AWM-MAA 1998 Invited Address
Thursday, July 16, 1998
Ryerson University, Toronto, Canada

Margaret H. Wright

Bell Laboratories, Lucent Technologies
Murray Hill, NJ

The Interior-Point Revolution
in Constrained Optimization

Dr. MARGARET, H. WRIGHT received her B.S. in Mathematics, and M.S. and Ph.D. in Computer Science, from Stanford University. Her research interests include optimization, linear algebra, scientific computing, and scientific and engineering applications. The topic of interior methods, for constrained optimization has been a recurring theme in her work beginning with her 1976 dissertation about methods based on the logarithmic barrier function.

Since 1988 she has been with the Computing Sciences Research Center at Bell Laboratories, Lucent Technologies (formerly AT&T Bell Laboratories). She was named a Distinguished Member of Technical Staff in 1993, and became head of the Scientific Computing Research Department in 1997. She worked from 1976–1988 as a researcher in the Systems Optimization Laboratory, Department of Operations Research, Stanford University.

Wright served during 1995 and 1996 as president of the Society for Industrial and Applied Mathematics (SIAM). She is currently the chair of the Advisory Committee for the Mathematical and Physical Sciences Directorate at the National Science Foundation, and has also served recently on several committees for the National Research Council, the National Science Foundation, and the Department of Energy. She is a member of the Scientific Advisory Council of the Mathematical Sciences Research Institute (MSRI), Berkeley. California. In 1997 she was elected to the National Academy of Engineering.

She is an associate editor of the SIAM Journal on Scientific Computing, the SIAM Journal on Optimization, IEEE Computational Science and Engineering, and Mathematical Programming. In 1999 she will become editor-in-chief of SIAM Review. She is the co-author (with Philip Gill and Walter Murray) of two books, "Practical Optimization" and "Numerical Linear Algebra and Optimization".

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