Dasha joined WorldPop in 2026 as a Senior Research Fellow. She is a statistician whose research focuses on developing and applying Bayesian statistical methods to understand and optimise complex, uncertain systems. Her work spans public health, engineering, and industrial applications, with particular interests in uncertainty quantification, model calibration, experimental design, Gaussian process emulation, and machine learning. More broadly, she is interested in making statistical models both more interpretable and more impactful, combining methodological innovation with real-world decision-making challenges.

She contributes to the development of statistical and AI methods for high-resolution population modelling, integrating diverse geospatial and demographic data sources to improve estimates of population distribution and characteristics. Her work focuses on uncertainty-aware modelling, the integration of emerging datasets such as satellite-derived products and other spatial data sources, and the development of scalable methods to support applications in public health, humanitarian response, and sustainable development.

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