Electronics and Electrical Engineering

Dr Sun is a Chancellor's Fellow (equivalent to AP) in Energy Systems Integration within the School of Engineering. His research focuses on planning and operating low-carbon energy systems with high renewable penetration, using applied data science and advanced optimization techniques. Dr Sun previously worked on building a multi-scale energy system integration architecture for National Centre for Energy Systems Integration (CESI) and as a lead researcher on Hydrogen’s Value in the Energy system (HYVE).

Dr Sun has also contributed to Realising Energy Storage Technologies in Low-carbon Energy Systems (RESTLESS) and Adaptation and Resilience In Energy Systems (ARIES).

Dr Sun is holding a visiting research fellowship at UCL.

Latest Press Coverage: Climate Prediction Market Competition Winner

• PhD Electrical Power Engineering, University of Edinburgh, 2015

• Chartered Engineer (CEng)
• Member of the Institution of Engineering & Technology (IET)
• Member of the Institute of Electrical and Electronic Engineers (IEEE)

• Hydropower Interdisciplinary Group Design Project [MEng]
• Electrical Engineering Fundamentals of Renewable Energy [MSc]
• MSc Sustainable Energy Systems - Dissertation supervision
• MSc Advanced Power Engineering - Dissertation supervision

• Network Integration of DER
• Electricity Network Modelling
• Gas/Hydrogen Network Modelling
• Climate Change Impacts on Renewable Energy
• Optimisation Modelling
• Statistic analysis
• Data Science applications in Power Systems

https://twitter.com/themispr

Themis holds the Regius Chair of Engineering at the University of Edinburgh and is Director of the Centre for Electronics Frontiers. His work focuses on developing metal-oxide Resistive Random-Access Memory technologies and related applications and is leading an interdisciplinary team comprising 30 researchers with expertise ranging from materials process development to electron devices and circuits and systems for embedded applications. He holds a Royal Academy of Engineering Chair in Emerging Technologies and a Royal Society Industry Fellowship. He is an Adjunct Professor at UTS Australia, visiting Professor at the Department of Microelectronics and Nanoelectronics at Tsinghua University, and Honorary Fellow at Imperial College London. He is Fellow of the Royal Society of Chemistry, the British Computer Society, the IET and the Institute of Physics and is also Senior Member of the IEEE. He served as the Director of the Lloyds Register Foundation International Consortium for Nanotechnology and Co-Director of the UKRI Centre for Doctoral Training in Machine Intelligence for Nano- Electronic Devices and Systems (MINDS). In 2015, he established ArC Instruments Ltd that delivers high-performance testing infrastructure for automating characterisation of novel nanodevices in over 21 countries and in 2019 he founded SoneT.ai that is building new power-efficient AI hardware solutions. His contributions in memristive technologies and applications have brought this emerging technology one step closer to the electronics industry for which he was recognised as a 2021 Blavatnik Award UK Honoree in Physical Sciences and Engineering.

I lead a research group focused on developing and applying signal processing algorithms to biomedical data. Our main aim is to reveal the subtle changes that major diseases (e.g., Alzheimer's and epilepsy) cause in the brain activity and how this changes in different conditions and mental states.

In October 2013, I joined the Institute for Digital Communications, School of Engineering, as a Chancellor's Fellow in biomedical signal processing. I was tenured in August 2016 and promoted to Senior Lecturer in August 2020.

Previously, I held a post-doctoral position at the School of Computing and Mathematics of Plymouth University.

My training includes an MEng in telecommunications engineering from the University of Valladolid (Spain) in 2005 and a PhD in biomedical signal processing from the same university in 2010.

• 2010 - PhD in Telecommunications Engineering - University of Valladolid (Spain)
• 2005 - MEng in Telecommunications Engineering (First) - University of Valladolid (Spain)

• Senior Member of the IEEE
• Fellow of the Higher Education Academy

• Programme Director of the MSc in Signal Processing and Communications
• Course organiser of Image Processing
• Teacher in Engineering Software 3
• Tutor in Engineering Mathematics 2A
• Supervision of final year projects and MSc theses

• Biomedical signal processing
• Brain connectivity
• Graph theory
• Machine learning
• Nonlinear analysis

Dr. Serb is a reader in Unconventional AI Hardware Technologies at the University of Edinburgh.

He is a MIET and SMIEEE.

He has led a grant portfolio of ~£2M worth of projects, including a DSTL contract for studying the feasibility of adiabatic capacitive neural networks and the UKRI New Investigator Award "ANAGRAM".

