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Babak Hassibi is the Mose Lillian S. Bohn Professor of Electrical Engineering at the California Institute of Technology. His research encompasses various aspects of information theory, signal processing, and control theory, with a specific focus on machine learning, adaptive statistical signal processing, and robust distributed control. He has made significant contributions to the theory and application of wireless communications, robust control, and adaptive filtering. His interests also extend to network information theory, coding control, phase retrieval, and structured signal recovery. Additionally, he studies epidemic spread in complex networks and is involved in research related to DNA microarrays. His mathematical work emphasizes linear algebra, fast algorithms, random matrices, and group representation theory.
California Institute of Technology • Pasadena, CA
Started as an Assistant Professor in the Department of Electrical Engineering.
California Institute of Technology • Pasadena, CA
Promoted to Associate Professor, contributing to research and teaching in Electrical Engineering.
California Institute of Technology • Pasadena, CA
Held the position of Professor and led numerous research initiatives.
California Institute of Technology • Pasadena, CA
Served as Binder/Amgen Professor in Electrical Engineering.
California Institute of Technology • Pasadena, CA
Managed departmental operations and academic programs.
California Institute of Technology • Pasadena, CA
Oversaw specific educational programs within the department.
California Institute of Technology • Pasadena, CA
Currently holds the title of Bohn Professor in the Department of Electrical Engineering.
Most Caltech graduate programs are PhD-only. GRE General and Subject tests vary by department; many have made them optional or no longer accept them.