Alan Edelman | |
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Born | June 1963 (age 60–61) Brooklyn, New York, U.S. |
Education | Yale University (BS, MS) Massachusetts Institute of Technology (PhD) |
Awards |
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Scientific career | |
Fields | |
Institutions | MIT |
Thesis | Eigenvalues and Condition Numbers of Random Matrices (1989) |
Doctoral advisor | Lloyd N. Trefethen [1] |
Doctoral students | |
Website | math |
Alan Stuart Edelman (born June 1963) is an American mathematician and computer scientist. He is a professor of applied mathematics at the Massachusetts Institute of Technology (MIT) and a Principal Investigator at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) where he leads a group in applied computing. In 2004, he founded a business called Interactive Supercomputing which was later acquired by Microsoft. Edelman is a fellow of American Mathematical Society (AMS), Society for Industrial and Applied Mathematics (SIAM), Institute of Electrical and Electronics Engineers (IEEE), and Association for Computing Machinery (ACM), for his contributions in numerical linear algebra, computational science, parallel computing, and random matrix theory. He is one of the creators of the technical programming language Julia.
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.
Edelman's research interests include high-performance computing, numerical computation, linear algebra, and random matrix theory.
A Sloan fellow, Edelman received a National Science Foundation (NSF) Faculty Career award in 1995. He has received numerous awards, among them the Gordon Bell Prize and Householder Prize (1990), the Chauvenet Prize (1998), [6] the Edgerly Science Partnership Award (1999), the SIAM Activity Group on Linear Algebra Prize (2000), and the Lester R. Ford Award, [7] (2005, with Gilbert Strang).
Jack Joseph Dongarra is an American computer scientist and mathematician. He is a University Distinguished Professor of Computer Science in the Electrical Engineering and Computer Science Department at the University of Tennessee. He holds the position of a Distinguished Research Staff member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory, Turing Fellowship in the School of Mathematics at the University of Manchester, and is an adjunct professor and teacher in the Computer Science Department at Rice University. He served as a faculty fellow at the Texas A&M University Institute for Advanced Study (2014–2018). Dongarra is the founding director of the Innovative Computing Laboratory at the University of Tennessee. He was the recipient of the Turing Award in 2021.
William Gilbert Strang is an American mathematician known for his contributions to finite element theory, the calculus of variations, wavelet analysis and linear algebra. He has made many contributions to mathematics education, including publishing mathematics textbooks. Strang was the MathWorks Professor of Mathematics at the Massachusetts Institute of Technology. He taught Linear Algebra, Computational Science, and Engineering, Learning from Data, and his lectures are freely available through MIT OpenCourseWare.
Lloyd Nicholas Trefethen is an American mathematician, professor of numerical analysis and head of the Numerical Analysis Group at the Mathematical Institute, University of Oxford.
Numerical linear algebra, sometimes called applied linear algebra, is the study of how matrix operations can be used to create computer algorithms which efficiently and accurately provide approximate answers to questions in continuous mathematics. It is a subfield of numerical analysis, and a type of linear algebra. Computers use floating-point arithmetic and cannot exactly represent irrational data, so when a computer algorithm is applied to a matrix of data, it can sometimes increase the difference between a number stored in the computer and the true number that it is an approximation of. Numerical linear algebra uses properties of vectors and matrices to develop computer algorithms that minimize the error introduced by the computer, and is also concerned with ensuring that the algorithm is as efficient as possible.
Nicholas John Higham FRS was a British numerical analyst. He was Royal Society Research Professor and Richardson Professor of Applied Mathematics in the Department of Mathematics at the University of Manchester.
William Douglas Gropp is the director of the National Center for Supercomputing Applications (NCSA) and the Thomas M. Siebel Chair in the Department of Computer Science at the University of Illinois at Urbana–Champaign. He is also the founding Director of the Parallel Computing Institute. Gropp helped to create the Message Passing Interface, also known as MPI, and the Portable, Extensible Toolkit for Scientific Computation, also known as PETSc.
In theoretical computer science, the computational complexity of matrix multiplication dictates how quickly the operation of matrix multiplication can be performed. Matrix multiplication algorithms are a central subroutine in theoretical and numerical algorithms for numerical linear algebra and optimization, so finding the fastest algorithm for matrix multiplication is of major practical relevance.
Richard Steven Varga was an American mathematician who specialized in numerical analysis and linear algebra. He was an Emeritus University Professor of Mathematical Sciences at Kent State University and an adjunct Professor at Case Western Reserve University. Varga was known for his contributions to many areas of mathematics, including matrix analysis, complex analysis, approximation theory, and scientific computation. He was the author of the classic textbook Matrix Iterative Analysis. Varga served as the Editor-in-Chief of the journal Electronic Transactions on Numerical Analysis (ETNA).
The Sidney Fernbach Award established in 1992 by the IEEE Computer Society, in memory of Sidney Fernbach, one of the pioneers in the development and application of high performance computers for the solution of large computational problems as the Division Chief for the Computation Division at Lawrence Livermore Laboratory from the late 1950s through the 1970s. A certificate and $2,000 are awarded for outstanding contributions in the application of high performance computers using innovative approaches. The nomination deadline is 1 July each year.
James Weldon Demmel Jr. is an American mathematician and computer scientist, the Dr. Richard Carl Dehmel Distinguished Professor of Mathematics and Computer Science at the University of California, Berkeley.
Joel Aaron Tropp is the Steele Family Professor of Applied and Computational Mathematics in the Computing and Mathematical Sciences Department at the California Institute of Technology. He is known for work on sparse approximation, numerical linear algebra, and random matrix theory.
Robert James Plemmons is an American mathematician specializing in computational mathematics. He is the emeritus Z. Smith Reynolds Professor of Mathematics and Computer Science at Wake Forest University. In 1979, Plemmons co-authored the book Nonnegative Matrices in the Mathematical Sciences.
Validated numerics, or rigorous computation, verified computation, reliable computation, numerical verification is numerics including mathematically strict error evaluation, and it is one field of numerical analysis. For computation, interval arithmetic is used, and all results are represented by intervals. Validated numerics were used by Warwick Tucker in order to solve the 14th of Smale's problems, and today it is recognized as a powerful tool for the study of dynamical systems.
Beresford Neill Parlett is an English applied mathematician, specializing in numerical analysis and scientific computation.
Daniel Kressner is a German numerical analyst. He has a Chair of Numerical Algorithms and High Performance Computing in the Institute of Mathematics at EPF Lausanne.
A Bohemian matrix family is a set of fixed, finite, matrices population. The term was first used to refer to matrices whose entries are integers of bounded height, hence the name, derived from the acronym BOunded Height Matrix of Integers (BOHEMI). Since then, other populations have been studied. There is no single family of Bohemian matrices. Instead, a matrix can be said to be Bohemian with respect to a set from which its entries are drawn. Bohemian matrices may possess additional structure. For example, they may be Toeplitz matrices or upper Hessenberg matrices.
Daniel B. Szyld is an Argentinian and American mathematician who is a professor at Temple University in Philadelphia. He has made contributions to numerical and applied linear algebra as well as matrix theory.
Françoise Chatelin was a French mathematician whose research interests included spectral theory, numerical analysis, scientific computing, and the Cayley–Dickson construction.