معرفی
Alan Edelman 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). He leads the MIT Julia Lab and serves as chief scientist at Julia Computing. Edelman received his BS and MS from Yale University and PhD from MIT in 1989 under Lloyd N. Trefethen.
His research spans high-performance computing, numerical computation, linear algebra, random matrix theory, and scientific machine learning. Edelman is particularly known for his work on the geometry of algorithms with orthogonality constraints, the generalized singular value decomposition, and applications of Lie algebra to matrix factorizations. His computational thinking class has gained worldwide recognition for its unique integration of computer science, mathematics, science, and engineering.
Edelman has received numerous prestigious awards including the Chauvenet Prize (1998), IEEE Computer Society Charles Babbage Award (2015), IEEE Sidney Fernbach Award (2019), and the James H. Wilkinson Prize for Numerical Software. He is a fellow of ACM, SIAM, AMS, and IEEE.
- ACM Fellow (2020) for contributions to algorithms and languages for numerical and scientific computing
- IEEE Fellow (2017) for contributions to the development of technical-computing languages
- AMS Fellow (2015) for contributions to random matrix theory, numerical linear algebra, high-performance algorithms, and applications
- SIAM Fellow (2011) for contributions in bringing together mathematics and industry
Edelman founded Interactive Supercomputing in 2004 (later acquired by Microsoft) and co-created the Julia programming language with Jeff Bezanson, Stefan Karpinski, and Viral Shah. The language solved the long-standing two-language problem in computing, being as easy as Python and as fast as C. Julia is widely used at institutions including MIT, Stanford, BlackRock, US Federal Reserve, and NASA. His 2023 Amazon Research Award focused on Scientific Machine Learning with Application to Probabilistic Climate Forecasting and Sustainability.
As leader of the MIT Julia Lab, Edelman supervises work on scientific machine learning and compiler methodologies. His research group has developed widely adopted tools used across academia and industry for solving large-scale scientific problems in fields ranging from finance to pharmaceuticals.
