Prof. Alan Edelman
Professor of Applied Mathematics
Areas of Interest and Expertise
Parallel Scientific Computing
Numerical Analysis
Applied Probability and Statistics
Numerical Linear Algebra
Physical Mathematics
Theoretical Computer Science
Applied Mathematics
Big Data
EigenValues of Random Matrices (some words of explanation  scientific computing as opposed to the term "parallel computation" refers to the solutions of numerical problems using either fast computers or new specialized algorithms. Emphasis is on the solution of an applied problem that usually originates from an engineering or applied math problem rather than the study of the algorithm itself)
Numerical Analysis
Applied Probability and Statistics
Numerical Linear Algebra
Physical Mathematics
Theoretical Computer Science
Applied Mathematics
Big Data
EigenValues of Random Matrices (some words of explanation  scientific computing as opposed to the term "parallel computation" refers to the solutions of numerical problems using either fast computers or new specialized algorithms. Emphasis is on the solution of an applied problem that usually originates from an engineering or applied math problem rather than the study of the algorithm itself)
Research Summary
Dr. Edelman specializes in numerical analysis and parallel computing and is the recognized leader in eigenvalue analyses and in random matrices. He has written important algorithms for parallel computing. His most recent work concerns computer graphics and medical imaging.
Edelman's group analyzes and develops numerical algorithms both mathematically and as software on the world's fastest supercomputers. Research interests are in applications to physics, medicine, and graphics. Some accomplishments include the analysis of a Fourier transform that is nonexact but might be faster in parallel, as well as the development of a parallel MATLAB enhancement that exploits parallelism through polymorphism.
Edelman's group analyzes and develops numerical algorithms both mathematically and as software on the world's fastest supercomputers. Research interests are in applications to physics, medicine, and graphics. Some accomplishments include the analysis of a Fourier transform that is nonexact but might be faster in parallel, as well as the development of a parallel MATLAB enhancement that exploits parallelism through polymorphism.

Projects
December 4, 2017Department of Mathematics
Applied Computing Group (ACG)
Principal Investigator Alan Edelman
October 9, 2013Department of MathematicsApplied Free Probability Theory
Principal Investigator Alan Edelman
January 27, 2009Department of MathematicsComputational Science and Numerical Analysis
Principal Investigator Alan Edelman