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About

Sadaf Zeeshan is a leading researcher in agricultural robotics, with a focused expertise in developing autonomous systems for fruit harvesting in unstructured environments. Her work addresses the critical challenge of integrating artificial intelligence and mechanical design to enhance the sustainability and efficiency of modern agriculture. Zeeshan’s major contributions include the performance analysis of path planning algorithms and the design of a convolutional neural network (CNN)-based model for accurate orange fruit detection under dynamic orchard conditions, achieving high precision despite challenges like occlusion and variable lighting. Her research extends to the kinematic analysis and simulation of harvesting robots, as well as the innovative design of solar energy systems to power these robots in regions like Pakistan, promoting energy sustainability. With over 43 citations across her most-cited works, Zeeshan’s impact is evident in her comprehensive evaluations of robot performance, including damage rate analysis, which provides critical insights for improving robot design. Her notable achievements include pioneering in-depth studies on environmental factors affecting harvesting success, positioning her as a key contributor to the advancement of intelligent, resilient agricultural automation.