Oleg P. Burdakov

Professional Activities

• Editor-in-Chief of the international journal Optimization Methods and Software (Editorial Board, contents)
• Affiliated Faculty of the Center for Applied Optimization, University of Florida, USA
  
• Conference Chair for the 4th International Conference on Optimization Methods and Software (December 16-20, 2017, Havana, Cuba)
• Conference Chair for the 3rd International Conference on Optimization Methods and Software (May 13-17, 2012, Chania, Greece)
• Conference Chair for the Joint EUROPT-OMS Conference on Optimization (July 4-7, 2007, Prague, Czech Republic)
  
• Conference Chair for the 1st International Conference on Optimization Methods and Software (15-18.12.2002, Hangzhou, China)
  
• Workshop organizer for the Workshop on Linear Algebra in Optimization (1996, Albi, France)
• Workshop organizer for the Workshop on Optimum Design of Multibody Systems (1996, Toulouse, France)
•  Member of the Mathematical Optimization Society and the International Society of Global Optimization
• Coordinator for Seminar on Optimization
  

Curriculum Vitae and Publications

• Curriculum Vitae 
• Publications
  

Awards and recognition

• A winner of the International Implementation Challenge in Solving Steiner Tree Problems organized in 2014 by the US Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) which is a collaboration between Rutgers University, Princeton University, and the research firms AT&T, Bell Labs, NEC, and Applied Communication Sciences.
• A winner of the Society for Mathematical Psychology award for the most outstanding paper published in the Journal of Mathematical Psychology in 2016-2019.
• Visiting Scientist award under the Chinese Academy of Sciences President's International Fellowship Initiative for 2017.
• Keynote / plenary invited speaker

Research Interests

Numerical methods for solving optimization problems and systems of nonlinear equations, in particular, Newton-type, stable secant and interpolation methods, globalization strategies. Cardinality-constrained optimization. Inverse problems, multilinear least-squares, nonsmooth optimization and equations. Linear and nonlinear saddle problems and monotone equations. Monotonic regression: data fitting and interpolation. TSP-related problems. Hop-restricted shortest path and Steiner tree problems in graphs.

Software

• Algorithms for solving partially ordered monotonic regression problems in MATLAB
• LMTR suite for unconstrained optimization in MATLAB

Teaching

• Nonlinear optimization, equations and least squares, a course for PhD students (6FMAI07, spring term 2021)
• Optimization, an Advanced Course (TAOP24, spring term 2020)
• Introduction to Optimization (TAOP07, spring term 2019)
• Operations research, an Advanced Course (TAOP62, spring term 2019)
• Introduction to Operations Research (TAOP52, spring term 2019)
• Engineering Optimization (TAOP88, autumn term 2020)

• Operations Research, an Advanced Course (TAOP37, spring term 2015)
• Introduction to Operations Research (TAOP14, autumn term 2016)
• Optimization (TAOP23, autumn term 2014)