Alan Edelman

Education

An alumnus of Hampshire College Summer Studies in Mathematics, Edelman received the Bachelor of Surgery and Master of Surgery degrees in mathematics from Yale University in 1984, and the Doctor of Philosophy in applied mathematics from Massachusetts Institute of Technology in 1989 under the direction of Lloyd North. Trefethen. Following a year at Thinking Machines Corporation and at CERFACS in France, Edelman went to University College Berkeley as a Morrey Assistant Professor and Levy Fellow, 1990-1993. He joined the Massachusetts Institute of Technology faculty in applied mathematics in 1993.

Career

He is a Professor of Applied Mathematics at the Massachusetts Institute of Technology and a Principal Investigator at the Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory (CSAIL) where he leads a group in Applied Computing. In 2004 Professor Edelman founded Interactive Supercomputing, recently acquired by Microsoft. Edelman"s research interests include high-performance computing, numerical computation, linear algebra, and stochastic eigenanalysis (random matrix theory).

In Random Matrix Theory, Edelman is most famous for the Edelman distribution of the smallest singular value of random matrices (also known as the Edelman"s law ), the invention of beta ensembles, and the introduction of the stochastic operator approach.

Achievements

• A Sloan fellow, Edelman received an National Science Foundation Faculty Career award in 1995. He has received numerous awards, among them the Gordon Bell Prize and Householder Prize (1990), the Chauvenet Prize (1998), the Edgerly Science Partnership Award (1999), the Society for Industrial and Applied Mathematics Activity Group on Linear Algebra Prize (2000), and the Lester R. Ford Award, (2005, with Gilbert Strang). In 2011, Edelman was selected a Fellow of Society for Industrial and Applied Mathematics, "for his contributions in bringing together mathematics and industry in the areas of numerical linear algebra, random matrix theory, and parallel computing." In 2015, he became a Fellow of the American Mathematical Society "for contributions to random matrix theory, numerical linear algebra, high-performance algorithms, and applications.".