Agnieszka Borowska
VU Amsterdam

a 'dot' borowska2 'at' vu 'dot' nl
Welcome to my website! I am an adjunct faculty at the School of Business and Economics, Vrije Universiteit Amsterdam. My research interests lie in the area of Bayesian and computational statistics and econometrics. My work has focused on developing efficient sampling-based algorithms for prediction and inference in different contexts, such as time series forecasting, risk evaluation, state space models, and high-dimensional problems with intractable likelihood.
Previously I was a research associate in Statistics at the School of Mathematics and Statistics, University of Glasgow, working with Dirk Husmeier on computer-intensive statistical methods for soft-tissue mechanical models based on partial differential equations. I worked within two EPSRC funded projects, the Closed-Loop Data Science (CLDS) centre and SofTMech. My CLDS work concentrated on incorporating feedback effects into healthcare prognostication systems. In SofTMech, my research was mostly related to inference and uncertainty quantification in biomechanical models.
I did my PhD at the Department of Econometrics and OR (now the School of Business and Economics), Vrije Universiteit Amsterdam, and the Tinbergen Institute, under the supervision of Siem Jan Koopman and Lennart Hoogerheide. I worked on developing methods for accurate and efficient Bayesian inference for time series analysis, with a particular focus on applications in Econometrics and Finance. In Spring 2017 I visited Ruth King at the School of Mathematics, the University of Edinburgh, to work on efficient algorithms for Bayesian inference in state space models.
I hold a Bachelor’s degree in Mathematics from the Faculty of Mathematics, Informatics, and Mechanics, the University of Warsaw, and a Master’s degree in Economics from the Warsaw School of Economics.
In 2021 and 2023 I was on maternity leave.
news
Mar 8, 2025 | My paper with Jon Devlin, Dirk Husmeier and John Mackenzie entilted Approximate Bayesian inference in a model for self-generated gradient collective cell movement has been accepted for publication in Computational Statistics. |
May 1, 2023 | I will be on maternity leave until the end of August 2023. |
Mar 1, 2023 | I have rejoined the School of Business and Economics at the Vrije Universiteit Amsterdam, where I will conduct research on Bayesian econometrics and statistics, and supervise MSc students from our Econmetrics and Data Science programme. |
May 6, 2022 | My paper with Ruth King on Semi-Complete Data Likelihood for efficient state space model fitting has been accepted for publication in Journal of Computational and Graphical Statistics. The journal version can be accessed here. |
Oct 9, 2021 | On the 7th of November 2021 I will talk about our paper Neural Network-Based Left Ventricle Geometry Prediction from CMR Images with Application in Biomechanics at the ML in PL 2021 Conference. |
Oct 9, 2021 | On the 7th of November 2021 I will talk about our paper Neural Network-Based Left Ventricle Geometry Prediction from CMR Images with Application in Biomechanics at the ML in PL 2021 Conference. |
Aug 3, 2021 | Our paper Neural Network-Based Left Ventricle Geometry Prediction from CMR Images with Application in Biomechanics has been accepted in Artificial Intelligence in Medicine. The journal version is available here. |
Apr 12, 2021 | I will be on maternity leave until the end of October 2021. |
Mar 23, 2021 | Our paper Inference in cardiovascular modelling subject to medical interventions has been accepted in the proceedings of ICSTA’21. This is a part of my current research agenda within the Closed-Loop Data Science centre. |
Jan 27, 2021 | I will present our paper on GP-enhanced ABC for chemotaxis at the mini-symposium Stochastic models in biology informed by data during the British Applied Mathematics Colloquium (BAMC). |