With the explosion of Earth observation (EO) data, fast EO market growth is bottlenecked by the lack of intelligent analytics that can automatically transfer large-volume, ever-increasing, noisy, heterogeneous raw EO data into compact, real-time, value-added information products. I tailor-design cutting-edge AI solutions to enable automatic generation of scalable EO information products in a high-precision, fast and cost-effective manner to better support various key applications in environmental monitoring, resource exploration and climate change studies. I have strong expertise on AI and machine learning (ML), geospatial data science, different remote sensing techniques (i.e., Hyperspectral, Lidar and SAR remote sensing), and their environmental monitoring applications, e.g., land cover/use classification, hyperspectral mapping of biophysical, biochemical, and geochemical parameters, oil spill detection, and high-resolution Pan-Arctic sea/lake ice mapping.