World-renowned mathematician at Corvinus

Yurii Nesterov is an internationally highly recognized expert in convex optimization, especially in the development of efficient algorithms and numerical optimization analysis (number of his citations in Google Scholar is 44.311). His primary research areas include Convex optimization, Applied mathematics, Mathematical optimization and Rate of convergence.  

In 1977, Yurii Nesterov graduated in applied mathematics at Moscow State University. Since 1993, he has been working at UCLouvain, specifically in the Department of Mathematical Engineering from the Louvain School of Engineering, Center for Operations Research and Econometrics.   

Yurii Nesterov is widely known as an inventor of the Fast Gradient Method (1983) and developer of Lexicographic Differentiation (1985). He is one of the creators of the modern theory of polynomial-time interior-point methods for structural convex optimization problems.  In the book entitled “Interior-Point Polynomial Algorithms for Convex Programming”, co-authored with A. Nemirovskii, they introduced the theory of self-concordant functions to unify global complexity results obtained for convex optimization problems including linear, second-order cone and semidefinite programming. His subsequent achievements are related to development of Smoothing Technique (2005) and promotion of the higher-order methods (2019). The main impact of these results for practical computations consists in an extension of abilities of the optimization methods above the limits prescribed by complexity theory.  

He accepted our invitation specifically to visit Corvinus Centre for Operations Research. There are many researchers around the world working on interior point algorithms, but the team of CCOR is unique in several ways. As Yurii Nesterov said, “It might be the only research group in Europe that works actively with IPM.”  

He is a recipient of several prestigious scientific awards (Dantzig Prize 2000, von Neumann Theory Prize 2009, Euro Gold Medal 2016, Lanchester Prize, INFORMS, 2022) and is a member of both the National Academy of Sciences and the Academia Europaea.