I am a Principal Member of Technical Staff at Sandia National Laboratories in Livermore, California (currently remote-working from Brooklyn, New York).
My research evolves around uncertainty quantification (UQ), statistical learning and predictability analysis of physical and computational models. I have developed and applied methods for model reduction, UQ and data assimilation, targeting fundamental challenges such as structural errors, intrinsic stochasticity, high-dimensionality, limited data, discontinuities, and rare events, with a range of applications including climate modeling, chemical kinetics, turbulent combustion, fusion science, hardware architecture simulation.
Ph.D. in Applied and Interdisciplinary Mathematics, 2007
University of Michigan, Ann Arbor
B.S. in Applied Mathematics and Applied Physics, 2002
Moscow Institute of Physics and Technology