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| Alan Edelman | |
|---|---|
| Name | Alan Edelman |
| Birth date | 1963 |
| Birth place | Boston |
| Nationality | United States |
| Fields | Applied mathematics, Computer science, Numerical linear algebra |
| Workplaces | Massachusetts Institute of Technology, National Science Foundation, Mathematics and Computer Science Division, Argonne National Laboratory |
| Alma mater | Harvard University, Massachusetts Institute of Technology |
| Doctoral advisor | Gilbert Strang |
| Known for | Julia (programming language), random matrix theory, eigenvalue algorithms |
Alan Edelman Alan Edelman is an American mathematician and computer scientist known for work in numerical linear algebra, scientific computing, and for cofounding the Julia (programming language). He has held positions at Massachusetts Institute of Technology, Microsoft Research, and Goldman Sachs, and has collaborated with researchers at Argonne National Laboratory, Lawrence Berkeley National Laboratory, and Los Alamos National Laboratory. His research spans interactions with topics in random matrix theory, high-performance computing, and applied probability.
Edelman was born in Boston and raised with early exposure to mathematics and computing through connections to institutions like Harvard University and Massachusetts Institute of Technology. He completed undergraduate studies at Harvard University where he studied under faculty including Gilbert Strang-adjacent networks and later pursued doctoral work at Massachusetts Institute of Technology under the supervision of Gilbert Strang, engaging with seminal figures in numerical linear algebra and applied mathematics. During this period he interacted with scholars associated with Institute for Advanced Study, Courant Institute of Mathematical Sciences, Princeton University, and Stanford University through conferences and collaborations.
Edelman joined the faculty at Massachusetts Institute of Technology before moving to positions that connected academia, national laboratories, and industry, including engagements with Argonne National Laboratory, Lawrence Berkeley National Laboratory, and Los Alamos National Laboratory. He has been involved with funding agencies and program directors at the National Science Foundation and has collaborated on projects with DARPA, Department of Energy, and industrial research groups at IBM Research, Microsoft Research, Google Research, and Intel laboratories. His scholarly network includes collaborators from University of California, Berkeley, University of Michigan, University of Cambridge, University of Oxford, ETH Zurich, École Polytechnique Fédérale de Lausanne, Weizmann Institute of Science, Tel Aviv University, University of Toronto, University of Washington, Columbia University, and California Institute of Technology.
Edelman made foundational contributions to eigenvalue algorithms, spectral theory, and the application of random matrix theory to practical computations. His work connects to classical results from John von Neumann, Eugene Wigner, and Marcel Riesz-era influences, and to modern developments influenced by researchers at Institute for Advanced Study and the Courant Institute. He published influential analyses relating to eigenvalue spacing, condition numbers, and perturbation theory, interfacing with advances by James Wilkinson, Gene Golub, Alan J. Hoffman, and Lloyd N. Trefethen. Edelman’s studies on the statistical behavior of eigenvalues have implications for fields linked to statistical mechanics, quantum chaos, and algorithms used at National Center for Supercomputing Applications and Oak Ridge National Laboratory.
He has contributed to theory and practice of high-performance linear algebra libraries and algorithmic techniques used in LAPACK, BLAS, and parallel implementations on architectures from Cray Research and IBM supercomputers to clusters built with NVIDIA GPUs and AMD processors. His research touches topics pursued at Simons Foundation, Howard Hughes Medical Institute, and groups at Flatiron Institute and Zuse Institute Berlin. Collaborations extended to specialists in optimization at Princeton University and Cornell University and to applied users in bioinformatics and signal processing at Broad Institute and MIT Lincoln Laboratory.
Edelman is a cofounder of the Julia (programming language), working with Jeff Bezanson, Stefan Karpinski, and Viral Shah to create a high-performance language bridging MATLAB, Python (programming language), and R (programming language). He contributed to the development of packages and tools integrating with BLAS, LAPACK, and parallel runtimes used by HPC centers such as Argonne Leadership Computing Facility and National Energy Research Scientific Computing Center. His entrepreneurship spans roles at startups and collaborations with Goldman Sachs, Two Sigma, Jane Street, and venture-backed initiatives linked to Y Combinator-style ecosystems. He has engaged with open-source communities alongside organizations like the Python Software Foundation, NumFOCUS, and The Julia Computing Company.
Edelman has received recognition from professional societies and institutions including fellowships and prizes associated with Society for Industrial and Applied Mathematics, American Mathematical Society, and programmatic awards from National Science Foundation and Department of Energy. His election to fellowships and invited lectures has placed him in company with recipients of the Guggenheim Fellowship, Simons Fellowship, and invited speakers at meetings of the American Mathematical Society, SIAM Annual Meeting, and conferences such as NeurIPS, ICLR, and ICML. He has been acknowledged by centers including MIT Computer Science and Artificial Intelligence Laboratory and national labs including Argonne National Laboratory and Lawrence Berkeley National Laboratory.
Edelman’s career bridges academia, national laboratories, and industry, influencing pedagogy and software ecosystems at institutions like Massachusetts Institute of Technology, Harvard University, and University of California, Berkeley. His mentorship has extended to doctoral students and postdocs who have taken positions at Princeton University, Stanford University, University of Michigan, Cornell University, and technology firms such as Google, Facebook, and Microsoft. His legacy includes shaping computational practice through links to LAPACK, the Julia community, and cross-disciplinary collaborations with fields represented at Broad Institute, Flatiron Institute, Simons Foundation, and major conferences including SIAM Annual Meeting and NeurIPS.
Category:American mathematicians Category:Computer scientists