Shing Chyi Chua

Multimedia University

Papers

7

Total Citations

162

H-Index

5

About

Shing Chyi Chua is a leading researcher in robotic manipulation, with a primary focus on enabling robots to intelligently perceive, grasp, and place objects in complex, cluttered environments. His work bridges computer vision, deep reinforcement learning, and dexterous manipulation, tackling fundamental challenges in how robots interact with their surroundings. Chua’s most impactful contribution is his comprehensive review on reaching and grasping in robotics (78 citations), which synthesizes decades of research and serves as a key reference for the field. He has also advanced learning-based manipulation with his review on robotic manipulation in cluttered settings (39 citations) and developed novel frameworks for pick-and-place tasks using deep reinforcement learning (17 citations) and self-supervised learning with minimal training resources. His work on grasping under clutter and occlusion (16 citations) addresses the critical challenge of spatial equivariance in visual perception. Chua’s research is distinguished by its practical focus on efficient, resource-conscious methods that make robotic manipulation more accessible and deployable. His contributions have significant implications for industrial automation, assistive robotics, and autonomous systems operating in unstructured environments.

Research Focus

Key Achievements

5
H-Index
7
Papers
162
Total Citations
23
Avg Citations/Paper
🏆 Most Cited Paper
Comprehensive Review on Reaching and Grasping of Objects in Robotics
78 citations · 2021
📈 Most Prolific Year: 2021 (4 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Multimedia University

Top Papers

  1. 1
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    Pick and Place Objects in a Cluttered Scene Using Deep Reinforcement Learning
    17 citations · 2020
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago