Katya Scheinberg
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Columbia University (PhD, 1997)
Katya Scheinberg | |
|---|---|
| Education | Moscow State University Columbia University (PhD, 1997) |
| Scientific career | |
| Fields | applied mathematics |
| Institutions | |
| Doctoral advisor | Donald Goldfarb |
Katya Scheinberg is a Russian-American applied mathematician known for her research in continuous optimization and particularly in derivative-free optimization. She is a professor in the School of Industrial and Systems Engineering at Georgia Institute of Technology.
Scheinberg was born in Moscow.[1] She completed a bachelor's and master's degree in computational mathematics and cybernetics at Moscow State University in 1992,[2] and earned a Ph.D. in operations research at Columbia University in 1997. Her dissertation, Issues Related to Interior Point Methods for Linear and Semidefinite Programming, was supervised by Donald Goldfarb.[2][3]
Scheinberg worked for IBM Research at the Thomas J. Watson Research Center from 1997 until 2009. After working as a research scientist at Columbia University and as an adjunct faculty member at New York University, she joined the Lehigh faculty in 2010. Scheinberg became Wagner Professor at Lehigh in 2014.[2] In 2019 she moved to Cornell University where she was a professor in the School of Operations Research and Information Engineering.[4] In July 2024 she moved to Georgia Tech.[5]
Scheinberg has been editor-in-chief of the SIAM-MOS Book Series on Optimization since 2014, and was the editor of Optima, the newsletter of the Mathematical Programming Society, from 2011 to 2013.[2]
Research
Scheinberg works on the intersection of optimization and machine learning, in particular on kernel support vector machines.[6]
With Andrew R. Conn and Luís Nunes Vicente, Scheinberg authored the book Introduction to Derivative Free Optimization (SIAM Press, 2008).[7]
