Dr Yunjie Yang

Chancellor's Fellow



1.13 Alexander Graham Bell building

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Engineering Discipline: 

  • Electronics and Electrical Engineering

Research Institute: 

  • Digital Communications

Research Theme: 

  • Signal and Image Processing
  • Tomography
  • Sensors


Dr. Yunjie Yang is the Lecturer and Chancellor’s Fellow in Data Driven Innovation (Assistant Professor) at The University of Edinburgh. He received his Ph.D. in Engineering Electronics from The University of Edinburgh (2018), MSc in Control Science & Engineering from Tsinghua University (2013), and BEng in Measurement & Control Engineering from Anhui University (2010). From Aug 2013 to Feb 2014, he was a research assistant at the University of Connecticut, Storrs, US. After obtaining his Ph.D., he briefly worked as a Postdoctoral Research Associate in Chemical Species Tomography at The University of Edinburgh until Sept 2018.

Dr. Yang’s research interests are in the areas of sensing and imaging with AI-based tomography, machine learning, digital twins, and flexible sensors. The goal of his research is to improve observability in both industrial (e.g. multiphase flow), robotics (e.g. soft robotics), and biomedical processes for enhanced control and fault diagnosis, and to address the pressing challenges of efficient utilization/interpretation of enormous sensing data. His research has led to more than 90 peer-reviewed journal and international conference publications, many of which were published in high-impact journals such as IEEE TNNLS, TMI, TII, and TIM. His research outputs have been licensed to overseas research institutes and industry partners.

He is the Associate Editor of IEEE Transactions on Instrumentation and Measurement and IEEE Access, the Topic Editor of Chemosensors, the Guest Editor for IEEE Sensors Journal, and the Guest Editor for Chemosensors, and serves as the regular reviewer for more than 50 high-impact international journals. He has been the Technical Program Committee member of the IEEE International Conference on Imaging Systems and Techniques since 2015. He was the recipient of the 2015 IEEE I&M Society Graduate Fellowship Award. He is a member of IEEE, IET, the Fellow of the International Society for Industrial Process Tomography (FISIPT), and the Fellow of Higher Education Academy (FHEA).

Research group website: www.yangresearchgroup.com

(Office: 1.13 Alexander Graham Bell)

Academic Qualifications: 

  • 2018  Doctor of Philosophy (PhD), School of Engineering, The University of Edinburgh, UK
  • 2013  Master of Science (MSc) (Distinction), Department of Automation, Tsinghua University, China
  • 2010  Bachelor of Science (BEng) (First Class Honors), Department of Measurement & Control Engineering, Anhui University, China

Professional Qualifications and Memberships: 


  • Signals and Communication Systems 3 (ELEE09027)
  • Digital System Laboratory 3 (ELEE09035)
  • Electrical Engineering 1 Tutorial (ELEE08001)
  • Supervision of PhD, MSc, MEng and BEng projects

Research Interests: 

  • AI-powered multi-modal tomographic imaging for tissue engineering
  • Digital twins for multiphase flow systems
  • Soft robotics perception and control
  • Machine learning for medical imaging
  • Electrical and optical tomography


  • Medical imaging and machine learning
  • Soft sensors, Sensing for soft robotics
  • Agile Tomography
  • Multi-modal Tomography
  • Digital twins

Further Information: 

We welcome undergraduates, graduates, and postdocs who are interested in joining our group. Please feel free to contact us at anytime.