Imaging, Data and Communications

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Dr. Yunjie Yang is a Senior Lecturer (Associate Professor) at The University of Edinburgh. He is also an affiliate of the Edinburgh Futures Institute (EFI), the Edinburgh Generative AI Laboratory (GAIL) fellow, and part of the Edinburgh Centre for Robotics. He was the Chancellor’s Fellow in Data Driven Innovation (2018-2023) and Bayes Innovation Fellow (2023-2024). He received his PhD in Engineering Electronics from The University of Edinburgh, MSc in Control Science & Engineering from Tsinghua University, and BEng in Measurement & Control Engineering from Anhui University. In 2018, he briefly worked as a Postdoctoral Research Associate in Chemical Species Tomography at the University of Edinburgh before securing the lectureship.

His research interests focus on AI-powered sensing and imaging, soft sensors & electronics, soft robotics, and embodied/physical AI. His research takes a highly interdisciplinary approach, integrating Sensors, Materials, AI, Tomography, and Robotics (SMART) to advance autonomous physical intelligence. It has led to over 150 peer-reviewed journal and international conference publications, many of which were published in high-impact journals such as Nature/Cell portfolio journals (e.g., Nature Machine Intelligence), IEEE TNNLS, TMI, TIE, TII, 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 awardee of the prestigious European Research Council (ERC) Starting Grant (2024-2029) and ERC Proof of Concept Grant (2026-2027).

Dr. Yang serves as the Associate Editor of IEEE Transactions on Instrumentation and Measurement, IEEE Sensors Reviews, the Editorial Board Member of Scientific Reports, and the regular reviewer for over 70 high-impact international journals (including Nature, Nature Communications, PNAS, TRO, TMI, TIE, TII, TPAMI). He served as the track/session chair of several international conferences and was frequently invited for keynotes/seminars. He is the recipient of the 2024 IEEE J. Barry Oakes Advancement Award (For demonstrated exceptional expertise, innovation and leadership in the field of Instrumentation and Measurement), the IEEE I&M Society Distinguished Lecturer (2027-2029), 2015 IEEE I&M Society Graduate Fellowship Award, and multiple Best Paper/Poster Awards. He is a Senior Member of IEEE, a Fellow of the Young Academy of Europe (FYAE), a Fellow of the International Society for Industrial Process Tomography (FISIPT), and a Fellow of the Higher Education Academy (FHEA).

More information about the Yang Research Group: UoE SMART Group www.yangresearchgroup.com

Press coverage:

• UoE: https://www.ed.ac.uk/news/gloves-to-help-robots-get-to-grips-with-human-tasks
• EI: https://edinburgh-innovations.ed.ac.uk/news/sensor-gloves-could-help-robots-get-to-grips-with-human-tasks
• Channel 4: https://www.channel4.com/news/uk-scientists-finally-granted-eu-funding-post-brexit
• ERC StG: Dr Yunjie Yang awarded €1.5 million European Research Council Starting Grant | School of Engineering
• 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)
• The Independent: Best inventions and discoveries of 2023: From robot skin to mind-reading caps | The Independent
• 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

(Office: 1.13 Alexander Graham Bell (AGB) Building)

• Doctor of Philosophy (PhD), The University of Edinburgh, UK
• Master of Science (MSc) (Outstanding Graduate and Thesis), Tsinghua University, China
• Bachelor of Science (BEng) (Outstanding Graduate), Anhui University, China

• Senior Member of IEEE
• Senior Member and Distinguished Lecturer (2027-2029) of IEEE I&M Society
• Member of IET
• Fellow of ISIPT
• Fellow of the Young Academy of Europe (FYAE)
• Fellow of the Higher Education Academy (FHEA)

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

• Soft sensors & electronics
• Robotic perception
• Soft robotics
• Physical and embodied intelligence
• Tomographic imaging and applied machine learning

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

https://smcdonagh.github.io/

Prof. Mulgrew received his B.Sc. degree in 1979 from Queen's University Belfast. After graduation, he worked for 4 years as a Development Engineer in the Radar Systems Department at Ferranti, Edinburgh.

From 1983-1986 he was a research associate in the Department of Electrical Engineering at the University of Edinburgh.

He was appointed to lectureship in 1986, received his Ph.D. in 1987, promoted to senior lecturer in 1994 and became a reader in 1996.

The University of Edinburgh appointed him to a Personal Chair in October 1999 (Professor of Signals and Systems).

He currently holds the Royal Academy of Engineering Chair in Signal Processing.

His research interests are in adaptive signal processing and estimation theory and in their application to radar and audio systems.

Prof. Mulgrew is a co-author of three books on signal processing.

• 1987 Ph.D. University of Edinburgh
• 1979 BSc Queen's University Belfast

• 2012 Fellow of the Institute of Electrical and Electronics Engineers, FIEEE
• 2007 Fellow of the Royal Academy of Engineering, FREng
• 2002 Fellow of the Royal Society of Edinburgh, FRSE