My current affiliation: The University of Sheffield, UK; School of Mathematics and Statistics. web-page
2018 — Postdoctoral research associate — Brown University, USA
2017-2018 — Postdoctoral fellow — KAUST, Saudi Arabia
2017 — PhD in Statistical Science — Duke University, USA
2016 — Graduate Research Assistant — Los Alamos National Lab, USA
2014 — MSc in Statistical Science — Duke University, USA
2011 (2009) — MSc (BSc) in Applied Mathematics and Computer Science — ITMO University, Russia
My previous web-page at Duke University, Department of Statistical Science.
I was born in Russia (the former Soviet Union). Before coming to Duke, I studied at the Academic Gymnasium of Saint Petersburg State University. I received a BSc and a MSc in Applied Mathematics and Computer Science from Saint Petersburg State University of Information Technologies, Mechanics and Optics.
After moving to the United States, I earned a MSc in Statistical Science en route to PhD in 2014. In the summer of 2016 I completed an internship at Los Alamos National Laboratory, CCS-6 Statistical Science group guided by my mentor James R. Gattiker.
I completed PhD in Statistical Science at Duke University, USA in 2017. The main outcome of my studies is my dissertation ''On Uncertainty Quantification for Systems of Computer Models''.
In my dissertation I have developed and analyzed a fully probabilistic Bayesian framework for testing theoretical scientific models, often realized as scientific computer models, with respect to experimental data. Scientific computer models appear in fundamental science and engineering. This Bayesian statistical framework allows to provide probabilistic answers to analysis of agreement between the theory and experimental data.
During my studies I have produced good number of important negative results (documented in my dissertation) with respect to current practice in statistical science. Such results are unwelcome for publishing in statistical journals or paper books. The majority of materials in such journals and books are non-scientific, lacking any mathematical justification and fundamental reasoning, and, therefore, simply inadequate.