He has further been a co-investigator in UKRI MINDS CDT.

He has supervised 20+ PhD students and 6× postdocs. His research interests span across circuit and system design and AI, with particular focus on emerging technologies such as memimpedance elements.

He has published 50+ journal articles and 50+ conference papers, and filed 5× patents.

Furthermore, he is co-founder and CTO of ArC instruments ltd., a company that manufactures instrumentation for memimpedance device characterisation and testing (https://www.arc-instruments.co.uk/).

PhD degree in EEE - Imperial college, London, 2014.

MEng degree in BioMedical engineering - Imperial college, London, 2009

MIET - Member of the IET

SMIEEE - Senior member of the IEEE

ELEE08015 - Digital System Design 2

PGEE11136 - Applications of Sensor and Imaging Systems (component module leader)

• 2007-2012: Postdoctoral Research Associate, Department of Engineering, University of Cambridge
• 2003-2007: Postdoctoral Research Associate, Department of Physics, University of Durham
• 1995-1999: MSci Physics, University of Durham
• 1999-2003: PhD Condensed Matter Physics, University of Durham

• Microelectronics 2 (Lecture course)
• Electromagnetics 3 (Lecture course)
• Electromagnetics 4 (Lecture course)
• Applications of Liquid Crystals in Sensing (Lecture course)
• Electrical Engineering 1 (Tutorials)
• Electronics Project Laboratory 2A (Labs)
• Electronics Project Laboratory 2B (Labs)

• MicroRNA biosensors
• Adaptive photonic systems and devices
• Liquid crystal lenses
• Polymer composites
• Liquid crystals
• Liquid crystal lasers
• Wireless and flexible pressure sensors for wearable electronics

• Google Scholar

Dr. Yunjie Yang is a Senior Lecturer (US Equivalent: 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. After his PhD, he briefly worked as a Postdoctoral Research Associate in Chemical Species Tomography at The University of Edinburgh before he secured the lectureship.

His research interests focus on AI-powered sensing and imaging, soft sensors & electronics for robotics, and AI for robotics. 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 (Nature Machine Intelligence, Communications Engineering), 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).

Dr. Yang serves as the Associate Editor of IEEE Transactions on Instrumentation and Measurement, the Editorial Board Member of Scientific Reports, the Guest Editor of IEEE Sensors Journal, and the regular reviewer for over 70 high-impact international journals (including 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), 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:

• 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 of IEEE I&M Society
• Member of IET
• Fellow of ISIPT
• Fellow of Young Academy of Europe (FYAE)
• Fellow of 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 (especially flexible tomography)
• AI for 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/

Spyros has a background in semiconductor physics and currently works on the realisation, fabrication and characterisation ofnovel devices based on semiconductors and thin films. His main research interest is around heterogeneous integration of thin filmsand semiconductors to enable applications in novel memories and beyond-CMOS electronics. He is also responsible for developingnew fabrication and testing processes that cut across the different CEF areas of research.

• MSc Applied Physics - Nat. University of Athens - 2009
• PhD Applied Physics - Nat. University of Athens - 2015

I'm a Research Associate in Energy Market Integration for Grid-Scale Storage at the School of Engineering, University of Edinburgh. Prior to this, I’ve been a Faculty Member at the Department of Electrical Engineering at Sirjan University of Technology, Iran, from Jun. 2017. I have Ph.D. in Electrical Engineering-Power Systems from the University of Isfahan, Iran obtained in Oct. 2016 and my thesis title was “Generation Scheduling of a Virtual Power Plant Considering Industrial Microgrids in Power Systems”. My Ph.D. dissertation discusses about a transmission power network that is actively working under a regional electric company, and different VPPs within this system are included various types of distributed generation units like wind powers and demand response loads. The purpose was focused on industrial VPP and its management under a stochastic environment in a short-term power market. From Oct. 2015 to Apr. 2016, as a visiting researcher, I’ve worked on VPP self-scheduling problem in a power system and robust optimization method and I’ve also worked on day-ahead and intraday power markets of MIBEL (Iberian Electricity Market) in Electrical Engineering Department of Universidad de Castilla – La Mancha, Spain. I’ve been also involved as PI or Co-PI in 5 research projects within the power and energy systems field funded through universities or companies.

• Ph.D. in Electrical Engineering, University of Isfahan, Iran, 2016.
• M.Sc. in Electrical Engineering, University of Kashan, Iran, 2011.
• B.Sc. in Electrical Engineering, Shahid Bahonar University of Kerman, Iran, 2008.