Intelligent Sensing, Analysis & Control Group

Dr. Yunjie Yang was appointed as the Chancellor’s Fellow in Data Driven Innovation (Lecturer) at the University of Edinburgh in September 2018. He received his PhD in Engineering Electronics from the University of Edinburgh (01/2018), MSc (Distinction) in Control Science & Engineering from Tsinghua University, China (07/2013), and BEng (First Class with Honours) in Measurement & Control Engineering from Anhui University, China (07/2010). From August 2013 to February 2014, he was a Research Assistant at the Electromechanical System Laboratory, University of Connecticut, Storrs, US. After his PhD, he briefly worked as a Postdoctoral Research Associate in Chemical Species Tomography at the University of Edinburgh until September 2018.

Dr. Yang’s research expertise expands the areas of sensing and imaging with miscellaneous tomography modalities, soft robot perception and control, and machine learning for sensing data analysis. The goal of his research is to improve the observability in both industrial and biomedical processes for enhanced control and fault diagnosis, and address the pressing challenges of efficient utilisation/interpretation of enormous sensing data generated by multiple sensing techniques. His research has led to more than 50 peer reviewed journal and international conference publications, many of which were published in high-impact journals (including one cover story and one review paper). Part of his research outputs has been licensed to overseas research institutes, e.g. Pennsylvania State University (US), and local industry, e.g. AIE Ltd. He was the recipient of the 2015 IEEE I&M Society Graduate Fellowship Award and the Innovation Initiative Grant from the University of Edinburgh Development Trust. He was also the recipient of the Best Student Paper Award of 2017 IEEE International Conference on Imaging Systems and Techniques and the Best Poster Award of the 4th International Conference on Impedance-Based Cellular Assays.

He is the Associate Editor of IEEE Access Journal. He also serves as the regular reviewer for more than 20 high-impact international journals, including four IEEE Transactions. He has been the member of the Technical Program Committee of the IEEE International Conference on Imaging Systems and Techniques since 2015. He is a member of IEEE, IET, and the International Society for Industrial Process Tomography (ISIPT).

​

Specifically, Dr. Yang's group works on:
1. Biomedical imaging and machine learning for tissue engineering.
2. Intelligent soft robots control and perception.
3. Sensing and machine learning for multi-phase flow measurement.
4. Industrial process tomography: sensor, system, inverse problems, and applications.

More information can be found here:
Data Driven Innovation Programme website: https://ddi.ac.uk/chancellors/yunjie-yang/
Offical website: https://www.eng.ed.ac.uk/about/people/mr-yunjie-yang

​

Email: y.yang@ed.ac.uk