Edelman received B.S. and M.S. degrees in mathematics from Yale University in 1984, and a Ph.D. in applied mathematics from MIT in 1989 under the direction of Lloyd N. Trefethen. Following a year at Thinking Machines Corporation, and at CERFACS[2] in France, Edelman went to U.C. Berkeley as a Morrey Assistant Professor and Levy Fellow, 1990–93. He joined the MIT faculty in applied mathematics in 1993.
Research
Edelman's research interests include high-performance computing, numerical computation, linear algebra, and random matrix theory.
In random matrix theory, Edelman is known for the Edelman distribution of the smallest singular value of random matrices (also known as Edelman's law[3]), the invention of beta ensembles,[4] and the introduction of the stochastic operator approach,[5] and some of the earliest computational approaches.
In high performance computing, Edelman is known for his work on parallel computing, as the co-founder of Interactive Supercomputing, as an inventor of the Julia programming language and for his work on the Future Fast Fourier transform. As the leader of the Julialab, he supervises work on scientific machine learning and compiler methodologies.
In 2011, Edelman was selected a Fellow of SIAM,[8] "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[9] "for contributions to random matrix theory, numerical linear algebra, high-performance algorithms, and applications."
In 2017, he became an IEEE Fellow Class of 2018[10] "for contributions to the development of technical-computing languages."
In 2019, he was selected as the winner of Sidney Fernbach Award by IEEE Computer Society[11] "for outstanding breakthroughs in high-performance computing, linear algebra and computational science, and for contributions to the Julia programming language."
In 2021, he became an ACM Fellow of Class 2020[12] "for contributions to algorithms and languages for numerical and scientific computing."
^Rudelson, Mark; Vershynin, Roman (2011). "Non-asymptotic Theory of Random Matrices: Extreme Singular Values". Proceedings of the International Congress of Mathematicians 2010 (ICM 2010). Hindustan Book Agency (HBA), India. World Scientific for All Markets Except in India. pp. 1576–1602. arXiv:1003.2990. doi:10.1142/9789814324359_0111. ISBN978-981-4324-30-4.