Anis Salwa Mohd Khairuddin
Papers
7
Total Citations
104
H-Index
4
About
Anis Salwa Mohd Khairuddin is a multidisciplinary researcher whose work spans computer vision, environmental monitoring, robotics, and sustainable manufacturing. She has made significant contributions to automated waste detection, developing optimized YOLO-based models for identifying solid waste and floating debris in riverine environments — research that directly addresses the growing global challenge of urban pollution and ecological degradation. Her 2022 paper on automated solid waste detection has accumulated 42 citations, underscoring its relevance to smart environmental management systems. Khairuddin has also emerged as a notable voice in robotics, particularly in the domain of robotic manipulator motion planning within dynamic environments. Her 2024 reviews and deep reinforcement learning-based path planning work — collectively garnering over 36 citations within their first year — reflect her timely engagement with the demands of collaborative and autonomous robotics in industrial settings. Beyond these areas, she has contributed to tropical wood species recognition and energy-efficient manufacturing strategies, demonstrating a broad commitment to applying intelligent systems across diverse real-world challenges. Her growing citation profile and consistently applied research agenda position her as an impactful contributor to intelligent automation and environmental technology fields.
Research Focus
Key Achievements
Top Papers
- 1
- 2Review on Motion Planning of Robotic Manipulator in Dynamic Environments19 citations · 2024
- 3
- 4An automatic garbage detection using optimized YOLO model15 citations · 2023
- 5Online System for Automatic Tropical Wood Recognition4 citations · 2019
- 6YOLO-based Network Fusion for Riverine Floating Debris Monitoring System4 citations · 2021
- 7