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Dr. Pavlos Tafidis is a Lecturer in Transport (Systems) Engineering at the School of Engineering, University of Edinburgh. His work integrates interdisciplinary approaches to advance transport planning and engineering, with a focus on smart and sustainable mobility solutions. PhD in Transport Engineering, Hasselt University (2022) M.Sc in Transport Planning, Aristotle University of Thessaloniki (2015) M.Eng in Transportation, Aristotle University of Thessaloniki (2013) He leads projects like "BikeHood" (Science Foundation of Ireland), developing Ireland’s first cycling neighborhood, and contributes to initiatives such as "REALLOCATE" (Horizon 2020) and "CISMOB" (Interreg Europe). His research emphasizes accessible mobility solutions, equity in transport infrastructure, and urban livability. Recent publications analyze cyclist crash hotspots using machine learning, electric bike route preferences via GPS data, and traffic-emission correlations in Dublin. His expertise spans digital twins, virtual reality, and geospatial analysis. Dr. Tafidis teaches courses including Transport Engineering 3, Transport and Society, and Multi-Scale Energy Demand, affiliated with the School of Engineering and Edinburgh Future Institute.

• Transport Planning
• Smart Mobility
• Sustainable Transportation
• +7 more

Dr. Hongye Zhang serves as a Lecturer in Superconducting and Cryogenic Electric Machines at the School of Engineering, University of Edinburgh, while maintaining a Visiting Research Fellow position at the University of Manchester. He actively contributes to the European Society for Applied Superconductivity (ESAS) as a Board Member and chairs the international HTS 2026 workshop. His educational foundation includes: BSc and MSc in Electrical Engineering from Xi’an Jiaotong University (2015, 2018) Diplôme d’ingénieur (MEng) from École Centrale de Lyon (2018) PhD in Applied Superconductivity from the University of Edinburgh (2021) Dr. Zhang’s research centers on decarbonizing transport through superconducting/cryogenic electric machines for hydrogen-powered aircraft, integrating artificial intelligence with superconductor technology and cryogenic techniques. His work targets net zero emissions by developing high-power-density propulsion systems that leverage hydrogen energy and advanced numerical modeling of superconductors. Analysis of his 2022-2025 publications reveals dominant themes in superconducting machine design for wind energy and electric aviation, with significant contributions to loss mitigation, flux pump technology, and trapped field magnet applications. His research bridges fundamental superconductor characterization with practical system integration for renewable energy. Recognized with the 2021 IEEE Council on Superconductivity Graduate Study Fellowship, his professional engagements include: Early Career Editorial Board Member for Elsevier’s Superconductivity journal Technical Editor for IEEE Transactions on Applied Superconductivity Program Committee Member for SMT 2023 He leads critical research within the £54-million H2GEAR project developing hydrogen-electric aircraft propulsion, while teaching Power Engineering 2 and Electrical Machines courses. His advisory roles span doctoral supervision and industry collaboration through Energy Systems research institute. Based at the University of Edinburgh’s Faraday Building, Dr. Zhang directs a research group focused on hydrogen energy applications and superconducting machine testing, with strong ties to the H2GEAR consortium and ESAS working groups.

• Superconductor Technology
• Cryogenic Techniques
• Electric Machines and Drives
• +3 more

Zhenhong Li is a Lecturer in Robotics and Control at the University of Manchester, holding an EPSRC Fellowship in physical human-robot interaction. He earned his B.Eng. from Huazhong University of Science and Technology (2013), and M.Sc. and Ph.D. in Control Engineering from the University of Manchester (2014 and 2019). Before joining Manchester in 2023, he was a Research Fellow in Rehabilitation Robotics at the University of Leeds (2019–2023). His research focuses on control technologies for human-robot systems, with applications in healthcare and industry. Key areas include physical human-robot interaction for rehabilitation, brain-computer interfaces, and neuromusculoskeletal modeling. He leads the Neurorobotics Lab (NRL) at Manchester and collaborates with healthcare professionals, industries, and designers via EPSRC/STFC/Wellcome Trust funding. Notable achievements include the 2019 Best Paper Award for Unmanned Systems and the 2020 EPS International Academic Pump-priming Award. In 2025, he was elected as a Senior Member of the IEEE. He actively organizes conferences and special issues, including the 2025 IEEE UK Robotics Conference and a Frontiers special issue on intelligent rehabilitation technology. Dr. Li supervises PhD candidates in robotics and control, emphasizing interdisciplinary approaches to human-robot interaction. His lab develops cutting-edge technologies like assistive exoskeletons and adaptive control systems for healthcare and industrial applications.

