Agricultural Intelligence and Digital Engineering (AIDE)

Mission

To elevate agricultural productivity and sustainability through cutting-edge digital technologies and advanced analytical methodologies.

We employ a wide range of tools to monitor crop growth and development, including remote sensing technologies (UAVs and satellites), optical sensors, ground-based robotics, and Internet-of-Things (IoT) devices. Leveraging data-driven Artificial Intelligence (machine and deep learning models) and physics-driven process-based models (radiative transfer model, crop growth model), we make accurate and robust predictions for crop performance.

Join us!

I am actively looking for graduate students to join our lab at the Department of Biosystems Engineering, University of Manitoba. Students with strong self-motivation and passion for agricultural engineering are welcome to contact me.