Data assimilation and uncertainty quantification
Work Package 6
Data assimilation and uncertainty quantification
Vision
To process geophysical datasets for detection, estimation and prediction based on statistical machine learning techniques.
What we will do
- Coherent probabilistic data assimilation of diverse geophysical data sources.
- Transfer learning, building on recent machine learning approaches reducing the need for expensive real-world measurements.
- Optimise available communication and computational resources.
- Identify effective data gathering approaches for improved decision support systems.
WP Leader
Key Personnel
-
Geetartha Dutta
-
Marcus Gehrmann
PhD Candidate -
The Tien Mai
Postdoctoral Fellow -
Ole Jakob Mengshoel
Professor -
Giampiero Salvi
Professor -
Pierluigi Salvo Rossi
Professor; Deputy Director; Head of the Ph.D. Program in Electronics and Telecommunication -
Håkon Tjelmeland
Professor -
Khanh Truong
PhD Candidate