• Physical Human-Robot Interaction
• Rehabilitation Robotics
• Brain-Computer Interface
• +4 more

James Carroll is a Professor in the Department of Electronic & Electrical Engineering (EEE) at the University of Strathclyde, where he also serves as Director and Principal Investigator of the Wind and Marine Energy Systems and Structures CDT (2019–2027) and the Strathclyde lead for the EnerHy Wind and Hydrogen CDT (2024–2032). He is Co-Lead of the Wind Energy and Control (WEC) Group, one of the largest university-based wind energy research groups in the UK, comprising 8 academics and over 35 researchers. His research interests are centered on wind energy systems, with a focus on: Novel wind turbine concept development Wind turbine reliability and maintenance modeling Cost of energy and O&M cost modeling Drive train selection impact on reliability Condition monitoring and failure prediction of wind turbine components Data-driven machine learning and physical modeling for remaining useful life prediction SCADA and vibration data analytics The recent articles highlight a consistent trend in offshore and onshore wind energy innovation, with strong emphasis on predictive maintenance, cost reduction, digital twins, and novel turbine design. His work bridges engineering, data science, and sustainability, contributing significantly to renewable energy advancement. Scientific recognition includes: 2nd Place, Future Energy Competition (2019) James Carroll has been actively involved in major research projects, including EPSRC-funded CDTs and industry collaborations, focusing on hydrogen integration, digital twins for powertrains, and offshore wind maintenance optimization. He has also contributed to professional activities such as keynote speaking at the Wind Energy Science Conference 2019 and participation in EPSRC scoping workshops. He supervises research students and leads a dynamic team within the WEC Group, driving innovation in wind and marine energy systems. His research group, the Wind Energy and Control (WEC) Group, is a leading UK academic team in wind energy, fostering interdisciplinary collaboration and training the next generation of energy engineers through doctoral training programs.

• Wind Energy
• Wind Turbine Reliability
• Condition Monitoring
• +12 more

Xiaoze Pei is a Professor in the Department of Electronic & Electrical Engineering at the University of Bath, affiliated with the Institute for Advanced Automotive Propulsion Systems (IAAPS) and the Electronics Materials, Circuits & Systems Research Unit (EMaCS). His research focuses on superconductivity applications in electric systems, cryogenic power electronics, and DC network technologies for aerospace and renewable energy integration. Key projects include leading initiatives such as Towards Zero Emissions Electric Aircraft through Superconducting DC Distribution Network and HSTEA - Aerospace R&I , addressing challenges in electric propulsion, fault current limiters, and cryogenic power converters. His work contributes to UN Sustainable Development Goals related to clean energy and sustainable transport. Expertise: Superconducting fault current limiters (SFCL), DC circuit breakers, cryogenic power systems. Current roles: Principal Investigator (PI) on multiple UK and EU-funded projects. Collaborations: Extensive work with industry partners and academic institutions on electric aircraft, hydrogen control systems, and e-mobility technologies. Recent research emphasizes high-current cryogenic DC circuit breakers, superconducting air-core motors for aircraft, and topology optimization for power electronics. He actively supervises doctoral students in these areas and has published over 90 peer-reviewed articles. Labs/Teams: Leads research within EMaCS and collaborates with teams specializing in power electronics, cryogenics, and aerospace propulsion.

