James Demmel

James Demmel is a Professor Emeritus and Professor in the Graduate School at the University of California, Berkeley, in the Department of Computer Science. His research focuses on Computer Architecture & Engineering (ARC) and Scientific Computing (SCI), with areas including numerical analysis and linear algebra. He holds joint appointments in the Computer Science Division and Mathematics Departments. Demmel's work has contributed to the development of high-performance software for computational science and engineering. His publications span topics such as sparse Gaussian elimination, linear algebra packages, and scalable computing. He is affiliated with the Berkeley Benchmarking and Optimization Group (BeBOP) and the SpeciaLIzed Computing Ecosystems (SLICE) research center.

James W Demmel is a Professor of EECS and Mathematics at UC Berkeley, specializing in high performance computing. His research focuses on developing efficient algorithms and software for numerical linear algebra, with applications in parallel computing and large-scale scientific computations. He has contributed significantly to the development of libraries such as LAPACK and ScaLAPACK, which are essential for solving linear systems on high-performance computing platforms. His work also includes optimizing matrix operations for emerging architectures and improving the accuracy of numerical methods. Demmel's research has had a broad impact on both theoretical and applied computing, particularly in the areas of parallel algorithms and numerical stability.