Jun Xiong is an AI/ML engineering lead and seasoned geospatial scientist with over a decade of experience applying remote sensing, machine learning, and cloud computing to real-world problems across industry and government. He has led production-grade ML lifecycles—from satellite data ingestion and large-scale image segmentation to MLOps and HIPAA-compliant AI deployment—bridging domain experts (e.g., psychiatrists, agronomists) and engineering teams. His work spans NASA and USGS research to commercial productization, including global cropland mapping, real-time wildfire detection, and agronomic layer generation to boost crop models. Jun is skilled at scaling geospatial pipelines using hybrid cloud/HPC approaches and making complex datasets accessible to non-experts through well-designed tools and knowledge bases. Based in Orinda, CA, he combines rigorous academic training (PhD in Geosciences) with practical mentorship and governance experience, often improving team productivity by introducing reproducible workflows and standards. An uncommon thread in his profile is translating satellite-derived signals into medically and agriculturally actionable insights, not just maps or models.
10 years of coding experience
15 years of employment as a software developer
Doctor of Philosophy - PhD Geological and Earth Sciences/Geosciences, Doctor of Philosophy - PhD Geological and Earth Sciences/Geosciences at University of Chinese Academy of Sciences
Bachelor of Engineering - BE Geographic Information System, Bachelor of Engineering - BE Geographic Information System at Nanjing University
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