Yuchen Dai is a machine learning engineer and urban planner with a decade of experience applying GIS, remote sensing, and data science to urban and resource planning problems. He combines advanced spatial analysis skills (ArcGIS Pro, ENVI, QGIS) with programming expertise in Java, Python/ArcPy, and R to build reproducible workflows—ranging from 3D geological models for coal resource optimization to city-scale dashboards for smart-city benchmarking. Currently pursuing a Master’s in Urban Planning at Columbia, he has supported academic and government projects across China, Brazil, and the U.S., translating complex spatial data into actionable metrics and web-based map resources. Notably, he programs sensors for long-term data collection and automates geospatial pipelines, a hands-on capability that bridges field data acquisition and machine learning analysis. Bilingual in Mandarin and English, he brings both rigorous research experience from institutions like the Chinese Academy of Sciences and practical planning delivery for municipalities.
10 years of coding experience
Master's degree, City/Urban, Community and Regional Planning, Master's degree, City/Urban, Community and Regional Planning at Columbia University in the City of New York
Bachelor of Arts - BA, City/Urban, Community and Regional Planning, GPA: 3.71, Bachelor of Arts - BA, City/Urban, Community and Regional Planning, GPA: 3.71 at Miami University
Doctor of Philosophy - PhD, City/Urban, Community and Regional Planning, Doctor of Philosophy - PhD, City/Urban, Community and Regional Planning at University of North Carolina at Chapel Hill
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