I am working at the Max Planck Institute as a PhD student (with a stipend) under the supervision of Isabel Valera, leader of the Probabilistic Learning Group in the Department of Empirical Inference.
I studied a simultaneous bachelor program of mathematics and computer science at the University of Murcia which I finished in 2018. That same year, I obtained my master degree in computer science within the same institution.
My research interests cover a wide range of topics and I am always open to new problems to dive in. A common feature among all of these topics is that they lie in-between the fields of mathematics and computer science, since solid mathematical foundations are key to develop well-behaved algorithms and models.
At this moment my main research focus is on Bayesian probabilistic modelling, Deep Learning, and variational inference. Specifically, my work with Isabel Valera focus on the development of deep generative models for incomplete and heterogeneous data.
Machine Learning; Mathematics; Bayesian Statistics; Deep Learning
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