Electronics and Electrical Engineering

Chair of Integrated Electronic Systems
+44(0)131 6505592
G.09 Scottish Microelectronics Centre
Electronics and Electrical Engineering
Integrated Micro and Nano Systems
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Prof Tughrul Arslan
  • BEng
  • PhD
  • Senior Member of The Institution for Electrical and Electronic Engineers (SMIEEE)
  • Fellow of the Institution for Engineering and Technology (FIET)
  • Chartered Engineer (CEng)
  • Embedded and Wireless Systems - MEng (year 5) and MSc
  • Radio Frequency Engineering - Year 4
  • Engineering Software -Year 3
  • Digital System Design - Year 3
  • Coordinator of MEng Programme
  • Leader Digital Teaching Subject Group
  • High Performance Reconfigurable Architectures
  • Low Power Design techniques and strategies.
  • Reliable Operating System and Software for Reconfigurable Systems
  • Positioning and Location Indoors and in Urban canyons
  • Use of sensors for positioning, localisation and tracking.
  • Use of wireless technologies for positioning, localisation and tracking.
  • Smart Antenna and Radio Frequency (RF) Systems
  • RF MEMS devices such as switches and phase shifters
  • Design for Mission Critical and Harsh environments
  • Evolvable, bioinspired, and adaptive hardware and software systems.
  • Multi-objective optimisation.
Director of International Students
+44(0)131 6505586
3.090 Faraday Building
Electronics and Electrical Engineering
Energy Systems
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Professor Aristides Kiprakis

I am an electrical power engineer by training, holding the Personal Chair of Agile Energy Systems at the School of Engineering of the University of Edinburgh.

As a member of the Institute for Energy Systems I lead the Agile Energy Systems Research Group, conducting interdisciplinary research in the areas of renewable energy conversion and integration, smart grids, and robotics and smart materials for energy applications. Our group currently comprises 9 Doctoral and Postdoctoral Researchers and has already graduated an additional 10 PhDs. Our research has generated ~100 peer-reviewed publications. 

My teaching includes courses on renewable energy, power and control engineering and research methods. I have a strong track record in developing and delivering courses and programme curricula at both under- and postgraduate levels.

My administrative roles include the School's Directorship of Internationalisation - Students, responsible for the strategic development and delivery of the School's international academic partnerships, while I am also the founding Programme Director of the MSc in Electrical Power Engineering and the 2-year MSc in Advanced Power Engineering.

  • BEng Electronics Engineering, Technological Educational Institute of Crete (TEIC), 1999
  • Postgraduate Diploma in Communications, Control & DSP, University of Strathclyde, 2000
  • PhD in Electrical Power Engineering, University of Edinburgh, 2005
  • Senior Member of the Institute of Electrical and Electronic Engineers (IEEE)
  • Member of the Institution of Engineering & Technology (IET)

Control & Instrumentation Engineering 3Course Organiser 3rd Year Mechanical Engineering / Electrical Engineering

Solar Energy & Photovoltaic SystemsCourse Organiser MSc in Sustainable Energy Systems / Electrical & Advanced Power Engineering

Solar Energy Conversion 5Course Organiser 5th Year MEng Undergraduate Programmes

Engineering Research Methods with Grand ChallengeCourse Organiser (2018-2021) Core course for all Engineering MScs

  • Power System Modelling
  • Distributed Generation
  • Renewable Energy
  • Smart Grids & Demand Side Management

Since 2018 I have been a Visiting Professor at the China-UK Low Carbon College of the Shanghai Jiao-Tong University, China. I am currently Associate Editor of the IET Smart Grid Journal and Member of the Editorial Board of the MDPI EnergiesJournal. I have also been Guest Editor for the Special Issue on Marine Energy, the Special Issue on Data-Driven Methods in Modern Power Engineering and the Special Issue on Advances in Electrical Power Conversion for Energy, Transportation and Industry Applications of the MDPI Energies Journal.

I am a Senior Member of the IEEE and Member of the IET. I am also an active STEM Ambassador for East Scotland, having organised several events promoting Science, Technology, Engineering and Mathematics to the public and especially primary and high school children, specifically in the areas of renewable energy and robotics.

Personal Chair of Engineering Biology
+44(0)131 6505663
3.7 Mary Bruck, 3.10 Mary Bruck
Electronics and Electrical Engineering
Bioengineering
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Professor Filippo Menolascina
Research Associate (C1) (ACAD - Researcher)
1.04-E Alrick Building
Electronics and Electrical Engineering
Energy Systems
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Mr Seyyed Mostafa Nosratabadi

 
  • 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.
Principal Experimental Officer
1.24D Murchison House
Electronics and Electrical Engineering
Integrated Micro and Nano Systems
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Dr Spyridon Stathopoulos
  • MSc Applied Physics - Nat. University of Athens - 2009
  • PhD Applied Physics - Nat. University of Athens - 2015
Senior Lecturer in AI and Computer Vision for Health
Electronics and Electrical Engineering
Imaging, Data and Communications
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Dr Steven McDonagh
Senior Lecturer
1.13 Alexander Graham Bell Building
Electronics and Electrical Engineering
Imaging, Data and Communications
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Yunjie Yang

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, machine learning, digital twins, soft sensors & electronics for robotics. His research has led to over 130 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, 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.

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). He served as the track/session chair of several international conferences. 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 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).

Research group: UoE SMART Group www.yangresearchgroup.com

Press coverages:

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

  • 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
  • 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.

Senior Lecturer and Director of Student Recruitment
+44(0)131 6507473
G.07 Scottish Microelectronics Centre
Electronics and Electrical Engineering
Integrated Micro and Nano Systems
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Dr Philip Hands
  • 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
Reader in Unconventional AI Hardware Technologies
1.24C Murchison House
Electronics and Electrical Engineering
Integrated Micro and Nano Systems
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Dr. Alexander Serb

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)

Reader
+44(0)131 6505599
2.08 Alexander Graham Bell Building
Electronics and Electrical Engineering
Imaging, Data and Communications
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Dr Javier Escudero Rodriguez

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