Carlos completed his PhD in statistical machine learning at Stanford University in 2017. Previously, he obtained a MSc in Mathematics at the University of Oxford, UK, and a double bachelor in Mathematics and Computer Science at Universidad Autonoma de Madrid, Spain. His research focuses on sequential decision making under uncertainty. In addition to reinforcement learning and active learning, he recently became interested in unsupervised learning; in particular, in deep generative models, with applications to images, videos, and, text.