Aufa Faiz Setyawan
Papers
1
Total Citations
1
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1
About
Aufa Faiz Setyawan is a researcher at the forefront of edge AI and mobile deep learning, with a primary focus on advancing autonomous systems for critical applications. His most cited work, "Edge AI-Driven Video Analytics: A Mobile Deep Learning Framework for Victim Detection in SAR Robotics" (2024), tackles a pressing challenge in post-disaster search and rescue: enabling robots to reliably distinguish between actual victims and dummy objects in real time. By deploying high-performing deep learning models directly on edge devices, Setyawan’s framework overcomes the traditional trade-off between accuracy and computational efficiency, achieving robust victim detection without relying on cloud connectivity. This contribution is vital for time-sensitive SAR missions where every second counts. With growing recognition in the robotics and computer vision communities, his work has already garnered citations, underscoring its practical impact. Setyawan’s research not only pushes the boundaries of edge intelligence but also directly enhances the lifesaving capabilities of autonomous rescue robots, making him a notable emerging voice in the field of AI-driven humanitarian technology.
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Top Papers
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