, L., Ruiz-Llorente, S., Muñoz-Romero, S., Yagüe, M., Barquín, A., García-Donas, J., Rojo-Álvarez, J. L. (2021). Text analytics and mixed feature extraction in ovarian cancer clinical and genetic data. IEEE Access, 9, 58034-58051. F.I.:4.098 (61/266, Q1 Engineering, Electrical and Electronic).

    8.         Bote-Curiel, L., Ruiz-Llorente, S., Muñoz, S., Yagüe, M., Barquín, A., García-Donas, J., Rojo-Álvarez, J. L. (2021). A resampling univariate analysis approach to ovarian cancer from clinical and genetic data. IEEE Access, 9, 25959-25972. F.I.:4.098 (61/266, Q1 Engineering, Electrical and Electronic).

    9.         González L, P Talón, S Muñoz-Romero, C Soguero, JL Rojo-Álvarez. A Big Data Approach to Customer Relationship Management Strategy in Hospitality using Multiple Correspondence Domain Description. Applied Sciences 10(15):5334, 2020. FI: 2.474 (67/148, Q2 Applied Physics)

    10.       Venegas P, Perez N, Zapata S, Mosquera J, Augot D, JL Rojo-Álvarez, Benitez D. An Approach to Automatic Classification of Culicoides Species by Learning the Wing Morphology. Plos ONE 934-941, 2020. F. I: 2.74 (27/71, Q2 Multidisciplinary sciences).

    11.       El Yaagoubi M, Mora I, Jabrane Y, S Muñoz-Romero, JL Rojo-Álvarez, Pareja JA. Quantitative Cluster Headache Analysis for Neurological Diagnosis Support using Statistical Classification. Information and Communications Technology. Information 11(8):393, 2020.

    12.       Vayas G, Soguero C, JL Rojo-Álvarez, Gimeno J. On the Differential Analysis of Enterprise Valuation Methods as a Guideline f

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