Dr. Kemp received his Ph.D. from Cornell in 2005. He held an Escobar Assistant Professorship at Cornell during 2005-2006 and since then has been a Moore Instructor at MIT. Dr. Kemp's research is in Functional Analysis, especially in random matrices, free probability theory; and functional inequalities. Random matrix theory is of importance to mathematics, statistics, physics and engineering. Dr. Kemp is the author of six research papers, and his research has been recognized by a three year individual investigator grant from the NSF.

Dr. Kemp is an excellent teacher, with a record of outstanding teaching at Cornell and MIT.
He
has advised one PhD student, whose research is in the interface between
mathematics and electrical engineering.
He has also been active in working with high school students and undergraduates, including running a NSF-sponsored Research Experience for Undergraduates (REU) program at Cornell in 2007, and running the MIT Integration Bee. At UCSD, Dr. Kemp will teach courses ranging from lower-division calculus courses, to upper-division courses and research-level graduate courses in analysis and probability.

Dr. Kemp works primarily in functional analysis (free probability and q-deformed probability; heat kernel analysis). Additional works are in probability theory (stochastic analysis, random matrices), harmonic analysis (L_p spaces of holomorphic and subharmonic functions), and combinatorics (partition lattices and associated enumeration problems)