Juan Pablo Rojas Bustos
Project Center for Agro Technologies
I am a Computer Science researcher specializing in robotics, computer vision, and machine learning for agricultural innovation. Over the past seven years, I’ve developed advanced methods to analyze environmental data—including temperature, humidity, aerial imagery (RGB, multispectral, thermal), satellite data (e.g., Sentinel), and LiDAR point clouds. My work focuses on creating novel technologies to monitor crop growth, enable early stress detection, and improve pest management, driving efficiency and sustainability in agriculture.
Beyond data analysis, I design electronics and control systems to optimize environmental conditions in greenhouses and phenotyping platforms. My greatest passion lies at the intersection of computer vision and aerial robotics, where I build cutting-edge solutions for the future of smart farming.
Interested in collaborating or discussing a project? I’d love to connect—feel free to reach out
Supervisor: Raghavendra Jana
- Computer Vision for Crop & Tree Phenotyping
- Developing advanced imaging techniques (RGB, multispectral, thermal, LiDAR) to analyze plant morphology, architecture, health, and growth dynamics.
- Automating high-throughput phenotyping for precision agriculture and breeding programs.
- Aerial Robotics for Smart Farming
- Designing autonomous drone systems for real-time crop monitoring, stress detection, and yield prediction.
- Integrating AI with UAVs for scalable, efficient data collection in open fields and controlled environments.
- Optimization of Deep Learning Models for Agricultural AI
- Creating lightweight, efficient neural networks for edge deployment on drones and IoT devices.
- Enhancing model interpretability and robustness for diverse environmental conditions (e.g., varying light, weather, crop types).
- Rojas, J. P., Branthomme, A., Costes, E., & Boudon, F. (2022). Comparison between UAV and terrestrial LiDAR scans for high throughput phenotyping of architectural traits of a core collection of apple trees. ISHS.
- Colorado, J. D., Calderon, F., Mendez, D., Petro, E., Rojas, J. P., Correa, E. S., … & Jaramillo-Botero, A. (2020). A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops. PloS One, 15(10), e0239591.
- Artzet, S., Rojas, J. P., Pallas, B., Costes, E., & Boudon, F. (2020). Machine and deep learning based identification of organs within LiDAR scans of tree canopies: Application to the estimation of apple production. Institute of Horticultural Production Systems.
- Devia, C. A., Rojas, J. P., Petro, E., Martinez, C., Mondragon, I. F., Patiño, D., … & Colorado, J. (2019). High-throughput biomass estimation in rice crops using UAV multispectral imagery. Journal of Intelligent & Robotic Systems, 96, 573–589.
- Devia, C. A., Rojas, J. P., Petro, E. E., Mondragon, I. F., Patino, D., Rebolledo, C., & Colorado, J. (2019). Aerial monitoring of rice crop variables using an UAV robotic system.
- Rojas, J. P., Petro, E., Martinez, C., Mondragon, I. F., Patino, D., Rebolledo, M. C., & Colorado, J. (2018, June). Aerial mapping of rice crops using mosaicing techniques for vegetative index monitoring. In 2018 International Conference on Unmanned Aircraft Systems (ICUAS) (pp. 846–855). IEEE.
- Rojas, J. P., Martinez, C., Mondragon, I., & Colorado, J. (2017). Towards image mosaicking with aerial images for monitoring rice crops. In Advances in Automation and Robotics Research in Latin America: Proceedings of the 1st Latin American Congress on Automation and Robotics, Panama City, Panama 2017 (pp. 279–296). Springer International Publishing.
Ph.D. in Computer Science
University of Montpellier, France
[2020 – 2024]
M.Sc. in Electronics Engineering
Pontificia Universidad Javeriana, Colombia
[2016 – 2019]
B.Eng. in Mechatronic Engineering
Universidad Piloto de Colombia
[2009 – 2014]