Arvind Raju

Papers

Total Citations

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About

Arvind Raju is a researcher at the forefront of applying artificial intelligence to industrial automation, with a particular focus on robotic welding quality control. His most-cited work, "Unsupervised Welding Defect Detection Using Audio and Video" (2024), addresses a critical gap in modern manufacturing: the inability of robotic welding systems to autonomously identify defects introduced during the welding process. Raju’s key contribution lies in developing deep-learning models that leverage both audio and visual data for unsupervised defect detection, enabling robots to self-monitor and improve weld quality without requiring extensive labeled training datasets. This multimodal approach represents a significant advancement in non-destructive testing and smart manufacturing. With 3 citations in a short time, his work is gaining traction among researchers in industrial AI and automation. Raju’s research promises to enhance production efficiency, reduce waste, and increase safety in industries ranging from automotive to aerospace, making him a rising voice in the integration of AI with real-world manufacturing challenges.