Reimagining Agriculture through Robots & AI
When the American Cranberry Growers Association gathered for its annual meeting, Computer Science M.S. student Malav Champaneria was there—not as a spectator, but as a presenter sharing research at the crossroads of computer science and agriculture. His work is part of a collaboration led by Dr. Iman Dehzangi with scientists from the U.S. Department of Agriculture Agricultural Research Service (USDA-ARS), where robotics and artificial intelligence are being applied to solve challenges in crop research.
Champaneria has been enhancing the Hyperspectral Agricultural Research Vehicle (HARV), a robotic platform built for automated crop phenotyping and navigation. His contributions include programming centimeter-accurate camera pipelines with GPS RTK data, developing deep learning models that distinguish crops from soil, and creating visualizations such as bird’s-eye heatmaps to guide navigation. He also designed a convolutional neural network for autonomous route prediction and laid the groundwork for hyperspectral imaging to detect field traits like cranberry fruit rot.
Through this project, Champaneria is demonstrating how advanced computer science techniques can translate into practical solutions in the field. The experience highlights his ability to bridge robotics and data science with applied research, reflecting the kind of innovation that defines his graduate journey and future career path.
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