Dr. Yunjie Yang is the Chancellor’s Fellow in Data Driven Innovation 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 the observability in both industrial (e.g. multiphase flow), robotics (e.g. soft robotics), and biomedical processes for enhanced control and fault diagnosis, and address the pressing challenges of efficient utilization/interpretation of enormous sensing data. His research has led to more than 60 peer-reviewed journal and international conference publications, many of which were published in high-impact journals such as IEEE TMI, TII, TIM. His research outputs have been licensed to overseas research institutes and industry partners.
He has been the Associate Editor of IEEE Access since 2019, the Topic Editor of Chemosensors since 2021, the Guest Editor for IEEE Sensors Journal in 2021, and serving as the regular reviewer for more than 35 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, and the International Society for Industrial Process Tomography (ISIPT).
Research group website: www.yangresearchgroup.com
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