• Superconductivity
• Cryogenic Power Electronics
• Electric Aircraft Systems
• +6 more

Professor Antonio Griffo holds the position of Professor of Power Electronics and Electric Drives at the University of Sheffield's School of Electrical and Electronic Engineering. He leads the Electrical Machines and Drives Research Group and is involved in the High Reliability Drives Group. His academic journey includes a MSc (2003) and PhD (2007) in Electrical Engineering from the University of Naples, followed by research roles at Bristol and Sheffield Universities before becoming a Lecturer in 2013 and later a Professor. His research focuses on advanced control of electric drives, SiC-based power electronics for aerospace/renewables, fault detection in machines, and thermal management. Key projects include modeling hybrid AC/DC power systems for 'More Electric Aircraft', sensorless control techniques, and real-time simulation methodologies. He has pioneered work on SiC converter reliability, insulation monitoring, and condition-based maintenance systems. Publications (15+ in top journals like IEEE Transactions) emphasize innovative solutions for power electronics challenges, including voltage stress mitigation, thermal modeling, and fault tolerance. His work bridges theory and application, addressing critical issues in aerospace, renewable energy, and electric vehicle systems. Griffo also contributes to educational advancements through modular training platforms for power electronics education. Labs/Teams: Active in the Electrical Machines and Drives Research Group, focusing on high-reliability drive systems and sustainable energy technologies. Collaborates with industry on projects like the EPSRC Offshore Wind Prosperity Partnership.

• Power Electronics
• Electric Drives
• SiC Power Converters
• +5 more

Professor Alasdair McDonald holds the Chair in Renewable Energy Technology at the School of Engineering, University of Edinburgh . His work focuses on the integrated electrical-magnetic-mechanical modeling and design of large electrical machines for offshore renewable energy systems , particularly wind turbine powertrains . He previously served as a Lecturer, Senior Lecturer, and Reader in Wind Turbine Technology at the University of Strathclyde. Education: PhD in Structural Analysis of Low-Speed, High-Torque Generators (University of Edinburgh, 2008) MEng (Hons) in Integrated Electrical & Mechanical Engineering (University of Durham, 2004) Research Interests: Design of permanent magnet electrical machines for wind and marine energy Lightweight generator structures and advanced manufacturing methodologies Condition monitoring using SCADA and vibration data Cost of energy optimization for offshore renewables Projects: STREAM 1: Innovations in Forth/Tay Offshore Wind Clusters (EPSRC, 2025-2029) Wind2DC: Medium Voltage DC Power Take-Off Systems (EPSRC, 2023-2026) PV054: Modular Generators for Floating VAWTs (EPSRC & SeaTwirl AB, 2023) Media Contributions: Quoted in research media about floating hydrogen production systems (2025)

• Offshore Wind Energy
• Renewable Energy Systems
• Electrical Machine Design
• +5 more

Chris Freeman is a Professor of Robotics and Control at the University of Southampton's Electronics and Computer Science (ECS) school. His research focuses on iterative learning control theory, biomedical engineering, and robotics with applications in industrial automation and healthcare. As Deputy Head of School (Equity, Diversity and Inclusion) and Chair of the ECS Belonging, Inclusion, Diversity and Equity (BIDE) Committee, he drives initiatives promoting inclusive academic environments. Freeman leads multidisciplinary research projects such as "Towards intelligent, pervasive, high performance control system architectures" "Elder Athletes: building incidental interaction at home" "Low-cost personalised instrumented clothing with integrated FES electrodes" . His work combines robotics, functional electrical stimulation (FES), and wearable technologies to develop rehabilitation systems for stroke patients and industrial automation solutions. His recent publications demonstrate expertise in iterative learning control (ILC), model predictive control, and biomedical applications. Research groups include: Digital Health and Biomedical Engineering Institute for Life Sciences Centre for Health Technologies Centre for Robotics

• Iterative Learning Control
• Repetitive Control Theory
• Biomedical Engineering
• +7 more

