Fengqi You, the Roxanne E. and Michael J. Zak Professor in Energy Systems Engineering, and his research at the Smith School are exemplars of interdisciplinary innovation, focusing on the development and application of advanced computational models, optimization algorithms, and artificial intelligence (AI) techniques. You’s work spans across multiple domains, including energy systems, digital agriculture, materials informatics, and sustainability, addressing critical global challenges such as energy efficiency, decarbonization, and food sustainability.
You leads the Process-Energy-Environmental Systems Engineering (PEESE) research group, where one of the key areas of exploration is the development of quantum computing and AI technologies to optimize energy systems. A 2024 study from the group highlighted the application of variational quantum circuits for robust optimization in AI-driven data centers. This research demonstrated significant potential in reducing both energy consumption and carbon emissions, showcasing how quantum computing can enhance the sustainability of large-scale data operations.
Another area of focus for the PEESE group is environmental sustainability, particularly the mitigation of pollution. For instance, a 2024 study on microplastic pollution examined the human dietary intake of microplastics across various countries. The findings suggest that effective plastic debris removal could substantially reduce this intake, offering a critical strategy for mitigating the environmental and health impacts of plastic pollution.
The group also contributes to the sustainable production of green hydrogen using offshore wind energy. A recent study by PEESE explored the feasibility of using offshore wind power to produce green hydrogen, emphasizing its potential for decarbonizing coastal regions of the United States. This work aligns with broader efforts to transition to renewable energy sources and reduce reliance on fossil fuels.
Beyond these areas, You’s research extends into digital agriculture, where his team applies machine learning and optimization to improve food production systems. By integrating data from weather forecasting and regulatory information, his research helps crop growers optimize operations and conserve natural resources, contributing to more sustainable agriculture practices.
You’s interdisciplinary approach is widely recognized, with his research being featured in leading scientific journals and honored with many national and international awards. His work continues to push the boundaries of sustainability and technological innovation, making significant impacts across multiple fields.