Katya Scheinberg

Katya Scheinberg


Harvey E. Wagner Endowed Chair Professor


Ph.D., Columbia University

Research Area: 

Developing Practical Algorithms (and their theoretical analysis) for Various Problems in Continuous Optimization
Convex Optimization
Derivative Free Optimization
Machine Learning
Quadratic Programming

Classes Taught: 

Optimization Models and Applications
Optimization Methods in Machine Learning
Derivative free optimization


Mathematical programming
Linear, convex and nonlinear optimization
Derivative free optimization
Application of optimization to machine learning
Statistics and support vector machines
Conic programming
Interior point methods
Matrix factorizations in interior point methods
Sensitivity analysis

Professor Scheinberg joined the department from the Industrial Engineering and Operations Research Department at Columbia University in 2010. A native of Moscow, she earned her Master’s degree in operations research from the Lomonosov Moscow State University in 1992 and then received her Ph.D. in operations research from Columbia in 1997. Scheinberg was a Research Staff Member at the IBM T.J. Watson Research Center, where she worked on various applied and theoretical problems in optimization, until coming back to Columbia as a visiting professor. Her main research areas are related to developing practical algorithms (and their theoretical analysis) for various problems in continuous optimization, such as convex optimization, derivative free optimization, machine learning, quadratic programming, etc. Scheinberg has also published a book in 2008, titled Introduction to Derivative Free Optimization, which is co-authored with Andrew R. Conn and Luis N. Vicente.