Recently published a dataset from a complex subsystem of the ESS along with the ground-truth causal graph constructed from expert knowledge. This can be used as a causal discovery benchmark for time series methods.
Research Experience
In collaboration with researchers at the European Spallation Source (ESS), he develops and applies causal inference methods to solve challenging problems at this facility.
Education
Before joining CBS, he was a postdoc at the Department of Automatic Control at Lund University, funded by an International Postdoctoral Grant from the Independent Research Fund Denmark.
Background
Associate professor of statistics at the Department of Finance, Copenhagen Business School. Research focuses on graphical models and causal inference, particularly in stochastic processes. The overarching goal is to develop methods for extracting causal information from partial observation of data, such as point processes, diffusions, and time series.