I am a postdoctoral researcher at Zuse Institute Berlin and the Interactive Optimization and Learning (IOL) Lab, leading the Global Optimization research area within IOL and coordinating the development of the open-source constraint integer programming solver SCIP.
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 Optimization for Energy Systems” I developed convex relaxations and generalized convexity conditions for nonconvex nonlinear programming problems and mixed-integer nonlinear programming problems, in particular the optimal power flow problem and a mixed-integer extension of it known as the optimal transmission switching problem. Prior to this, I obtained a diploma in applied mathematics and informatics from the State Management University in Moscow.
I work on creating new techniques to efficiently solve mixed-integer nonlinear programs to global optimality and to improve the performance of branch-and-bound methods. I develop relaxations and cutting planes for convex and nonconvex MINLPs, in particular problems involving bilinear products, disjunctive structures and polynomials. In addition to conventional relaxation approaches, I work on applying nonnegativity certificates such as SONC and SAGE to finding lower bounds on high degree polynomial optimization problems. Furthermore, I am interested in generalized convexity and its applications to global optimization. I implement these methods within SCIP, ensuring their computational usefulness on large heterogeneous sets of instances.