Dr. Yunjie Yang is a Senior Lecturer (Associate Professor), Chancellor’s Fellow in Data Driven Innovation and Bayes Innovation Fellow 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). After obtaining his Ph.D., he briefly worked as a Postdoctoral Research Associate in Chemical Species Tomography at The University of Edinburgh.

Dr. Yang’s research interests are in the areas of sensing and imaging with AI-powered tomography, machine learning, digital twins, and flexible sensors for wearables and robotics. His research aims to improve observability in industrial (e.g. multiphase flows), robotics (e.g. soft robotics), and biomedical engineering and to address the pressing challenges of efficient utilization/interpretation of enormous sensory data. His research has led to over 100 peer-reviewed journal and international conference publications, many of which were published in high-impact journals such as Nature portfolio journals (Nature Machine Intelligence, Communications Engineering), IEEE TNNLS, TMI, TBME and TIM. His research has been licensed to overseas research institutes and industry partners and received wide media coverage, including BBC, EFE, USA Today and STV. 

He is the Associate Editor of IEEE Transactions on Instrumentation and Measurement, the Topic Editor of Chemosensors, the Guest Editor for IEEE Sensors Journal, Chemosensors, and Frontiers in Physics, and serves as the regular reviewer for over 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

Media coverage:

• BBC: https://www.bbc.co.uk/iplayer/episode/m001m1mr/click-medical-marvels (from 8:12)
• DDI case study: https://ddi.ac.uk/case-studies/smart-e-skin-for-soft-robotic-perception/
• STV: https://news.stv.tv/east-central/edinburgh-university-researchers-develo...
• EFE: Crean la primera "piel electrónica" para que los robots sientan (efe.com)     
• Evening Standard Podcast: https://play.acast.com/s/tech-science-daily/e-skin-boosts-robot-self-awareness
• Metro: https://metro.co.uk/2023/02/24/scientists-develop-electronic-skin-that-allows-robots-to-feel-18340234/
• The Independent: https://www.independent.co.uk/tech/robots-self-aware-ai-skin-b2288369.html
• The Daily Telegraph - https://www.telegraph.co.uk/news/2023/02/23/e-skin-game-scientists-invent-layer-silicone-allows-robots-touch/
• Irish Examiner: https://www.irishexaminer.com/world/arid-41078627.html
• Irish Independent: https://www.independent.ie/world-news/europe/britain/robots-will-be-able-to-touch-and-feel-the-world-like-humans-as-scientists-invent-flexible-e-skin-42357098.html
• Press and Journal: https://www.pressandjournal.co.uk/news/scotland/5432212/e-skin-developed-to-boost-self-awareness-in-soft-robots/

(Office: 1.13 Alexander Graham Bell)