Agnieszka Borowska is a research and teaching staff member at the Econometrics and Data Science department of the SBE. She is also an Honorary Research Associate at the School of Mathematics and Statistics, University of Glasgow. She holds a PhD from the Vrije Universiteit Amsterdam (2019).
Her research covers a range of areas in Bayesian and computational statistics, with a particular focus on developing efficient algorithms in various contexts such as risk evaluation, state space models, high-dimensional problems with intractable likelihood or black-box optimisation. She works with computational techniques such as Monte chain Monte Carlo, approximate Bayesian computation, Bayesian optimisation, Gaussian processes and density forecasting. She is also interested in machine learning, especially deep learning, which which provides numerous exciting opportunities for flexible dimensionality reduction or robust regression.
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