Babak Hassibi

Babak Hassibi is the Mose and Lillian S. Bohn Professor of Electrical Engineering and Computing and Mathematical Sciences at the California Institute of Technology, Department of Electrical Engineering. His research spans information theory, signal processing, control theory, and machine learning, with contributions to wireless communications, robust control, and high-dimensional statistics. Hassibi's work also includes topics such as random matrices, group representation theory, and structured signal recovery. He has held various academic positions at Caltech, including Assistant Professor, Associate Professor, Professor, and Binder/Amgen Professor. His teaching includes courses on information transmission, stochastic signal processing, and mathematics of signal processing.

Babak Hassibi is a professor of electrical engineering whose research spans information theory, communications, signal processing, control theory, and machine learning. His work focuses on the design and analysis of high-rate codes, wireless communication systems, and optimal algorithms for signal estimation and control. Hassibi has contributed significantly to the understanding of MIMO systems, network coding, and efficient decoding techniques. His research also explores the application of machine learning in signal processing and control systems, emphasizing the development of robust and adaptive algorithms. His publications often address the theoretical foundations of communication systems and their practical implementation.