Our research group is at the forefront of innovation in two dynamic areas: AI for Sustainability (AI4S) and AI for Science (AI4Sci). We focus on developing foundational theories and methodologies while driving interdisciplinary applications across diverse domains.
Focus Areas
Computational and Data Sciences
- Computational Optimization and Mixed-Integer Programming
- Data-Driven Decision Making and Multimodal Generative AI
- Quantum-Enhanced AI for Optimization and Deep Learning
- Intelligent Control and IoT for Cyber-Physical Systems
Process, Energy, and Environmental Systems Engineering
- Energy Systems Engineering, Decarbonization, and Carbon Neutrality
- Life-Cycle Sustainability Analytics and Industrial Ecology
- Materials Informatics and Materials Sustainability
- Digital Agriculture and Smart Manufacturing
Research Highlights
Our work addressing pressing global challenges and developing innovative solutions has garnered extensive media coverage.
Below is a selection from our Cornell Chronicle features; additional coverage and in-depth details on specific stories are available on the News page.
Engage with Our Research
We actively contribute to the broader research community by sharing our findings and insights through scientific publications, cover art, and patents. Explore our work:
Review or Perspective Articles
- Wang, Z., & You, F.* (2025). Leveraging generative models with periodicity-aware, invertible, and invariant representations to crystalline materials design. Nature Computational Science, 5, 365–376. [Select Media Coverage] [Cover Art of May 2025 issue of Nature Computational Science]
- Tian, X., Stranks, S.D., Huang, J., Fthenakis, V., Yang, Y., & You, F.* (2025). Perspectives for Sustainability Analysis of Scalable Perovskite Photovoltaics. Energy & Environmental Science, 18, 194-213. [Cover Art of January 2025 issue of Energy & Environmental Science]
- Yuan, W., Chen, G., Wang, Z. & You, F.* (2025). Empowering Generalist Material Intelligence with Large Language Models. Advanced Materials, doi:10.1002/adma.202502771 [Cover Art of August 2025 issue of Advanced Materials]
- Ajagekar, A., Decardi-Nelson, B., Shang, C., & You, F.* (2025). Computer-aided molecular design by aligning generative diffusion models: Perspectives and challenges. Computers & Chemical Engineering, 194, 108989.
- Zhao, B., Richardson, R.E., & You, F.* (2024). Advancing Microplastic Analysis in the Era of Artificial Intelligence: from Current Applications to the Promise of Generative AI. Nexus, 1, 100043. [Cover Art of December 2024 issue of Nexus]
- Li, S., Gao, H.O., & You, F.* (2024). AI for Science in Electrochemical Energy Storage: A Multi-Scale Systems Perspective on Transportation Electrification. Nexus, 1, 100026.
- Li, S., & You, F.* (2024). GenAI for Scientific Discovery in Electrochemical Energy Storage: State-of-the-art and Perspectives from Nano- and Micro-Scale. Small, 20, 2406153. [Frontispiece of December 2024 issue of Small]
- Zhao, X., & You, F.* (2024). From Sustainable Macro Debris Chemical Recycling to Microplastic Reclamation: Overview, Research Challenges, and Outlook. Journal of Cleaner Production, 454, 142281.
- Tao, Y., You, S., Zhu, J., & You, F.* (2024). Energy, climate, and environmental sustainability of trend toward occupational-dependent hybrid work: Overview, research challenges, and outlook. Journal of Cleaner Production, 442, 141083.
- Preuss, N., Alshehri, A.S., & You, F.* (2024). Large Language Models for Life Cycle Assessments: Opportunities, Challenges, and Risks. Journal of Cleaner Production, 466, 142824.
- Decardi-Nelson, B., Alshehri, A.S., Ajagekar, A., & You, F.* (2024). Generative AI and Process Systems Engineering: The Next Frontier. Computers & Chemical Engineering, 187, 108723.
- Zhang, Q., Yan, J.*, Gao, H.O.*, & You, F.* (2023). A Systematic Review on Power Systems Planning and Operations Management with Grid Integration of Transportation Electrification at Scale. Advances in Applied Energy, 9, 100147.
- Bang, R.S., Bergman, M., Li, T., Mukherjee, F., Alshehri, A.S., Abbott, N.L., Crook, N.C., Velev, O.D., Hall, C.K., & You, F.* (2023). An integrated chemical engineering approach to understanding microplastics. AIChE Journal, 69, e18020.
- Zhang, C., Yan, J.*, & You, F.* (2023). Critical metal requirement for clean energy transition: A quantitative review on the case of transportation electrification. Advances in Applied Energy, 9, 100116.
- Zhao, N., Zhang, H., Yang, X., Yan, J.*, & You, F.* (2023). Emerging Information and Communication Technologies for Smart Energy Systems and Renewable Transition. Advances in Applied Energy, 9, 100125.
