About me

I completed a Ph.D. in computer science at the Australian National University under the supervision of Dr. Hassan Hijazi, Prof. Sylvie Thiebaux and Prof. Markus Hegland. In my thesis titled “Global Optimisation for Energy Systems” I developed convex relaxations and generalised convexity conditions for nonconvex nonlinear programming problems and mixed-integer nonlinear programming (MINLP) problems, in particular the optimal power flow problem and a mixed-integer extension of it known as the optimal transmission switching problem. Following that, I worked as a researcher at Zuse Institute Berlin, and from 2023 to 2025, I led the Mathematical Optimization Methods research group at ZIB and coordinated the development of the open-source constraint integer programming solver SCIP. In 2025, I joined the solver development team at GAMS.

My research is focused on the theory and practice of global optimisation of mixed-integer nonlinear programs, with an emphasis on the fundamental understanding of structures and algorithms and motivated by some of the largest current bottlenecks in optimisation algorithms. I am developing a new approach to bridge the gap between convex and nonconvex (MI)NLPs algorithms via novel optimality conditions. Further, I am interested in studying the effects of cutting planes on algorithm performance. Highlights of my previous works include various new cutting planes methodologies for MI(N)LP problems, tight relaxations of MI(N)LPs, methods for polynomial optimisation, and contributions to applications such as energy systems, water treatment and production-maintenance planning. In addition to that, I have made contributions in the form of efficient academic code in multiple open-source projects, the latest of which, SCIP, has become a leading non-commercial MINLP solver.

Contact

Email: bestuzheva@zib.de