## Yurii Nesterov

Yurii Nesterov is a professor at the Université catholique de Louvain, Louvain-la-Neuve, Belgium. He is affiliated with the Center for Operations Research and Econometrics (CORE) and the Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM).

His collaboration with Arkadi Nemirovski, resulting in the book Interior-Point Polynomial Algorithms for Convex Programming, has developed the theory of self-concordant functions to unify global complexity results obtained for convex optimization problems including linear, second-order cone and semi-definite programming. Many scholars consider this book to be the single most important contribution to optimization theory in the past twenty years. More recently, Nesterov is also the author of the monograph Introductory Lectures on Convex Optimization, which develops state-of-the-art theory at a level appropriate for introductory graduate courses. In recent work he has obtained results on the global convergence of a regularized Newton's method for unconstrained optimization and established a theory of smoothing that allows for the applicability of optimal first-order methods to large-scale problems with nondifferentiable objectives. According to Google Scholar, the work of Prof. Nesterov has been cited more than 7,000 times.

Yurii Nesterov is the recipient of several awards and honors, including George B. Dantzig Prize (2000), the John Von Neuman Theory Prize (2009), and an invitation to address the International Congress of Mathematicians (2010). Dantzig Prize, awarded jointly by the Mathematical Programming Society and the Society for Industrial and Applied Mathematics, is awarded for original research, which by its originality, breadth and scope, is having a major impact on the field of mathematical programming, once every three years. The John von Neuman Prize is awarded annually to a scholar who has made fundamental, sustained contributions to theory in operations research and the management sciences.