
Dr Odysseas Pappas
MEng, PhD
Current positions
Senior Research Associate
School of Computer Science
Contact
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Research interests
My main research interests revolve around signal processing for remote sensing and geospatial applications, with a particular focus on SAR processing. More specifically these include inverse imaging problems, compressive sampling, machine learning and generative AI methods for inverse problems, object/target detection, superpixel segmentation and classification, statistical modelling, anomaly detection and multimodal image fusion.
My current research focuses on the use of diffusion models for compressive SAR imaging, as well as on ship and ship wake detection and classification in SAR images for maritime monitoring applications. Prior projects have included work on InSAR for volcano deformation monitoring, river segmentation, mapping, and analysis from SAR imagery, as well as applications of compressive sampling to biomedical imaging modalities.
Projects and supervisions
Thesis supervisions
Publications
Recent publications
07/03/2025Deep Unfolded Approximate Message Passing for Quantitative Acoustic Microscopy Image Reconstruction
ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Diffusion probabilistic models for compressive SAR imaging
Proceedings of SPIE
Measuring topographic change after volcanic eruptions using multistatic SAR satellites
Remote Sensing of Environment
R-Sparse R-CNN
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
On the Modelling of Ship Wakes in S-Band SAR Images and an Application to Ship Identification
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium