About me

PhD in Telecommunication Engineering, currently Professor at UPM, where I teach courses on Statistics and Machine Learning, both at Degree and Master level.

My main research interest focuses on Artificial Intelligence, Optimal Control and Signal Processing methods applied to different fields. Although right now I am focused on medical applications, I have also applied these tools to Autonomous Navigation, Cybersecurity and Audio Separation. For a more detailed view, you can check my publications.

Finally, you can find more details on my CV.

Students

For UPM students, if you are interested in applying AI methods to medicine in your Bachelor or Master thesis, do not hesitate to contact me via email or UPM Teams. If I do not reply within a week, mail again, as your mail may have been marked as spam.

Latest news

• In 2024, we have published:
  • MOSAIC: An Artificial Intelligence–Based Framework for Multimodal Analysis, Classification, and Personalized Prognostic Assessment in Rare Cancers, in the journal JCO Clinical Cancer Informatics.
  • Propensity weighted federated learning for treatment effect estimation in distributed imbalanced environments, in the journal Computers in Biology and Medicine.
  • Explainable drug repurposing via path based knowledge graph completion, in the journal Scientific Reports.
  • Synthetic tabular data validation: a divergence-based approach, in the journal IEEE Access.
  • NauSim: An open source simulator for underwater drone control, development and deployment, as a conference paper in XLV Jornadas de Automática.
  • An improved tabular data generator with VAE-GMM integration, as a conference paper in EUSIPCO.
  • CR-SAVAE: A Parametric Method for Survival Analysis with Competing Risks, as a conference paper in EUSIPCO.
  • Deep Learning as a new framework for passive vehicle safety design using finite elements models data, in the journal Applied Sciences.
  • Leveraging the variational Bayer autoencoder for survival analysis, in the journal Scientific Reports.