XiaoQi Chen

XiaoQi Chen

Director of Studies - Mechatronics 3rd Pro Year
Civil Mechanical E503
Internal Phone: 92190
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Qualifications & Memberships

Research Interests

Research interests include: mobile robots including unmanned aerial vehicle, unmanned underwater vehicle, GPS-guided autonomous land vehicle, walking machines and climbing robot; human-robot collaborative system; resources and environmental measurement, monitoring, management and control; assistive device for rehabilitation; machine health monitoring, diagnosis and prognosis; vibration-based energy harvesting for wireless instrumentation; manufacturing process automation; machine vision; bio-instrumentation and control; precision measurement and inspection; 3d printing of bio-scaffolds

Prof. Chen has extensively worked with the companies through collaborative research projects. These companies, in different industry sectors, include IBM, Motorola, Delphi Automotive Systems, Tata Consultancy Services, Singapore Technologies, Reed Tools, Turbine Overhaul Services, General Electric, Epoxy and Equipment Technology, Hewlett Packard, Rolls-Royce Plc (UK), Geospatial Research Centre, Dynamic Controls Limited, Commtest Instruments Ltd, Industrial Research Limited, and Methanex.

Recent Publications

  • Asgari H. and Chen XQ. (2016) Gas Turbines Modeling, Simulation, and Control: Using Artificial Neural Networks. Boca Raton: CRC Press. 216pp.
  • Asgari H. and Chen XQ. (2015) Gas turbines modeling, simulation, and control: Using artificial neural networks. 1-182. http://dx.doi.org/10.1201/b18956.
  • Hua C., Lu H., Yu C., Li D. and Chen X. (2019) Probing Laves phase formation in Ni-alloy during ultrasonic arc-welding with atomistic modelling. Science and Technology of Welding and Joining 24(4): 305-312. http://dx.doi.org/10.1080/13621718.2018.1534036.
  • Shao L., Pan Y., Li J., Liu H., Chen X. and Yu X. (2019) Steam piping infrared image segmentation with trend coefficients algorithm. International Journal of Pressure Vessels and Piping 170: 49-58. http://dx.doi.org/10.1016/j.ijpvp.2019.01.010.
  • Stewart AM., Pretty CG. and Chen X. (2019) An investigation into the effect of electrode type and stimulation parameters on FES-induced dynamic movement in the presence of muscle fatigue for a voltage-controlled stimulator. IFAC Journal of Systems and Control 8 100043 http://dx.doi.org/10.1016/j.ifacsc.2019.100043.