Influenza A viruses (IAVs) are responsible for substantial human morbidity and mortality and continue to present a substantial public health challenge. Since 2009, novel swine IAVs (SIVs) arising from reassortment between the emerging 2009 pandemic H1N1 virus and enzootic SIVs have frequently been detected in swine populations worldwide, most noticeably in China and the US. The overall goal of this study is to develop and apply interdisciplinary approaches to study and compare the evolution and ecology of SIVs through synergistic studies in China and the US, the two largest pork producing countries on the planet. Specifically, we will 1) identify and determine the evolutionary dynamics of novel SIVs in swine populations in the two countries through influenza surveillance and advanced evolutionary analyses, 2) determine unique, common, and synergistic ecological drivers through geospatial modeling and machine learning, and 3) develop an influenza risk assessment tool using Big Data and artificial intelligence (AI). This study is significant in that: 1) we will illustrate the evolutionary dynamics of SIVs leading to enhanced zoonotic and pandemic risk and identify atypical evolutionary events by defining a baseline for influenza prevalence and evolution; 2) we will identify ecological drivers associated with emergence and spread of novel SIVs within swine populations and at the animal-human interface; 3) we will integrate data from two unique but linked ecological settings using an interdisciplinary approach to facilitate the comprehensive understanding of the evolution and ecology of IAVs within swine populations and at the animal-human interface; and 4) we will develop and share Big Data and AI-based computational tools to advance computational methods linking medical, veterinary, social, and environmental sciences, enhancing our ability to respond to emerging and reemerging infectious diseases.