Event Detection and Causal Reasoning

Here you can find an overview of current research projects within this area. More details and related publications can be found on the respective project pages. Contact information for the team leader can be found down below.

Current Research Projects
Detection and Attribution of Changes in Soil Moisture and Temperature as Affected by Plant Diversity and Climate
Changes in Soil Moisture Teaser

This project aims to study climate variability impacts on plant-soil interactions and carbon cycling that occur across different temporal scales along a gradient of plant diversity. To this end, we aim to combine deep learning capabilities, causal inference theories, and domain knowledge to learn the cause-effect interaction patterns in the observed plant-soil-climate system. We use a unique, highly-resolved dataset on soil moisture and soil temperature from a long-term biodiversity experiment (the Jena Experiment).

Time frame: 2021 – 2024
Deep State Space Models for Understanding Changes in Ecosystems
Deep State Space Models Teaser

Data is ubiquitous in climate and ecosystems sciences. Despite the abundance of data to process, data science has not had a considerable impact on research for a better understanding of the complex dynamics of climate-ecosystem exchange. Accurate modeling of such dynamics is necessary for attribution of climate change, prediction of future data, as well as for planning future actions. Ecological processes exhibit variation over different spatial and temporal scales. Over at least some scales, these processes are nonlinear with possible unobserved causes/confounders.

Time frame: 2021 – 2024
Maha Shadaydeh
Maha Shadaydeh
Dr.-Ing. habil.
Team Leader
Room: 1221
Phone: (+49) 3641 9 46428