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David Brüggemann
David Brüggemann

David Brüggemann

Senior Data Scientist
Research
(Alumni)

David joined SDSC in February 2024. Before that, he completed his doctorate in computer vision at ETH Zürich. His doctoral thesis focused on multi-task learning and domain adaptation in neural networks for applications in visual recognition. In addition, he gained research experience in transfer learning and multi-modal learning. David’s current work at SDSC ranges from large-scale vegetation modeling based on satellite imaging to analysis of electronic health records with deep learning methods.

Projects

LUCID National Data Stream

In Progress
Low Value of Care in Medical Hospitalized Patients - a National Data Stream on Quality of Care in Swiss University Hospitals
Health & Biomedical

Dataspectrum4CVD

In Progress
Integrating medical image data and assessments for personalized cardiovascular risk estimation
Health & Biomedical

DIMPEO

Completed
Detecting drought impacts on forests in earth observation data
Climate & Environment

Publications

Hassan, M.; Stapf, S.; Rahimi, A.; Rezende, P. M. B.; Haghighi, Y.; Brüggemann, D.; Katircioglu, I.; Zhang, L.; Chen, X.; Saha, S.; et al. "GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control" Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 22404-22415 2025 View publication
Hassan, M.; Stapf, S.; Rahimi, A.; Rezende, P.; Haghighi, Y.; Brüggemann, D.; Katircioglu, I.; Zhang, L.; Chen, X.; Saha, S.; et al. "Gem: A generalizable ego-vision multimodal world model for fine-grained ego-motion, object dynamics, and scene composition control" Proceedings of the Computer Vision and Pattern Recognition Conference 22404–22415 2025 View publication

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