Andrea Walther (born 1970)[1] is a German applied mathematician whose research interests include nonlinear optimization, non-smooth optimization, and scientific computing, and who is known in particular for her work on automatic differentiation. She is professor of mathematical optimization in the institute for mathematics of Humboldt University of Berlin.[2]
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Education and career
After studying business mathematics at the University of Bayreuth beginning in 1991 and earning a diploma in 1996, Walther completed a doctorate at the Dresden University of Technology in 1999.[2] Her dissertation, Program Reversal Schedules for Single-and Multi-processor Machines, was supervised by Andreas Griewank.[3] She completed a habilitation at the Dresden University of Technology in 2008.[2]
She worked as a research assistant and junior professor at the Dresden University of Technology from 2000 to 2008. In 2009, she took a professorship at Paderborn University, and in 2019 she moved to her present position at Humboldt University.[2]
Since 2020 she has been convenor of European Women in Mathematics.[4]
Book
With her advisor Andreas Griewank, Walther is the coauthor of the second edition of the book Evaluating derivatives: principles and techniques of algorithmic differentiation (Society for Industrial and Applied Mathematics, 2008).[5]
References
- ^ Birth year from German National Library catalog entry, retrieved 2021-05-26
- ^ a b c d Kurzer Lebenslauf (in German), retrieved 2021-05-26
- ^ Andrea Walther at the Mathematics Genealogy Project
- ^ Andrea Walther and Kaie Kubjas elected new convenors, European Women in Mathematics, 31 July 2020, retrieved 2021-05-26
- ^ Review of Evaluating derivatives (2nd ed.): Manfred Tasche, Zbl 1159.65026
External links
- Home page
- Andrea Walther publications indexed by Google Scholar
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This page was last edited on 12 January 2023, at 09:58