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 obtaining his PhD, he was a Postdoctoral Research Associate in Chemical Species Tomography at the University of Edinburgh until August 2018.
Dr. Yang’s research expertise is in the areas of sensing and imaging with miscellaneous tomography modalities, and machine learning techniques 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 modalities. 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 12 high-impact international journals, including four IEEE Transactions. He has been the Technical Program Committee member 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). He is currently the supervisor of four PhD students and two MSc students.
As principal supervisor
Haokun Wang (2019-2023)
Haokun Wang obtained his BEng (2017) and MSc (2018) from the University of Edinburgh. He started his PhD study in January 2019 and worked on the project "Big data of multi-phase flow measurement for optimising oil and gas production".
Delin Hu (2019-2023)
Delin Hu received his BEeng degree from Sichuan University in 2015, and MSc degree from Tsinghua University in 2019. His research interests include machine learning, sensor data mining, and data innovation in industrial applications.
Zhou Chen (2019-2023)
Zhou Chen obtained her BEng degree in Electrical and Electronics Engineering, and Msc degree in Artificial Intelligence from University of Edinburgh. Her research interests focus on applying machine learning methods to engineering application.
Abdul Hafeez Abdul Bari (2019-2023)
Hafeez obtained his First Degree in Transportation Planning and Studies in 2008 at MARA University of Technology (UiTM) in Malaysia.
He later joined Oil and Gas industry for two years and did his MSc in Engineering (Industrial and Supply Chain) at Coventry University UK graduated in 2011
with Distinction and had been awarded Coventry University's Best Project Prize Winner in his outstanding dissertation work. Returned back to Malaysia right after,
Hafeez has been in upstream Oil and Gas industry until 2019 where he decided to pursue his PhD Engineering.
With his total industrial experience, particularly in upstream oil and gas of eleven (11) years, he has been working on-site (onshore and offshore) and first hand
oilfield development projects including drilling, upstream production and operations, machines performance and maintenance,data innovation
projects and support for realising the digitisation of oil and gas production and operations in Malaysia and Asia Pacific Region.
Zhe Liu (2019-2023)
Zhe Liu received his BEng (2018) from Huazhong University of Science and Technology, and MSc (2019) from the City University of Hong Kong. His research interests include biomedical imaging, image reconstruction, and signal and image processing.
As assistant supervisor
Changjiang Liu (with Prof. Tughrul Arslan)
Project title: "Efficient Capacitive Tactile Proximity Sensor System for Adaptive and Intelligent Human Robot Interaction".
MSc and BEng Students
Zhenyu Jiang (2018-2019)
Project title: "Machine learning for multi-phase flow characterisation based on massive sensing data".
Zhijin Sun (2018-2019)
Project title: "Multi-frequency tomographic imaging based on multiple measurement vector model".
Zhilin Liu (2019-2020)
Project title: "Machine learning for tomographic image reconstruction".
Brian Tinashe Toperesu (2019-2020)
Project title: "Frequency-difference imaging of CVECT".
Visiting PhD students
Jinxi Xiang (2019-2020, CSC-sponsored, Tsinghua University, China)
Project title: advanced image reconstruction algorithm for magnetic induction tomography.
Visiting undergraduate students