We present a neurosymbolic framework that integrates symbolic representations of PDE structure with deep learning, improving generalization, interpretability, and physical consistency of learned solvers across families of partial differential equations.
@inproceedings{oikonomou2026neurosymbolic,title={A Neurosymbolic Framework for Partial Differential Equations},author={Oikonomou, Orestis and others},booktitle={Proceedings of the 43rd International Conference on Machine Learning (ICML)},year={2026},}
ZeroFlood performs zero-shot flood extent mapping directly from SAR imagery without requiring labeled flood examples, enabling rapid response in regions and events with no available training data.
@inproceedings{oikonomou2026zeroflood,title={ZeroFlood: Zero-Shot Flood Mapping from SAR},author={Oikonomou, Orestis and others},booktitle={European Conference on Synthetic Aperture Radar (EUSAR)},year={2026},}
Approach and findings from the IBM x HuggingFace TerraMind Challenge, where our submission won the first round. Presented at the 2nd NASA/ESA workshop in the US, May 2026.
@misc{oikonomou2026terramind,title={Foundation-Model Approaches to Earth Observation: Lessons from the TerraMind Challenge},author={Oikonomou, Orestis and others},howpublished={2nd NASA / ESA Workshop on AI for Earth Observation},year={2026},note={1st-round winner, IBM × HuggingFace TerraMind Challenge},}