Summary
Wanwan Liang is a postdoctoral researcher and applied data scientist with eight years of experience combining remote sensing, machine/deep learning, and geospatial analysis to address environmental and agricultural challenges. Her work spans high-impact projects from wall-to-wall biomass mapping across boreal and Arctic North America to hyperspectral disease detection and invasive species forecasting, often turning methods into reusable Python and R packages. She has led cross-disciplinary teams in industry and academia, translating complex ecological questions into operational models for product development and climate/carbon assessments. Trained in statistics and integrated pest management (MS, PhD), she blends rigorous quantitative methods with domain expertise in plant protection. Based in Cary, NC, she is motivated by collaborative success and advancing solutions that scale from field plots to continental maps. An underappreciated strength is her track record of productizing research code into tools that accelerate decision-making in both corporate and research settings.
8 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Plant Protection and Integrated Pest Management, Master of Science - MS, Plant Protection and Integrated Pest Management at China Agricultural University
Master of Science - MS, Statistics, Master of Science - MS, Statistics at University of Tennessee, Knoxville