dr. ir. Thomas Mortier
Thomas Mortier specializes in uncertainty-aware machine learning for (sub)seasonal forecasting of hydro-climatic extremes.
Bio
After earning a Master of Science in Computer Science Engineering and a Master of Science in Statistical Data Analysis from Ghent University in 2017, I joined the KERMIT research group as a teaching assistant within the Department of Data Analysis and Mathematical Modelling at the Faculty of Bioscience Engineering, Ghent University. In this role, I contributed to courses on statistics and machine learning while mentoring several master's thesis students. My research at the time focused on developing algorithms for uncertainty-aware machine learning, with applications in applied biological and life sciences. Currently, my research is centered on predicting compound dry-hot events using machine learning approaches informed by physics and causal discovery.
Trajectory
- 2024–Present: Postdoctoral researcher | Ghent University, Hydro-Climate Extremes Lab
- 2023–2024: Postdoctoral researcher | Ghent University, KERMIT
- 2017–2023: Teaching assistant | Ghent University, KERMIT
- 2010-2017: MSc in Computer Science Engineering, MSc in Statistical Data Analysis | Ghent University
Contact
E-mail: ThomasF.Mortier@UGent.be
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