Intro — Hola!, I am postdoc @ the Section for Cognitive Systems (CogSys) in the Technical University of Denmark (DTU) 🇩🇰. Since I am in Copenhagen, I work in Søren Hauberg's group. Our projects typically revolve around probabilistic models, stochastic geometry, Bayesian neural networks and related topics, usually with focus on machine learning methods and theory. I am also ELLIS member and affiliated researcher at the Pioneer Center for Artificial Intelligence.

Past — My original background is statistical signal processing (I like streaming data!), and I worked on insightful ML/AI topics applied to healthcare during my PhD studies — i.e. mental health. During this time, I got interested in the probabilistic view of machine learning so I did some cool works on Gaussian processes and new adaptations of this algorithm from one of the most inspiring researchers in ML/AI.

Present — Is it possible to apply Bayesian principles to standard neural networks? How and why these recent large models — i.e. LLMs, work that well? These are two questions that I am very interested in (see A and B). I also like scalable methods, uncertainty quantification and information theory for deep learning. These topics are complementary with other interests like lite/low computational models and continual learning, often connected to other applied ideas.

Future — I'm extremely thankful and honored to be one of the recipients of the LaCaixa Junior Leader Fellowships. The short-term consequence for my research career is that I'll begin a new stage in Barcelona! The fellowship program consists of three years of funding, with new resources and the final goal of heading a new research group in the future.

Last News     |     All News

Short Bio