Hari Fitria Windi

Papers

Total Citations

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About

Hari Fitria Windi is a researcher at the forefront of autonomous robotics and artificial intelligence, with a particular focus on integrating deep learning with spatial perception. Her most-cited work, "Spatial Based Deep Learning Autonomous Wheel Robot Using CNN" (2020, 9 citations), exemplifies her core contribution: developing intelligent robotic systems that can navigate and make decisions independently by mimicking human cognitive functions. By leveraging Convolutional Neural Networks (CNNs), Windi's research enables wheeled robots to process spatial data in real time, effectively allowing them to "see" and react to their environment without human intervention. This work sits at the intersection of robotics, computer vision, and AI, addressing the growing demand for autonomous systems in industries ranging from logistics to smart manufacturing. While her citation count reflects a focused, emerging impact, Windi’s research is notable for its practical, application-driven approach—bridging theoretical deep learning models with real-world robotic autonomy. Her contributions are particularly relevant for students and researchers exploring how AI can be deployed in physical systems, offering a clear pathway from algorithm design to tangible robotic behavior.