Ph.D. degree program in Entomology with an emphasis on Precision Pest Management with Machine Learning, including certification in Geographic Information Systems (GIS). (2023) Kansas State University. Manhattan, KS.

MSc. in Entomology with an emphasis on IPM and Biological Control. (2019). Purdue University. West Lafayette, IN.

BSc. in Agricultural Sciences and Production with an emphasis on Crop Protection and IPM. (2014). Zamorano Pan-American Agricultural School. Tegucigalpa, Honduras.

Graduate GIS certification obtained from the Department of Geography and Geospatial Sciences from Kansas State University, which covered the use of spatial applications, remote sensing, and precision agriculture applications.

Remote pilot certificate to operate drone technology obtained from the Federal Aviation Administration. Part 107 certificate FAA.

Grijalva, I.., Adams, H. B., & McCornack, B. (2025). A fine-tuned deep learning model for detecting Japanese beetles in soybeans using unmanned aircraft systems (UAS) and mobile imaging. Machine Learning with Applications, 21, 100711. https://doi.org/10.1016/j.mlwa.2025.100711

Grijalva, I., Adams H.B., Clark, N., & McCornack, B. (2024). Detecting and counting sorghum aphid alates using smart computer vision models. Ecological Informatics 80:102540. https://doi.org/10.1016/j.ecoinf.2024.102540

Rahman, R., Indris C., Bramesfield G., Zhang T., Li K., Chen X.,Grijalva, I., McCornack B., Flippo B., Sharda A., & Wang, G. (2024). A new dataset and comparative study for real-time aphid cluster detection and segmentation. Journal of Imaging 10 (5): 114. https://doi.org/10.3390/jimaging10050114

Grijalva, I., Clark, N., Hamilton, E., Orpin, C., Perez, C., Schaefer, J., Vogts, K., & McCornack, B. (2024). Comprehensive wheat coccinellid detection dataset: essential resource for digital entomology. Data in Brief 110585. https://doi.org/10.1016/j.dib.2024.110585

Grijalva, I., Kang, Q., Flippo, D., Sharda, A., & McCornack, B. (2024). Unconventional strategies for aphid management in sorghum. Insects 15(7):475. https://doi.org/10.3390/insects15070475

Grijalva, I., Spiesman, B., & McCornack, B. (2023). Computer vision model for sorghum aphid detection using deep learning. Journal of Agriculture and Food Research, 13, 100652. https://doi.org/10.1016/j.jafr.2023.100652

Zhang, T., Li, K., Chen, X., Zhong, C., Luo, B., Grijalva, I., McCornack, B., Flippo, D., Sharda, A. & Wang, G. (2023). Aphid cluster recognition and detection in the wild using deep learning models. Sci Rep 13, 13410. https://doi.org/10.1038/s41598-023-38633-5

Wang, C., Grijalva, I., Caragea, D., & McCornack, B. (2023). Detecting of common coccinellids found in sorghum using deep learning models. Sci Rep 13, 9748. https://doi.org/10.1038/s41598-023-36738-5

Zhang, T., Li, K., Chen, X., Zhong, C., Luo, B., Grijalva, I., McCornack, B., Flippo, D., Sharda, A., & Wang, G. (2023). A new dataset and comparative study for aphid cluster detection. In 2nd AAAI Workshop on AI for agriculture and food systems. https://doi.org/10.48550/arXiv.2307.05929

Grijalva, I., Spiesman, B., & McCornack, B. (2022). Image classification of sugarcane aphid density using deep convolutional neural networks. Smart Agricultural Technology, 3, 100089. https://doi.org/10.1016/j.atech.2022.100089

Milne, M. A., Louderman, J., Foster, B., Grijalva, I., Lewis, J. J., Bishop, L., Deno, B. L., Acosta, J., Frandsen, L., & Stern, E. More spiders in Indiana: 100 new and updated distribution records. In Proceedings of the Indiana Academy of Science (Vol. 128, No. 1, pp. 87-105 (2019)). https://www.researchgate.net/publication/339036734

Special topics: Precision pest management applications.

IGLab | Precision Pest Management