In his early research,[4] Tropp developed performance guarantees for algorithms for sparse approximation and compressed sensing.
In 2011, he published a paper[5]
on randomized algorithms for computing a truncated singular value decomposition.
He has also worked in random matrix theory, where he has established a family of results,[6]
collectively called matrix concentration inequalities, that includes the matrix Chernoff bound.
Awards and honors
Tropp was a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2008.[7]
In 2010, he was awarded an Alfred P. Sloan Research Fellowship in Mathematics,[8]
and he received the Sixth Vasil A. Popov Prize in approximation theory for his work on Matching Pursuit algorithms.[4]
He won the Eighth Monroe H. Martin Prize in applied mathematics in 2011 for work on sparse optimization.[9]
He was recognized as a Thomson Reuters Highly Cited Researcher in Computer Science for the years 2014, 2015, and 2016.[10]
In 2019 he was named a SIAM Fellow "for contributions to signal processing, data analysis, and randomized linear algebra".[11]