Dr. Tropp's research focuses on algorithms for solving computationally difficult problems that arise in applied mathematics, statistics, electrical engineering, and computer science. In particular, he studies how constraints on data complexity can be used to develop new techniques for signal acquisition and processing. This area encompasses classical problems, such as variable selection in regression, as well as recent advances, such as compressive sampling. Other applications include inverse problems, machine learning, and data mining.
