Summary
Yitao Li is a PhD candidate and environmental engineer with eight years of interdisciplinary experience applying statistics, remote sensing, and machine learning to water quality and pollutant detection. Currently a graduate research assistant at Virginia Tech, his work spans hyperspectral imaging for pollutant identification, thermal hydrolysis-enhanced anaerobic digestion studies, and biosolid dewatering and structural integrity. He has applied geostatistics and 2D/3D visualization to contaminant mapping on Superfund sites, led wastewater-based epidemiology analyses at NYU, and has hands-on lab experience optimizing LCMS methods for antibiotic detection. Comfortable at the intersection of field sampling, lab analytics, and computational modeling, he brings a rare combination of environmental chemistry expertise and advanced statistical/remote-sensing skills. Based in Virginia, he leverages strong publications and cross-institutional collaborations to translate complex sensing data into actionable remediation strategies.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS, Sustainable Urban Environments, GPA 3.71/4.0, Cum Laude, Bachelor of Science - BS, Sustainable Urban Environments, GPA 3.71/4.0, Cum Laude at NYU Tandon School of Engineering
Doctor of Philosophy - PhD, Environmental/Environmental Health Engineering, Doctor of Philosophy - PhD, Environmental/Environmental Health Engineering at Virginia Tech
GPA 3.86/4.00, GPA 3.86/4.00 at Christian Brothers High School
Chinese, English