Artificial intelligence (AI) and computing systems are rapidly reshaping science, industry, and society, while also creating new demands for energy, materials, and infrastructure. Our group focuses on understanding the sustainability implications of AI and computing systems across their life cycles. Research in this area connects industrial ecology, life cycle assessment, carbon accounting, and systems modeling to support more transparent, actionable, and scalable sustainability strategies for digital technologies.
Featured Projects
Carbon Connect: An Ecosystem for Sustainable Computing
This project is an exciting 5-year initiative funded by NSF to lay the foundations for sustainable computing. From semiconductors to data centers, we will develop strategies and carbon accounting tools for sustainable computing systems and AI. This is a multi-institutional collaboration that involves Yale University, Harvard University, the University of Pennsylvania, the California Institute of Technology, Carnegie Mellon University, Cornell University, and the Ohio State University.
Project summary can be found here. Project team website can be found here.
Artificial Intelligence Applications in the Chemical Manufacturing Industry
Artificial intelligence has the potential to improve energy efficiency, process control, material design, and environmental performance in chemical manufacturing. However, realizing these benefits requires credible methods for evaluating when AI applications reduce environmental impacts, how to measure benefits, and where unintended trade-offs may occur. This project develops assessment approaches for understanding the energy and environmental implications of AI applications in the chemical industry. This project is part of the Project on the Energy and Environmental Implications of the Digital Economy, sponsored by the Alfred P. Sloan Foundation.
Selected Related Publications
Lee, B., Brooks, D., Benthem, A., Elgamal, M., Gupta, U., Hills, G., Liu, V., Phan, L., Pierce, B., Stewart, C., Strubell, E., Wei, G.-Y., Wierman, A., Yao, Y., and Yu, M. (2025). A view of the sustainable computing landscape. Patterns, 6(7), 101296. https://doi.org/10.1016/j.patter.2025.101296
Liao, M., Lan, K., and Yao, Y. (2022). Sustainability implications of artificial intelligence in the chemical industry: A conceptual framework. Journal of Industrial Ecology, 26, 164–182. https://doi.org/10.1111/jiec.13214
Liao, M. and Yao, Y. (2021). Applications of artificial intelligence-based modeling for bioenergy systems: A review. GCB Bioenergy, 13, 774–802. https://doi.org/10.1111/gcbb.12816