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Babak Hassibi
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Home  /  People  /  Babak Hassibi

Babak Hassibi

Mose and Lillian S. Bohn Professor of Electrical Engineering and Computing and Mathematical Sciences
B.S., University of Tehran, 1989; M.S., Stanford University, 1993; Ph.D, 1996. Assistant Professor, Caltech, 2001-03; Associate Professor, 2003-2008; Professor, 2008-2013; Binder/Amgen Professor, 2013-16; Executive Officer, 2008-15; Associate Director, 2010-2012; Bohn Professor, 2016-.
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Research interests: communications theory, information theory, adaptive and statistical signal processing, robust and distributed control, machine learning, high-dimensional statistics, convex optimization, DNA microarrays, random matrices, and group representation theory

Overview

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.

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Publications

View more publications on feeds.library.caltech.edu

Related Courses

2022-23
EE 164 – Stochastic and Adaptive Signal Processing
ACM/EE/IDS 170 – Mathematics of Signal Processing
2021-22
EE/CS/IDS 160 – Fundamentals of Information Transmission and Storage
2020-21
EE 164 – Stochastic and Adaptive Signal Processing
ACM/EE/IDS 170 – Mathematics of Signal Processing
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