Deep learning for remote sensing image classification, segmentation, and object detection; AI foundation models and vision transformers for geospatial analysis; Self-supervised and few-shot learning for remote sensing applications; Intelligent change detection and time-series analysis; Multi-modal data fusion and feature alignment; Explainable AI and uncertainty quantification in Earth observation; On-board AI processing and real-time satellite data analytics

Hyperspectral and multispectral remote sensing for mineral and hydrocarbon exploration; SAR and InSAR for subsurface structure imaging and ground deformation monitoring; Marine remote sensing for ocean dynamics, sea surface temperature, and salinity; AI-assisted detection of marine oil spills, red tides, and algal blooms; Remote sensing for offshore wind energy resource assessment; Seafloor mapping and deep-sea exploration using acoustic and optical remote sensing; Satellite altimetry for ocean circulation and sea-level rise monitoring

Remote sensing of atmospheric composition and air quality; Vegetation monitoring, biomass estimation, and carbon stock assessment; AI-driven ecosystem modelling and biodiversity conservation; Wetland mapping and water resource management using remote sensing; Glacier retreat, permafrost degradation, and climate change impacts; Landslide, subsidence, and earthquake monitoring via InSAR and optical imagery; AI-based early warning systems for geological disasters; Post-disaster damage assessment and rapid response using remote sensing