معرفی
Jacob Sanderson is a Researcher at the Computer and Information Sciences Department of Northumbria University. His work focuses on integrating hydrological prior knowledge into explainable deep learning models for flood susceptibility mapping. He holds a PhD in the field and actively contributes to interdisciplinary research bridging artificial intelligence and environmental science.
- Education: Doctor of Philosophy (PhD) in Computer and Information Sciences
His research emphasizes actionable counterfactual explanations (DiPACE) and hybrid gradient-based algorithms (GradCFA) to enhance neural network interpretability. Recent work includes flood inundation mapping using class activation techniques and multi-sensor image fusion for environmental monitoring.
Jacob's publications demonstrate a consistent focus on applying explainable AI to earth observation data, particularly for flood risk assessment. His methodological contributions span feature attribution analysis, semantic segmentation, and plausible counterfactual generation in neural networks.
Current projects involve collaborative research with international teams on remote sensing applications and deep learning interpretability. While specific grant details aren't provided, his work appears to involve multi-institutional partnerships in environmental AI.
