I'm Research Intern under the supervision of Isabel Valera at the Max Planck Institute for Intelligent Systems in Tübingen.
Additionally, I'm PhD student in Probabilistic Machine Learning at the Universidad Carlos III de Madrid under the supervision of Antonio Artés also in collaboration with Gregorio Marañon Health Research Institute and eB2. During the last two years, I have been working on the development of powerful statistical methods for personalized medicine applications. Previously, I spent 6 months as research trainee at the European Space Agency (ESA) and I was also visiting the University of Sheffield where I collaborated with Mauricio A. Álvarez.
My current research focuses on three main topics: probabilistic online learning, latent variable models and heterogeneous data. The general idea is to develop robust predictive methods for personalized medicine applications.
I'm very interested in finding such models that are able to capture an interpretable latent structure of human behavioral patterns as well as detect abrupt changes on them. Together with my supervisors, I have recently develop a novel extension of multi-output Gaussian processes for handling heterogeneous outputs.
Probabilistic Models Bayesian Inference Gaussian Processes Heterogeneous Data
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems