Tongshu Zheng received a Bachelor of Science in Environment and Sustainable Development at The Hong Kong Polytechnic University (PolyU). He then attended Duke University where he completed a MS and Ph.D. in Environmental Engineering. His PhD study is of a highly interdisciplinary characteristic that involves a nexus of environmental engineering, computer science, and statistics/machine learning. Tongshu Zheng is at the forefront of environmental analytics with dual specializations in both air pollution study and data science, and close to 7-year experience in air pollution research. He specializes in crafting innovative task-specific advanced statistical and machine learning models to solve the most challenging and pressing air quality problems. His current research foci consist of four main topics: 1) Low-cost air quality sensors siting, field deployment, and performance evaluation; 2) Machine learning approaches for the calibration and surveillance of low-cost air quality sensor networks; 3) Deep learning applied to the next generation low-cost micro-satellite imagery for estimating air pollutant concentrations and detecting localized major air pollutant emission sources at a high spatiotemporal resolution; and 4) Satellite-based remote sensing algorithm development for estimating the reductions in solar energy production by air pollution (e.g., solar PV soiling).