Mauro Maggioni is the Bloomberg Distinguished Professor of Data-Intensive Computation in the Whiting School of Engineering’s Department of Applied Mathematics and Statistics and the Krieger School of Arts and Science’s Department of Mathematics.
He is an expert in mathematical techniques for analyzing, modeling, and extracting information from large data sets in order to enable smarter machine learning algorithms and scientific discoveries. With a strong foundation in harmonic analysis and signal processing, Maggioni’s research is focused on the analysis of high-dimensional data, graphs, and networks. Specifically, he is developing algorithms that analyze and exploit the geometry of big data in order to train machines to learn and predict patterns in data. These hidden geometric structures in high-dimensional data are pervasive and appear in completely different data types, from images to text documents to trajectories of complex dynamical systems.