Shriti Gupta

Mody University of Science and Technology

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About

Shriti Gupta is a researcher at the forefront of applying artificial intelligence to agricultural challenges, with a primary focus on precision farming and weed management. Her most-cited work, "Improving Weed Detection Using Deep Learning Techniques" (2021), introduces advanced convolutional neural network architectures that significantly enhance the accuracy and speed of identifying invasive plant species in crop fields. This contribution addresses a critical bottleneck in sustainable agriculture—reducing herbicide overuse while maintaining crop yields. Although early in her career, her research has already garnered attention for its practical implications, demonstrating how deep learning can automate labor-intensive tasks and support data-driven decision-making for farmers. Gupta’s work bridges the gap between computer vision and agronomy, offering scalable solutions for real-time weed monitoring. Her dedication to developing robust, field-deployable models positions her as an emerging voice in the intersection of AI and environmental stewardship, with future potential to influence smart farming technologies globally.