Xiaobo Qu' Computational Sensing Group at Xiamen University


research  Introduction

High performance computing provides new opportunities to sense the atoms and moleculars in chemistry and biology, anatomical/functional structures of animal and human beings, as well as our living environments. Our group currently is focusing on developing multi-dimensional and multi-modal signal reconstruction models and computaitonal algorithms for fast magnetic resonance Imaging and spectroscopy, and extend these signal models into other applications including image processing, wireless sensor networks and remote sensing.

Theories and methods:

  • Signal processing
  • Image processing
  • Deep learning
  • Harmonic analysis
  • Optimization algorithm
  • High performance computing
  • Magnetic resonance physics


  • Magnetic resonance imaging
  • Magnetic resonance spectroscopy
  • Big data of medical imaging
  • Wireless sensor network
  • Remote image processing

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Lastest update at 03/12/2020