Professor Margaret H. Wright | |
---|---|
Born | San Francisco, United States | February 18, 1944
Nationality | American |
Education | B.S. in Mathematics, M.S., Ph.D. in Computer Science |
Alma mater | Stanford University |
Occupation | Computer scientist |
Awards | Member of the National Academy of Sciences Member of the National Academy of Engineering Fellow of the American Mathematical Society President of the Society for Industrial and Applied Mathematics (1995-1996) Bell Labs Fellow Editor-in-Chief of SIAM Review (1999-2004) |
Scientific career | |
Fields | Optimization, Linear Algebra, Scientific Computing |
Institutions | NYU Courant, Bell Laboratories, Stanford University (Systems Optimization Laboratory), GTE Sylvania |
Thesis | Numerical Methods for Nonlinearly Constrained Optimization (1976) |
Doctoral advisor | Gene H. Golub, Walter Murray |
Website | cs |
Margaret H. Wright (born February 18, 1944) is an American computer scientist and mathematician. [1] [2] [3] [4] She is a Silver Professor of Computer Science and former Chair of the Computer Science department at Courant Institute of Mathematical Sciences, New York University, with research interests in optimization, linear algebra, and scientific computing. [5] She was elected to the National Academy of Engineering in 1997 for development of numerical optimization algorithms and for leadership in the applied mathematics community. She was elected to the National Academy of Sciences in 2005. She was the first woman to serve as President of the Society for Industrial and Applied Mathematics.
Wright was born in San Francisco in 1944, and spent her early childhood in Hanford, California. [6] Both of her parents were medical doctors. [6] At age 10, her family moved to Tucson, Arizona, where she attended junior and high school. [6] She graduated high school in 1960 at the age of 16. [6] She excelled in school, especially in mathematics. [6]
She went to college at Stanford University, one of the few top-ranked universities that accepted women at that time. [6] She was interested in numerous subjects including literature, French, history, and mathematics, and she decided to major in mathematics thanks to some advice that a degree in mathematics would lead to better job opportunities than a degree in English or history. [2] [6] She planned to have a job because her mother had always worked. [6]
She received a B.S. degree in Mathematics from Stanford University in 1964. [6] She completed an M.S. in Computer Science from Stanford University in 1965. [6]
After completing her M.S., she worked at GTE Sylvania from 1965 to 1971 where she wrote software to implement mathematical simulations. As part of this work, she learned about optimization methods such as the newly published Fletcher-Powell method [7] and linear programming. At that time, it was legal for employers to discriminate against women, and she was earning significantly less than men with lower qualifications. [2] [6] For this and other reasons, she decided to return to Stanford in 1971 to earn her Ph.D. [6]
Wright entered the Ph.D. program in Computer Science at Stanford University in 1971 and was supported by an assistantship from Gene H. Golub. During her Ph.D. studies, Philip E. Gill and Walter Murray, two researchers from the National Physical Laboratory (United Kingdom), came to visit and ended up having a profound impact on her Ph.D. and career. She served as a teaching assistant for a course taught by Walter Murray and go to know him. When Gill and Murray returned to the UK, she went as well for six months and did much of her dissertation research during this period. She returned to Stanford and obtaining her Ph.D. in 1976. [6] [8] Her thesis was on numerical methods for nonlinearly constrained optimization.
After obtaining her Ph.D. in 1976, Wright joined George Dantzig's Systems Optimization Laboratory (SOL) in the Department of Operations Research at Stanford University as a Senior Research Associate. She was eventually joined at SOL by Gill Murray and Philip Gill, whom she had worked with when she was a graduate student, and Michael Saunders. They were known as the "Gang of Four" and published many scientific papers together, always using alphabetical order of their names. [6] In 1984, Karmarkar's algorithm was announced as a polynomial-time algorithm for linear programs, and he came to visit Stanford and present the work. It was immediately clear to the Gang of Four and John Tomlin that this was a special case of barrier methods (the subject of Wright's thesis), and that barrier methods were much more useful than previously believed. [2] [9]
In 1988, Wright moved east and joined Bell Labs, where she was ultimately promoted to Distinguished Member of the Technical Staff. [1] She headed the Scientific Computing Research Department from 1997 to 2000. [1] [10] She was named a Bell Labs Fellow in 1999. [11] Wright was involved in a number of projects during her years at Bell Labs. She worked in wireless systems engineering. [12] She also investigated the popular Nelder–Mead method for derivative-free numerical optimization. [13]
In 2001, Wright joined the Courant Institute of Mathematical Sciences as the Silver Professor of Computer Science and a professor of mathematics. She served as Chair of Computer Science from 2001 to 2009. [14]
Wright has several in numerous service roles including chairing and serving on prize and search committees, serving on a variety of national and international advisory committees, chairing several important reviews, etc. Highlights include the following:
From 1995 to 1996, she served as the (first female) president of the Society for Industrial and Applied Mathematics (SIAM). [15] [16] She served on the SIAM Board of Trustees from 2000 to 2005 and its Council from 1987 to 1989. She was SIAM Vice President at-large from 1990 to 1993.
