I am a postdoctoral research associate and Schmidt Futures AI2050 Early Career Fellow at the University of Oxford in the Department of Computer Science. My work is centered around scalable and flexible methods for spatiotemporal statistics and Bayesian machine learning with applications in epidemiology. Currently, my focus is on using deep generative modelling to power MCMC inference in classical spatial statistics, as well as adaptive survey design.
Previously, I was at Imperial College London, Department of Mathematics, Statistics section (2021-2022) and did a postdoc in Bayesian Machine Learning at AstraZeneca R&D (2019-2021) where I also collaborated with Prioris.ai. My research at AstraZeneca was dedicated to toxicity prediction and concentration-response curve fitting of large molecules.
In 2019 I completed a PhD in Epidemiology at the Swiss TPH, where I worked on modelling of point patterns using Log-Gaussian Cox Process and detection of hotspots on gridded surfaces.
I am also passionate about community building, diversity and inclusion. I have initiated and participated in a number of outreach activities, creating equitable access and opportunities in education, research and technology.
Download my resumé.
PhD (summa cum laude) in Epidemiology, 2019
Swiss Tropical and Public Health Institute (TPH), University of Basel, Switzerland
Diploma (first class honours) in Mathematics, 2008
Moscow State University, Russia