Biography
Dr. Condotta is an Assistant Professor at the University of Illinois. Her interdisciplinary research aims to reduce animal stress, improve animal well-being and environmental sustainability, and help farmers make better and more efficient management decisions by developing precision management systems for animals. She focuses on applying technologies, such as image and audio processing and machine learning algorithms, to acquire and analyze individual animals' electronic data, allowing continuous and automatic monitoring of their behavior, health, and well-being.
Additional Campus Affiliations
Assistant Professor, Animal Sciences
Assistant Professor, Agricultural and Biological Engineering
Assistant Professor, Center for Digital Agriculture, National Center for Supercomputing Applications (NCSA)
Recent Publications
Condotta, I. C. F. S., & Tedeschi, L. O. (2026). ASAS-NANP Symposium: Mathematical modeling in animal nutrition: Revolutionizing animal farming with artificial intelligence: Trends, challenges, and opportunities. Journal of animal science, 104, Article skaf441. https://doi.org/10.1093/jas/skaf441
Hanson, E. M., Shike, D. W., Condotta, I. C. F. S., Matthews, J., & Bresolin, T. (2026). Predicting body weight and efficiency traits in beef cattle based on depth image data. Frontiers in Animal Science, 7, Article 1752658. https://doi.org/10.3389/fanim.2026.1752658
Li, J., Hu, X., Lucic, A., Wu, Y., Condotta, I. C. F. S., Dilger, R. N., Ahuja, N., & Green-Miller, A. R. (2026). Promote computer vision applications in pig farming scenarios: High-quality dataset, fundamental models, and comparable performance. Journal of Integrative Agriculture, 25(6), 2534-2544. https://doi.org/10.1016/j.jia.2024.08.014
Rahman, M., Souza, V. H. S., Brown-Brandl, T. M., Rohrer, G. A., Shi, Y., & Condotta, I. C. F. S. (2026). Accelerating sow nursing behavior monitoring with modified YOLO11n architecture and TensorRT integration. Porcine Health Management, 12(1), Article 32. Advance online publication. https://doi.org/10.1186/s40813-026-00507-3
Zhou, M., Zhou, S., Xiong, B., Li, Z., Condotta, I. C. F. S., Dilger, R. N., Li, J., & Tang, X. (2026). Humanoid animal behavior labeler: An interactive annotation agent to accelerate ethological applications in precision management of animals using large vision-language models. Computers and Electronics in Agriculture, 241, Article 111307. https://doi.org/10.1016/j.compag.2025.111307