Ivan Oseledets

Biography

Ivan is an Associate Professor at Skoltech since August 2013, where he is a leader of the Scientific Computing Group. He worked at the Institute of Numerical Mathematics of the Russian Academy of Sciences from 2003, from 2013 – part time. Ivan’s research focuses on the development breakthrough numerical techniques (matrix and tensor methods) for solving a broad range of high-dimensional problems. The main tools are linear algebra, singular value decomposition, low rank approximation of tensors. It involves beautiful math, but has a big programming/software development component. The numerical treatment of high-dimensional problems is notoriously difficult due to the curse of dimensionality: the complexity grows exponentially with the number of indices. High-dimensional problems appear in physics, chemistry, biology and still keep coming. The quest is to find something common that unites different numerical methods for high-dimensional problems. And tensors and their decompositions are one of the most promising approaches. Ivan is the author of more than 40 published/accepted papers in high profile numerical math/computational physics journals, which include SIAM J. Sci. Comput, Computer Physics Communications. He graduated from the Moscow Institute of Physics and Technology in 2006, defended his Ph.D. thesis in 2007 and “doctor of science” dissertation in 2012 (both from the Institute of Numerical Mathematics)

Research Interest

Solution of multidimensional integral and differential equations discretized on fine grids Ab initio computations in quantum chemistry and computational material design Construction of reduced order models for multiparametric systems in engineering Uncertainty quantification in engineering sciences Data mining and compression