Picture of                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     Fang X.  Wu

Fang X. Wu B.Sc., M.Sc., Ph.D., P.Eng. Professor & Graduate Chair Mechanical Engineering

Room 3B42 Engineering Building

Research Area(s)

  • Bionetwork analysis
  • Network control theory and its applications
  • Machine Vision
  • Drug target identification
  • Biomedical signal and image processing and analysis
  • System identification and parameter estimation
  • Large scale biological data analysis
  • Machine learning

Research Group(s)

  • Biomedical Engineering
  • Control Systems, Robotics, and Fluid Power


Education and Experience

B.Sc.,M.Sc. (DLUT), Ph.D. (NWPU), Ph.D. (Saskatchewan), P. Eng.


  • Bionetwork analysis,
  • Network control theory and its applications,
  • Drug target identification,
  • Biomedical signal and image processing and analysis,
  • System identification and parameter estimation,
  • Large scale biological data analysis,
  • Machine learning

Current and Past Projects

  1. Development of Methodologies for modeling and designing biological systems
  2. Development of real-time control methodologies for tandem mass spectrometry
  3. Computational bioengineering Laboratory
  4. Control engineering approaches to gene regulatory networks

Positions for graduate students in Systems Biology are now available in my research group. I am interested in recruiting high-caliber graduate students who have expertise in the areas of my research. Top-tier control and systems, computer science amd applied mathematics students  who are self-motivated and have publications in relevant scientific journals are encourages to apply.