TITLE:


AI-LEAF: The National AI Research Institute for Land, Economy, Agriculture and Forestry

PRESENTER:

Shashi Shekhar : Biography ( 100 words, 400 words ), Picture ( 1 , 2 )

AFFILIATION:

Computer Science and Engineering Department, University of Minnesota.

Webpages:

official , personal , wikipedia entry

VIDEOS:

BROCHURES and POSTERS:

SLIDES:

ABSTRACT:

The AI-LEAF (National AI Institute for Land, Economy, Agriculture and Forestry) aims at accelerating adoption of resilient and sustainable land-management practices. These practices are of interest to farmers, foresters, companies, and policy-makers due to past experiences (e.g., Dust Bowl years) and improved understanding of ecosystem services. Currently, land-stewards are aware of many such practices and face a key decision: which practice should be used where, when and for how long? Challenges include the trade-offs between short-term and long-term economic and ecosystem considerations and confounding factors such as cropping, soil condition, and weather. To support such decisions via field-to-market decision support tools, AI-LEAF is developing novel AI-informed models to improve prediction accuracy, providing AI-driven higher resolution maps to improve data quality, and probing AI-guided surrogate models and multi-objective Pareto optimization algorithms to speed-up computational response time. However, traditional AI faces challenges such as out of sample prediction, hard constraints (e.g., conservation of mass or energy), etc. Thus, AI-LEAF is advancing AI by incorporating laws of nature to improve prediction out-of-sample, and combining learning and reasoning, etc. AI-LEAF is also expanding rural and urban AI workforce and catalyzing a cross-sector collaboration nexus.

AI-LEAF is a joint effort currently involving the University of Minnesota Twin Cities (lead), Colorado State University, Cornell University, Delaware State University, North Carolina State University, and Purdue University.

KEYWORDS:

ACKNOWLEDGMENTS: This work is supported by AFRI Competitive Grant No. 2023-67021-39829 / Project No. MINW-2023-03616 from the USDA National Institute of Food and Agriculture as well as the National AI Research Institute program of the National Science Foundation.

RESOURCES

  1. AI-LEAF project website
  2. Curbing Climate Change with Artificial Intelligence , Soundbyte Magazine, Computer Science and Engineering Department, University of Minnesota, Oct. 2023.(z.umn.edu/Soundbyte2023)
  3. AI Climate Institute is a leader in climate-smart agriculture and forestry. , University of Minnesota, September 2024. The article (and video) feature interviews with farmers discussing the challenges they face and how AI-CLIMATE is leveraging and strengening AI to provide solutions to promote sustainable, economically viable, and environmentally friendly practices.
  4. Looking back, looking ahead: Strategic initiatives in AI and NSF's AI Institutes Program, James Donlon, and Ashok Goel, AAAI Magazine, 07 August 2023. https://doi.org/10.1002/aaai.12107
  5. Vikram Adve, Steve Brown, Alan Fern, Baskar Ganapathysubramanian, Ananth Kalyanaraman, Shashi Shekhar, Ilias Tagkopoulos, Jessica Wedow, Advancing AI in Agriculture through Large-Scale Collaborative Research, Communications of the ACM (accepted).
  6. Shengya Zhang, Arun Sharma, Majid Farhadloo, Mingzhou Yang, Ruolei Zeng, Subhankar Ghosh, Yao Zhang, Mu Hong, Licheng Liu, David Mulla and Shashi Shekhar, Towards Surrogate Models with Hybrid Spatial Neural Networks: A Summary of Results, ACM SIGSPATIAL 8th International Workshop on GeoSpatial Simulation (GeoSim 2025) November 2025, Minneapolis, MN, USA.
  7. Biden-Harris Administration Announces New Investments to Improve Measurement, Monitoring, Reporting and Verification of Greenhouse Gas Emissions through President Biden’s Investing in America Agenda, July 23rd, 2023. refers to Federal Strategy to Advance Greenhouse Gas Measurement and Monitoring for the Agriculture and Forest Sectors, July 12th, 2023 and webinar on USDA Invests in Improved GHG Measurement, Monitoring, Reporting and Verification for Ag and Forestry July 21, 2023.
  8. The Time is Right for a Forest Moonshot in the U.S., Sacha Spector (Doris Duke Foundation), ecosystemmarketplace.Com
  9. USDA invests $1 billion for nearly 400 projects to expand access to trees and green spaces in communities and neighborhoods nationwide through Investing in America agenda , USDA Forest Service, Sept. 14th, 2023.
  10. U of M looks to use AI to create more climate-safe farming practices, KARE11, May 16th, 2023.
  11. University of Minnesota to lead new $20M AI Institute focusing on climate-smart agriculture and forestry, , College of Science and Engineering, University of Minnesota, May 4th, 2023. Republished on AAAS EurekAlert 8-May-2023,Fox 9 on May-4-2023, etc.
  12. Liu, L., Zhou, W., Guan, K. et al. , Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems . Nature Communication, 15, 357 (2024). https://doi.org/10.1038/s41467-023-43860-5 and News coverage
  13. Shabtai, I.A., Wilhelm, R.C., Schweizer, S.A. et al. Calcium promotes persistent soil organic matter by altering microbial transformation of plant litter . Nat Commun 14, 6609 (2023). https://doi.org/10.1038/s41467-023-42291-6
  14. Collaborative Geodesign and Spatial Optimization for Fragment-Free Land Allocation, Y. Xie, B. Runck, S. Shekhar, L. Kne, D. Mulla, N. Jordan, and P. Wringa, ISPRS Int. J. Geo-Inf. 2017, 6(7), 226; https://doi.org/10.3390/ijgi6070226.
  15. Computing and Climate, J. H. Faghmous, V. Kumar and S. Shekhar, in IEEE/APA Computing in Science \& Engineering (Guest editors introduction to the special issue on Computing and Climate), vol. 17, no. 6, pp. 6-8, Nov.-Dec. 2015, doi: 10.1109/MCSE.2015.114.
  16. Jens Malmodin et al. ICT sector electricity consumption and greenhouse gas emissions – 2020 outcome, Telecommunications Policy, 2024, 102701, ISSN 0308-5961, https://doi.org/10.1016/j.telpol.2023.102701
  17. Related Webpage: Transforming Agriculture Via Intelligent Infrastructure
  18. Related Webpage: Computing at the Nexus of Food, Energy, and Water