My research is mainly focused on Formal Methods for Computer Science. This topic includes, but is not limited to, Artificial Intelligence, Machine Learning, Software Testing, and Software Engineering. My early main field of research was the application of Information Theory and Artificial Intelligence to Software Testing, but I also worked in the develop and application of Artificial Intelligence techniques to other fields. Now, my main field of research is the generation of knowledge graphs using self-learning algorithms, applied to the area of computational medicine.
However, my research interests are not limited to those topics. Of course I am interested in Computational Medicine and Machine Learning, but I am also interested in Quantum Computing, Robotics, and Space Science & Exploration, as well as other topics.
I am a PostDoctoral researcher at Sano – Centre for Computational Medicine working on developing machine self-learning algorithms to generate knowledge graphs from self-reported data.
Previously, I’ve been a PhD student at the Design and Testing of Reliable Systems (DTRS) research group at the Universidad Complutense de Madrid. During that time I was hired by a Santander-Universidad Complutense de Madrid grant for Ph.D. students. I was also hired by the FORTE-CM program in 2019 and by the SICOMORo-CM program in 2018. Before that, I have done a Master’s on Formal Methods for Computer Science and a Double Degree on Computer Science and Mathematics, including an Erasmus+ studentship at Kungliga Tekniska Högskolan (KTH) in Sweden.
Memberships and Colaborations
- DMIST 2021: International Conference on Data Mining, Information Systems and Technology. (PC Member)
- ICCIA 2021: 6th International Conference on Computational Intelligence and Applications. (PC Member)
- ICCIA 2020: 5th International Conference on Computational Intelligence and Applications. (PC Member)