- Bernal, D.E., Ajagekar, A., Harwood, S.M., Stober, S.T., Trenev, D., & You, F.* (2022). Perspectives of Quantum Computing for Chemical Engineering, AIChE Journal, 68, e17651. [Cover Art of June 2022 issue of AIChE Journal]
- Alshehri, A.S, & You, F.* (2022). Deep learning to catalyze inverse molecular design. Chemical Engineering Journal, 444, 136669.
- Ajagekar, A., & You, F.* (2022). Quantum computing and quantum artificial intelligence for renewable and sustainable energy: A emerging prospect towards climate neutrality. Renewable & Sustainable Energy Reviews, 165, 112493.
- Alshehri, A.S., & You, F.* (2022). Machine learning for multiscale modeling in computational molecular design. Current Opinion in Chemical Engineering, 36, 100752.
- Ajagekar, A., & You, F.* (2022). New Frontiers of Quantum Computing in Chemical Engineering. Korean Journal of Chemical Engineering, 39, 811–820.
- Andersson, M.P., Jones, M.N., Mikkelsen, K.V., You, F., & Mansouri, S.S. (2022). Quantum computing for chemical and biomolecular product design. Current Opinion in Chemical Engineering, 36, 100754.
- Alshehri, A.S, & You, F.* (2021). Paradigm Shift: The Promise of Deep Learning in Molecular Systems Engineering and Design. Frontiers in Chemical Engineering, 3, 700717.
- Pistikopoulos, E.N., Lee, J.H., Misener, R., Mitsos, A., Reklaitis, G.V., Venkatasubramanian, V., You, F., & Gani, R. (2021). Process Systems Engineering – The Generation Next? Computers & Chemical Engineering, 147, 107252.
- Sun, L., & You, F.* (2021). Machine learning and data-driven techniques for the control of smart power generation systems: An uncertainty handling perspective. Engineering, 7 (9), 1239-1247.
- Leonard, K.C., Hasan, F., Sneddon, H.F., You, F.* (2021). Can Artificial Intelligence and Machine Learning Be Used to Accelerate Sustainable Chemistry and Engineering? ACS Sustainable Chemistry & Engineering, 9, 6126–6129.
- Alshehri, A.S, Gani, R., & You, F.* (2020). Deep Learning and Knowledge-Based Methods for Computer-Aided Molecular Design – Toward a Unified Approach: State-of-the-Art and Future Directions. Computers & Chemical Engineering, 141, 107005.
- Bora, R.R., Richardson, R.E., & You, F.* (2020). Resource Recovery and Waste-to-Energy from Wastewater Sludge via Thermochemical Conversion Technologies in Support of Circular Economy: A Comprehensive Review. BMC Chemical Engineering, 2, 8.
- Ning, C., & You, F.* (2019). Optimization under Uncertainty in the Era of Big Data and Deep Learning: When Machine Learning Meets Mathematical Programming. Computers & Chemical Engineering, 125, 434-448.
- Ajagekar, A., & You, F.* (2019). Quantum computing for energy systems optimization: Challenges and opportunities. Energy, 179, 76-89.
- Guillen-Gosalbez, G.*, You, F.*, Galan-Martin, A., Pozo, C., Grossmann, I.E. (2019) Process Systems Engineering thinking and tools applied to sustainability problems: Current landscape and future opportunities. Current Opinion in Chemical Engineering, 26, 170-179.
- Lee, I., Tester, J.W., & You, F.* (2019). Systems analysis, design, and optimization of geothermal energy systems for power production and polygeneration: State-of-the-art and future challenges. Renewable & Sustainable Energy Reviews, 109, 551-577.
- Shang, C., & You, F.* (2019). Data Analytics and Machine Learning for Smart Process Manufacturing: Recent Advances and Perspectives in the Big Data Era. Engineering, 5, 1010-1016.
- Gao, J., & You, F.* (2017). Design and Optimization of Shale Gas Energy Systems: Overview, Research Challenges, and Future Directions. Computers & Chemical Engineering, 106, 699-718.
- Garcia, D.J., & You, F.* (2017). Systems engineering opportunities for agricultural and organic waste management in the food–water–energy nexus. Current Opinion in Chemical Engineering, 18, 23–31.
- Garcia, D.J., & You, F.* (2016). The Water-Energy-Food Nexus and Process Systems Engineering: A New Focus. Computers & Chemical Engineering, 91, 49–67.
- Gong, J., & You, F.* (2015). Sustainable Design and Synthesis of Energy Systems. Current Opinion in Chemical Engineering, 10, 77-86.
- Chu, Y., & You, F.* (2015). Model-based integration of control and operations: Overview, challenges, advances, and opportunities. Computers & Chemical Engineering, 83, 2-20.
- Garcia, D.J., & You, F.* (2015). Supply Chain Design and Optimization: Challenges and Opportunities. Computers & Chemical Engineering, 81, 153-170.
- Yue, D., You, F.*, & Snyder, S.W. (2014). Biomass-to-Bioenergy and Biofuel Supply Chain Optimization: Overview, Key Issues and Challenges. Computers & Chemical Engineering, 66, 36-56.
Partner Research Centers
Our research group partners with leading research centers to drive interdisciplinary solutions in sustainability and scientific innovation.
