The Golub Cluster is named in honor of Gene Howard Golub (1932-2007), who was one of the preeminent numerical analysts of his generation. Golub was born in Chicago and received all three of his degrees from the University of Illinois at Urbana-Champaign, completing a B.S. in 1953, M.S. in 1954, and Ph.D. in 1959. His Ph.D. thesis was written under the direction of Abraham Haskel Taub. After a postdoctoral appointment at Cambridge University in England and a brief stint in industry, Golub became a founding faculty member of the newly formed Computer Science Department at Stanford University in 1962, a position he held until his death in 2007. Golub also served in a number of administrative capacities, including terms as Chair of Stanford’s Computer Science Department (1981-1984), President of SIAM (1985-1987), founding Director of Stanford’s Scientific Computing and Computational Mathematics (SCCM) Program (1988-1998), and founding editor of both SIAM Journal on Scientific Computing and SIAM Journal on Matrix Analysis and Applications.
Golub’s principal scientific legacy was his technical and personal leadership in establishing the central position of matrix computations in modern scientific computing. He published more than 170 journal articles with an immense number of co-authors, countless conference papers and technical reports, and several books, including the monumental treatise Matrix Computations, co-authored with Charles Van Loan, which has remained the definitive reference on this topic through multiple editions since its original publication in 1983. The phenomenal range of Golub’s research contributions touch almost every corner of numerical linear algebra and its applications. Golub provided the first viable, robust algorithm for computing the singular value decomposition (in collaboration first with Kahan and then with Reinsch), and also pioneered many of the most fundamental applications of the SVD to a host of problems in linear algebra, statistics, and other fields. He also established QR factorization as the algorithm of choice for linear least squares and related problems in computational statistics. His work with Concus, O’Leary, and others established the preconditioned conjugate gradient method and the closely related Lanczos algorithm as the prototypes and cornerstones of modern Krylov subspace methods for linear systems and eigenvalue problems. Some of Golub’s other pioneering contributions include algorithms for total least squares, generalized cross-validation, fast Poisson solvers, updating matrix factorizations, Gaussian quadrature rules, inverse eigenvalue problems, and most recently acceleration of the page rank algorithm for searching the World Wide Web. For his many lasting research contributions, Golub was elected to the National Academy of Engineering (1990), the National Academy of Sciences (1993), and the American Academy of Arts and Sciences (1994), and was awarded numerous honorary degrees, including from the University of Illinois in 1991.