I’m a Ph.D. candidate in Uncertainty Quantification and Statistical Learning at the Research Center Trustworthy Data Science and Security (UA Ruhr). Formerly, I worked as an ML Engineer, wrangling with satellite data (mostly Synthetic Aperture Radar).
My research interests are:
- Bayesian uncertainty quantification in Deep Learning
- Efficiently estimating intractable probability densities
- Deep Learning for Synthetic Aperture Radar data
- Calibrating predictive densities for DL tasks
- Modelling disease severity trajectories based on MRI data
- Self-supervised and unsupervised learning
Talks & Slides
Marginally calibrated response distributions for end-to-end learning in autonomous driving, manim-animated slides - Talk at the German Statistical Week, 2022
Marginally calibrated response distributions for end-to-end learning in autonomous driving - accepted for publication in Annals of Applied Statistics, 2022
Take a look at the Rapid Response Insights project I worked on as an ML Engineer at LiveEO to identify storm damages on radar images (German)
Find my CV here.