Tong Boon Tang

Universiti Teknologi Petronas, University of Edinburgh

Papers

6

Total Citations

85

H-Index

4

About

Tong Boon Tang is a leading researcher at the intersection of robotics, artificial intelligence, and biomedical engineering, with a focus on autonomous navigation and medical image analysis. His most impactful work centers on developing deep reinforcement learning (DRL) architectures for tracked robots, enabling collision-free autonomous steering in dynamic environments. His 2020 paper on vision-based navigation using DRL (28 citations) introduced a novel end-to-end network that significantly improved real-time decision-making, while his 2019 overview of DRL for visual navigation (13 citations) has become a key reference in the field. Tang also made notable contributions to medical imaging, particularly with his 2021 work on automatic polyp segmentation in colonoscopy images (17 citations), which employed a modified deep convolutional encoder-decoder architecture to enhance colorectal cancer screening efficiency. Earlier in his career, he demonstrated pioneering work in microelectromechanical systems (MEMS), developing a wireless-driven pond skater robot using electrowetting-on-dielectric (EWOD) technology (23 citations). With over 85 total citations across his most-cited papers, Tang’s research bridges robotics, AI, and healthcare, offering practical solutions for autonomous systems and clinical diagnostics.

Research Focus

Key Achievements

4
H-Index
6
Papers
85
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Vision-Based Autonomous Navigation Approach for a Tracked Robot Using Deep Reinforcement Learning
28 citations · 2020
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: Universiti Teknologi Petronas, University of Edinburgh

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago