Alfred Wegener Institute - Helmholtz Centre for Polar and Marine Research (AWI)
- Arctic Environmental Data Analytics
- Facilitating Machine Learning on Super-High Resolution Earth Observation Data for Detecting and Quantifying Arctic Permafrost Thaw Dynamics
- Data fusion using remote sensing data and machine/deep learning techniques to better understand present past and future vegetation dynamics in Central Yakutia
- Quantifying and explaining uncertainty in modeling permafrost thaw under a warming climate
- Tracing 3-D high latitude environmental change with billions of remotely sensed points
German Research Centre for Geosciences (GFZ)
- Online Learning and Decision Making for Real-Time Analytics of Synthetic Aperture Radar (SAR) Data
- Enhanced Computational Approaches for Seismic Risk Assessment of Infrastructure Networks
- Earthquake rupture predictability and the limitations of early warning
- Multi-satellite Approach of Monitoring Atmosphere/Magnetosphere Space Weather Interactions
- Data Mining Dynamic Human Behaviors for Flood Risk Assessment in Coupled Human-Environment Systems
- Bayesian Machine Learning with Uncertainty Quantification for Detecting Weeds in Crop Lands from Low Altitude Remote Sensing
- Predicting geomagnetic conditions on the Earth from multi-spectral images of the Sun by combining data science and physical models
Helmholtz Zentrum Berlin für Materialien und Energie (HZB)
- Optimizing nanotextured solar cells for realistic weather conditions
- Data Analytics for Solar Energy Yield and Optimization Possibilities for Load Management of Electric Buses
- Machine Learning Meets Theoretical Chemistry: Data-driven Analysis of Grapheneoxide
- Data-Driven Time-Dependent Multiphysics Simulation and Optimization of Electron Solvation from Nanodiamonds
- Explainable Artificial Intelligence and Trust in the Energy Sector
- Data-driven performance optimization of coloured and textured solar modules
Max-Delbrück Center for Molecular Medicine (MDC)
- End-to-End Management of Experimental Data Science on Biomedical Molecular Data
- Feature identification for single-cell omics data
- Corpus-wide inference of gene relationships using semantic word representations
- Deep Learning with sparse annotations for the analysis of lung tissue microscopy images
- Identification of disease causing genetic variants by genome-wide predictions of human variant effects
- Multi-resolution models for single-cell genomics data
- Towards molecular digital pathology: leveraging spatial transcriptomics and deep learning to predict gene expression from tissue morphology in solid tumors