Ishneet Sukhvinder Singh

Singapore University of Technology and Design

Papers

Total Citations

H-Index

About

Ishneet Sukhvinder Singh is a researcher advancing the intersection of computer vision, deep learning, and autonomous robotics, with a focus on intelligent cleaning systems. In their most-cited work, "Vision-based dirt distribution mapping using deep learning" (2023, 9 citations), Singh pioneered a novel approach to enable floor-cleaning robots to detect and map dirt distribution in real time using convolutional neural networks. This contribution addresses a critical gap in robotic cleaning—moving beyond simple vacuuming or scrubbing to context-aware, adaptive cleaning that targets areas based on actual dirt presence. By integrating deep learning with robotic perception, Singh’s work enhances the efficiency and autonomy of domestic and industrial cleaning robots, reducing energy waste and improving task completion. Their research has implications for smart home technologies and autonomous service robots, demonstrating how AI can transform mundane chores into intelligent operations. Singh’s achievements reflect a commitment to practical, real-world applications of machine learning, positioning them as an emerging voice in robotics and computer vision.