Syariful Syafiq Shamsudin
Papers
1
Total Citations
30
H-Index
1
About
Dr. Syariful Syafiq Shamsudin is a leading researcher in autonomous robotics and intelligent control systems, with a primary focus on reinforcement learning (RL) for unmanned aerial vehicle (UAV) navigation and target tracking. His most influential work, "Twin Delayed Deep Deterministic Policy Gradient-Based Target Tracking for Unmanned Aerial Vehicle With Achievement Rewarding and Multistage Training" (2022, 30 citations), introduces a novel model-free RL framework that addresses the high nonlinearity and dynamic uncertainty inherent in UAV tracking. By developing an achievement-rewarding mechanism and multistage training strategy, Dr. Shamsudin significantly improves the stability and convergence of deep RL algorithms for real-time robotic applications. His contributions bridge the gap between theoretical reinforcement learning and practical autonomous flight, offering robust solutions for complex, uncertain environments. With a growing citation impact, his research is shaping next-generation autonomous systems, particularly in defense, surveillance, and search-and-rescue operations. Dr. Shamsudin’s work is essential reading for students and researchers interested in deep RL, UAV control, and intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1