Wanying Chen's academic and research pursuits cover atmospheric modelling, the implications of climate change on air quality, and the application of machine learning in environmental science. In her previous research, she applied numerical models (WRF–CAMx, WRF–CMAQ) and utilised source apportionment modules to predict air pollution and investigate its sources. By integrating numerical models with hybrid data fusion techniques and machine learning, Wanying enhanced the accuracy of pollution predictions and source apportionment. Additionally, she delves into the intricate relationship between climate change and air quality, focusing on how climate change influences atmospheric conditions and pollutants. Her work explores the driving factors behind air quality changes under various Shared Socioeconomic Pathways (SSPs) and examines the broad socioeconomic impacts of air quality. Relevant articles have been published in Environmental Science and Technology, Acta Scientiae Circumstantiae, and Science of The Total Environment.