Mose and Lillian S. Bohn Professor of Electrical Engineering and Computing and Mathematical Sciences
communications theory, information theory, adaptive and statistical signal processing, robust and distributed control, machine learning, high-dimensional statistics, convex optimization, DNA microarrays, random matrices, group representation theory
Hassibi's research spans various aspects of information theory, signal processing, control theory, and machine learning. He has made contributions to the theory and practice of wireless communications and wireless networks, as well as to robust control, adaptive filtering and neural networks, network information theory, coding for control, phase retrieval, structured signal recovery, high dimensional statistics, epidemic spread in complex networks, and DNA micro-arrays. On the mathematical side, he is interested in linear algebra, with an emphasis on fast algorithms, random matrices, and group representation theory.