About

Dr. Quang Dan Le is a Lecturer in Embedded Sytems at the University of Derby, with a distinguished academic and professional background. He received his B.S. degree in Mechatronic Engineering from Danang University of Technology, Danang City, Vietnam, in 2011. He earned his M.S. and Ph.D. degrees from the School of Electrical Engineering at the University of Ulsan, South Korea, in 2022.

Dr. Le's professional experience includes serving as a Research Scientist at the Agency for Science, Technology and Research (A*STAR), Singapore, in 2022-2023. From 2023 to 2025, he conducted postdoctoral research in teleoperation and wearable haptics at the University of Strathclyde, United Kingdom. His expertise and passion for robotics inspire both his teaching and research, fostering innovation in intelligent systems.

Teaching responsibilities

Module: Real-Time Embedded Systems

This module explores the design and implementation of real-time embedded systems on Texas Instrument microcontroller, critical for applications in robotics and automation. Students learn about embedded system architectures, real-time operating systems, and programming techniques to develop responsive and reliable systems for industrial and research purposes

Research interests

Dr. Le's research primarily focuses on the following areas:

• End-to-End Multi-task Reinforcement Learning: Developing algorithms to enable robots to efficiently perform multiple tasks by leveraging diverse datasets.
• Imitation Learning via Inverse Reinforcement: Designing systems that allow robots to replicate human behaviour by inferring objectives from observed actions.
• Model-based Fault Detection for Robot Manipulators: Utilising dynamic models of robot manipulators to estimate actuator faults.
• Fault-tolerant Control for Robot Manipulators: Enabling robots to maintain acceptable performance during system faults until maintenance can be performed.
• Force Control: Developing precise force control techniques for robot manipulators and haptic devices.
• Teleoperation Control: Creating wearable haptic devices for industrial applications in teleoperation.
• Human-Robot Interaction: Designing controllers to enhance safe and effective collaboration between robots and humans in shared workspaces.

His work has been recognized in academic communities, contributing to advancements in intelligent automation and robotic systems.

www.researchgate.net/profile/Quang-Dan-Le

In the media

• Dr. Quang Dan Le - Biography
• Quang Dan LE profile on Research Gate

Recent publications

Journal Articles

• Le, Q.D.; Yang, E. Adaptive Fault-Tolerant Tracking Control for Multi-Joint Robot Manipulators via Neural Network-Based Synchronization. Sensors 2024, 24, 6837. https://doi.org/10.3390/s24216837.
• Vo, A.T.; Truong, T.N.; Le, Q.D.; Kang, H.J. Fixed-Time Sliding Mode-Based Active Disturbance Rejection Tracking Control Method for Robot Manipulators. Machines 2023,< 11(2), 140.

Conference Papers

• Chen, C.; Yan, S.; Yuan, M.; Tay, C.; Choi, D.; Le, Q.D. A Minimal Collision Strategy of Synergy Between Pushing and Grasping for Large Clusters of Objects. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Detroit, MI, USA, 2023, pp. 6817-6822. DOI: 10.1109/IROS55552.2023.10341452.