Sukhad Anand

Papers

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About

Sukhad Anand is a researcher whose work sits at the compelling intersection of computer vision, autonomous systems, and intelligent infrastructure monitoring. His most recognized contribution, "Crack-pot: Autonomous Road Crack and Pothole Detection" (2018), has garnered 78 citations and stands as a landmark effort in applying machine learning and image processing techniques to real-world road safety challenges. In this work, Anand and his collaborators developed a fully autonomous, real-time system capable of detecting road impairments such as cracks and potholes — a critical capability as self-driving vehicles and autonomous robots increasingly navigate complex urban environments. By enabling vehicles to identify and respond to road damage without human intervention, his research contributes directly to passenger safety and the reliability of autonomous navigation systems. Anand's work exemplifies how computer vision can be harnessed for practical, high-impact applications beyond traditional domains, bridging the gap between academic research and real-world infrastructure needs. For students and researchers in autonomous systems or intelligent transportation, his contributions offer both technical depth and meaningful societal relevance, making him a notable voice in the evolving field of AI-driven road monitoring.