Henri Funk (he / him)
PhD Candidate in Statistics · LMU Munich
I’m a PhD candidate at the Department of Statistics, LMU Munich, supervised by Prof. Dr. Helmut Küchenhoff, working in cooperation with Prof. Dr. Ralf Ludwig’s working group for Applied Physical Geography and Environmental Modeling, a member of the Statistical Consulting Unit (StaBLab), and affiliated with the Munich Center for Machine Learning (MCML).
My research decomposes climate model uncertainty into signal, bias and internal variability, with a focus on droughts: multivariate bias correction with vine copulas, uncertainty quantification, and algorithm-agnostic interpretability for clustering.
Starting October 2026 upcoming
I’ll be joining BayWaT-AI, a new project on river water temperatures and riverine heatwaves in Bavaria, developing deep-learning models to predict stream temperature extremes under climate change. More details on the Projects page.
Research interests
My work centers on droughts and climate extremes: decomposing climate model uncertainty into bias, internal variability and forced signal, and carrying that decomposition through to drought characterisation and forecasting.
- Uncertainty decomposition and quantification (aleatoric/epistemic)
- Multivariate bias correction & copula modelling
- Generalised additive models
- Deep learning for probabilistic forecasting
- Explainable / algorithm-agnostic machine learning
- Climate models, specifically single-model large ensembles (SMILEs)
- Droughts and compound climate extremes
- Internal variability
- European drought hotspots under future warming
- Hydrology & meteorology, streamflow deficits
- River water temperatures & riverine heatwaves