Biography
Dr. Martin improves long-term profitability and stability of cropping systems by exploring applications of quantitative methods on big data. He leverages interdisciplinary efforts to expand the frontiers of agricultural research; investigates quantitative methods on processes at multiple spatial and temporal scales; and studies effective approaches to implement new insights and discoveries in agricultural decisions and operations.
Education
Crop Sciences, PhD, University of Illinois Urbana-Champaign
Additional Campus Affiliations
Associate Professor, Crop Sciences
Associate Professor, Center for Latin American and Caribbean Studies
Associate Professor, Center for Digital Agriculture, National Center for Supercomputing Applications (NCSA)
Recent Publications
Gilbert, C., & Martin, N. (2024). Using agro-ecological zones to improve the representation of a multi-environment trial of soybean varieties. Frontiers in Plant Science, 15, Article 1310461. https://doi.org/10.3389/fpls.2024.1310461
Alesso, C. A., & Martin, N. F. (2023). Spatial and temporal variability of corn response to nitrogen and seed rates. Agronomy Journal. Advance online publication. https://doi.org/10.1002/agj2.21471
Li, N., Bullock, D., Butts-Wilmsmeyer, C., Gentry, L., Goodwin, G., Han, J., Kleczweski, N., Martín, N. F., Paulausky, P., Pistorius, P., Seiter, N., Schroeder, N., & Margenot, A. J. (2023). Distinct soil health indicators are associated with variation in maize yield and tile drain nitrate losses. Soil Science Society of America Journal, 87(6), 1332-1347. Advance online publication. https://doi.org/10.1002/saj2.20586
Tao, R., Zhao, P., Wu, J., Martin, N., Harrison, M. T., Ferreira, C., Kalantari, Z., & Hovakimyan, N. (2023). Optimizing Crop Management with Reinforcement Learning and Imitation Learning. In E. Elkind (Ed.), Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 (pp. 6228-6236). (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2023-August). International Joint Conferences on Artificial Intelligence.
Tao, R., Martin, N. F., Zhao, P., Harrison, M. T., Wu, J., Ferreira, C., Kalantari, Z., & Hovakimyan, N. (2023). Optimizing Crop Management with Reinforcement Learning and Imitation Learning. Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, 2023-May, 2511-2513.