Amandine Pierrot is a Research Associate in the Department of Mathematical Sciences at the University of Bath, working on new models and analysis techniques for dynamic network data, applied to challenges arising from industry.

Before moving to Bath, Amandine graduated with a PhD from the Technical University of Denmark. Her thesis focused on forecasting offshore wind energy, through the online learning of probability distributions for bounded random variables. Prior to her PhD, she worked for eleven years as a research engineer in statistics for EDF, the main electric utility in France.

Amandine’s research interests include mathematics more broadly related to statistical learning, with a keen interest in time series forecasting and online learning. In particular, she is interested in probabilistic forecasting and forecast verification, hierarchical forecasting, distributed learning, game theory, differential privacy for time series, and modelling and forecasting dynamic network data.