Mien Van


Accepting PhD Students

PhD projects

- Resilient control for trustworthy autonomous systems - AI/Machine learning for Human-Computer Interface/Human-Robot Collaboration - AI/Machine Learning for Health Care - Shared control Human-Robot Grinding Systems for Metal parts - Cooperative control for multi-robot system - Optimal Human-robot collaboration for disassembly in Remanufacturing - Inline process condition monitoring for remote laser welding - Advanced industrial robots for 3D surface finishing


Research output per year

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Personal profile

Research Focus


  • Dr. Van is a Lecturer in Robotics and Control Engineering. He has authored and co-authored for over 42 journal and 8 conference papers (first author >35 journal papers,). Many papers are published in prestigious journals, including TFS (IF: 9.518), TMECH (IF: 5.673), TCYN (IF: 11.079), TII (IF: 9.112), T-SMC (IF: 9.309), MSSP (IF: 6.471), etc. His publication get >1050 citations, h-index=20. 
  • Dr. Van has participated in several major projects in Robotics and Control Engineering. For example, Robotics projects: Human-robot collaborative systems in industrial unstructured environments (funded by A*Star), Dexterous and Flexible Robotic Hand with Force Sensing and Adaptive Compliant Control (funded by ONR Global, USA). Manufacturing project: RLW Navigator: Rapid development of remote laser welding process in automotive assembly (funded by FP7). Control engineering project: Control of Launch and Recovery in Enhanced Sea-States (funded by EPSRC).
  • Dr. Van received a Best paper award from BK21 (south Korea goverment), the prestigious IET premium award, and Best paper award from ICROS (conference).
  • Dr. Van is an Associate Editor of International journal of Control Autonomous System (IF:2.733) and Frontiers in Control Engineering, and Guest Editor of journal Sensor (IF:3.031).


Research Focus and Interest

  • Resilient Risk-Aware Autonomy for Unmanned autonomous vehicles: develop health monitoring, disturbance observer, intelligent control and resilient control.
  • In-process quality control for manufacturing systems: develop inline quality manufacturing, in-process quality control for welding and machining systems.
  • Human-robot interaction: Shared control and safe control, intelligent human-robot interaction.
  • Fault diagnosis and fault tolerant control for mechanical systems: robot, aerospace, etc.


Teaching: ELE4024: Robotics and Intelligent Systems

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