Who am I
Research. My research primarily focuses on advancing the field of Machine Learning by understanding and developing novel probabilistic models that address real-world biomedical problems. To overcome the common challenges encountered in the biomedical field, such as missing data and heterogeneous modalities, I am dedicated to learn, develop and apply heterogeneous generative models that offer more accurate and reliable predictions. I have a deep interest in the fields of eXplainable AI (XAI) and ethical AI. With the growing influence of AI technologies in our society, it is crucial to ensure transparency, trustworthiness, and ethical alignment.
Previously. I obtained my Ph.D. with honors (cum laude) from UC3M (Universidad Carlos III de Madrid) in the field of Machine Learning for Personalised Medicine, specifically the clinical microbiology field. I am grateful for the invaluable guidance and joint supervision provided by Dr. Pablo M. Olmos and Dr. Vanessa Gómez-Verdejo throughout my doctoral journey. During my thesis, I was affiliated with the Gregorio Marañón Health Research Institute (IISGM), where I had the privilege of working under the guidance of Dr. Belén Rodríguez-Sánchez. The experience gained during my time at IISGM has significantly shaped my research interests and provided me with valuable insights into the challenges faced by the biomedical community.
🌟 Big news 🌟
🌐 Introducing BacteriaID: A Leap Forward in Bacterial Identification 🌐
We’re thrilled to unveil our latest innovation: BacteriaID, a pioneering web application poised to transform the landscape of bacterial classification. Developed from our recent research, BacteriaID employs state-of-the-art MALDI-TOF MS technology to automate the identification of toxigenic European ribotypes of Clostridioides difficile.
🔒 Currently in closed beta, BacteriaID represents our most ambitious milestone yet, embodying the synergy of cutting-edge research and practical application. This tool helps advancing microbiology through technology, providing an accessible, accurate, and indispensable resource for researchers and healthcare professionals worldwide.
👥 Crafted through a collaborative effort with renowned institutions, BacteriaID is not just a tool but a movement towards a future where bacterial infections are detected with unprecedented precision and speed.
Stay tuned for exclusive updates, insights, and the official launch date. Join us in this groundbreaking journey at BacteriaID.
🌟 Latest Buzz 🌟
March 2024: 📢 Exciting news! We’ve released a groundbreaking public dataset on Parkinsonian speech. Perfect for researchers! Use it wisely and don’t forget to cite! Explore now.
January 2024 🚀: Dive into our latest breakthrough! Discover our new preprint on revolutionizing Clostridioide difficile ribotyping with cutting-edge probabilistic Machine Learning. Check it out!
December 2023 📊: Exciting News! We’ve released a groundbreaking public dataset on Clostriodide Difficile ribotypes. Perfect for researchers! Use it wisely and don’t forget to cite! Explore now.
👀 Keep your eyes peeled for more thrilling updates and milestones in my journey!
- Postdoctoral researcher at the Bioengineering and Optoelectronics Group, UPM, Madrid, Spain.
- Ph.D. candidate at Signal Processing Group, UC3M, and predoctoral researcher at Gregorio Marañón Health Research Institute, Madrid, Spain.
- M.Sc. in Information Health Engineering at UC3M, Madrid, Spain.
- Telecommunication Engineer at Alcort, Mallorca, Spain.
- Research assistant at UGIVIA, UIB, Mallorca, Spain.
- B.Sc. in Telematics Engineering at UIB, Mallorca, Spain.