From 1999 to 2004, she was Editor-in-Chief of SIAM Review. [17]
In 2010, she chaired the UK International Review of the Mathematical Sciences, Engineering and Physical Sciences Research Council. [18]
In 1997, she was elected to the National Academy of Engineering. [2] [19]
In 2000, she was selected to deliver the Noether Lecture, an award of the Association for Women in Mathematics honoring "women who have made fundamental and sustained contributions to the mathematical sciences."
In 2001, she was elected a member of the American Academy of Arts and Sciences. [2] [20]
In 2000, she received the SIAM Award for Distinguished Service to the Profession. [21]
In 2002, she received the AMS Award for Distinguished Public Service. [22]
In 2002, she became a Fellow of the Institute for Operations Research and the Management Sciences. [23]
In 2003, she received an honorary doctorate (D. Math) from the University of Waterloo. [24]
In 2005, she was elected to the National Academy of Sciences. [2] [25]
In 2008, she was awarded an Honorary Doctor of Technology by the Royal Institute of Technology (KTH), Sweden. [26]
In 2009, she became a Fellow of the Society for Industrial and Applied Mathematics (SIAM). [27]
In 2012, she became a fellow of the American Mathematical Society. [28]
In 2013, she was named an honorary member of the London Mathematical Society. [29]
In 2016, she was named a Senior Fellow in the Simons Society of Fellows.
In 2019, she was awarded the John von Neumann Prize "in recognition of her pioneering contributions to the numerical solution of optimization problems and to the exposition of the subject." [30] [31] Her prize lecture was presented at ICIAM in Valencia, Spain on July 16, 2019.
A list of her selected publications includes
George Bernard Dantzig was an American mathematical scientist who made contributions to industrial engineering, operations research, computer science, economics, and statistics.
Linear programming (LP), also called linear optimization, is a method to achieve the best outcome in a mathematical model whose requirements and objective are represented by linear relationships. Linear programming is a special case of mathematical programming.
Jack Joseph Dongarra is an American computer scientist and mathematician. He is a University Distinguished Professor Emeritus of Computer Science in the Electrical Engineering and Computer Science Department at the University of Tennessee. He holds the position of a Distinguished Research Staff member in the Computer Science and Mathematics Division at Oak Ridge National Laboratory, Turing Fellowship in the School of Mathematics at the University of Manchester, and is an adjunct professor and teacher in the Computer Science Department at Rice University. He served as a faculty fellow at the Texas A&M University Institute for Advanced Study (2014–2018). Dongarra is the founding director of the Innovative Computing Laboratory at the University of Tennessee. He was the recipient of the Turing Award in 2021.
Narendra Krishna Karmarkar is an Indian mathematician. Karmarkar developed Karmarkar's algorithm. He is listed as an ISI highly cited researcher.
Society for Industrial and Applied Mathematics (SIAM) is a professional society dedicated to applied mathematics, computational science, and data science through research, publications, and community. SIAM is the world's largest scientific society devoted to applied mathematics, and roughly two-thirds of its membership resides within the United States. Founded in 1951, the organization began holding annual national meetings in 1954, and now hosts conferences, publishes books and scholarly journals, and engages in advocacy in issues of interest to its membership. Members include engineers, scientists, and mathematicians, both those employed in academia and those working in industry. The society supports educational institutions promoting applied mathematics.
Karmarkar's algorithm is an algorithm introduced by Narendra Karmarkar in 1984 for solving linear programming problems. It was the first reasonably efficient algorithm that solves these problems in polynomial time. The ellipsoid method is also polynomial time but proved to be inefficient in practice.
Gene Howard Golub, was an American numerical analyst who taught at Stanford University as Fletcher Jones Professor of Computer Science and held a courtesy appointment in electrical engineering.
Frances Elizabeth Allen was an American computer scientist and pioneer in the field of optimizing compilers. Allen was the first woman to become an IBM Fellow, and in 2006 became the first woman to win the Turing Award. Her achievements include seminal work in compilers, program optimization, and parallelization. She worked for IBM from 1957 to 2002 and subsequently was a Fellow Emerita.
Nimrod Megiddo is a mathematician and computer scientist. He is a research scientist at the IBM Almaden Research Center and Stanford University. His interests include combinatorial optimization, algorithm design and analysis, game theory, and machine learning. He was one of the first people to propose a solution to the bounding sphere and smallest-circle problem.
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Robert J. Vanderbei is an American mathematician and Emeritus Professor in the Department of Operations Research and Financial Engineering at Princeton University.
Alexander (Lex) Schrijver is a Dutch mathematician and computer scientist, a professor of discrete mathematics and optimization at the University of Amsterdam and a fellow at the Centrum Wiskunde & Informatica in Amsterdam. Since 1993 he has been co-editor in chief of the journal Combinatorica.
Michael Alan Saunders is a New Zealand American numerical analyst and computer scientist. He is a research professor of Management Science and Engineering at Stanford University. Saunders is known for his contributions to numerical linear algebra and numerical optimization and has developed many widely used software packages, such as MINOS, NPSOL, and SNOPT.
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Marguerite Straus Frank is a French-American mathematician who is a pioneer in convex optimization theory and mathematical programming.
Ruth Jeannette Williams is an Australian-born American mathematician at the University of California, San Diego where she holds the Charles Lee Powell Chair as a Distinguished Professor of Mathematics. Her research concerns probability theory and stochastic processes.
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