Machine Learning
Machine learning is revolutionizing how we understand and interact with the world around us, and it does so by offering tools to learn from data. The availability of data at unprecedent scale and the diversity of data that characterizes modern day applications pose novel challenges to the way machine learning is conceived and employed. At EURECOM, we work at the interface of computational, statistical and mathematical sciences to develop novel machine learning algorithms that can deal with the volume, diversity and complexity of data to advance our understanding of complex phenomena in a number of applied domains, such as:

Multimedia analysis

Social networks

Life sciences

Environmental sciences
We do this by carrying out fundamental research on scalable approaches to Bayesian nonparametrics, causality, largescale matching, clustering, deep learning, graph theory, linear algebra and the interaction of machine learning with game theory.