Professor Kais Atallah is a Professor in Electrical Engineering at the University of Sheffield's School of Electrical and Electronic Engineering, with a secondary role as a Lecturer in Aerospace Engineering. He joined the University in 1989 as a PhD student and became academic staff in 2000. His research focuses on electromechanical energy conversion, magnetic torque systems, and applications in renewable energy, electric vehicles, and aerospace actuation. He is a member of the Centre for Research Into Electrical Energy Storage and Applications (CREESA) and leads the Electrical Machines and Drives Research Group. His research interests include novel drivetrain designs for wind turbines, flywheel systems, and fault-tolerant machine systems for safety-critical aerospace applications. He has advised multiple PhD students and contributed to over 150 publications, with recent work emphasizing magnetic gear design, high-performance ferrite machines, and modular multilevel converters. His articles explore themes like high-efficiency power transmission, magnetic gear optimization for wind turbines, and traction machine control systems. Collaborations include work on subsea ROV propulsion and flywheel energy storage. He oversees research labs focused on advanced electrical machine design and energy storage solutions.

• Electromechanical Energy Conversion
• Magnetic Torque/Force Transmission Systems
• Renewable Energy Systems
• +4 more

Soteris Demetriou is a Senior Lecturer of Computer Systems Security at Imperial College London's Department of Computing, within the Faculty of Engineering. He leads the Applications, Platforms, and Systems Security (APSS) Research Lab and directs the Academic Centre of Excellence in Cyber Security Research (ACE-CSR). His research focuses on securing mobile, IoT, and cyber-physical systems through techniques like explainable AI, reverse engineering, and trusted computing. Notable contributions include tools for privacy preservation in machine learning models, detection of LiDAR spoofing attacks, and securing Android's middleware. Education: PhD and MSc in Computer Science (University of Illinois at Urbana-Champaign), Diploma in Electrical and Computer Engineering (University of Patras). Research Interests: Mobile/IoT security, AI security, trusted computing, and vulnerability analysis. Key areas include privacy in generative models, adversarial attacks on autonomous systems, and large-scale distributed systems. Publications: Over 50 peer-reviewed papers in top venues like NDSS, CCS, and SOSP. Recent work addresses privacy in speech generation, LiDAR security for autonomous vehicles, and hyperscale serverless architectures at Meta. Awards: Distinguished Paper Award at NDSS 2018, Best Paper at SafeThings 2024, and multiple travel grants. Served on technical committees for PETS, CCS, and AutoSec. Grants & Collaborations: SPRITE+ grant for Bio-IoT security, collaboration with Meta on distributed systems, and leadership in ACE-CSR. Labs: APSS Lab focuses on systems and AI security, with interdisciplinary projects in healthcare and autonomous systems.

• Computer System Security
• Cyber-Physical Systems Security
• Machine Learning Security
• +3 more

Sohag Kabir is an Associate Professor in the School of Computer Science, Artificial Intelligence, and Electronics at the University of Bradford. He leads the MSc Big Data Science and Technology, MSc Artificial Intelligence and Machine Learning, and MSc Applied Computer Science and Artificial Intelligence programs. He holds a Ph.D. in Computer Science from the University of Hull (2016), an M.Sc. in Embedded Systems, and a B.Sc. in Computer Science and Engineering. Dr. Kabir's research focuses on safety, reliability, and security assurance of cyber-physical autonomous systems. His work includes model-based safety analysis, probabilistic risk assessment, dynamic reliability analysis, and stochastic modeling. Current projects address IoT security, machine learning certification for automotive systems, and dependability frameworks for complex systems. His publications demonstrate consistent focus on developing integrated frameworks for system dependability, with recent work emphasizing IoT security, autonomous vehicle safety, and AI certification challenges. Dr. Kabir has contributed to multiple EU-funded projects including DEIS (Dependability Engineering Innovation for Cyber-Physical Systems) and MAENAD (Model-based Analysis & Engineering of Novel Architectures for Dependable Electric Vehicles).

• Cyber-Physical Systems
• System Safety Assurance
• Model-Based Engineering
• +2 more

Dr. Mohammad Yazdani-Asrami is a Lecturer in Electrically Powered Aircraft and Operations at the Autonomous Systems & Connectivity (ASC) division of the James Watt School of Engineering, University of Glasgow. He leads research in electrification and cryo-electrification of transportation, particularly in aviation, leveraging applied superconductivity and AI techniques. His research interests span the Electrification and cryo-electrification of power and transportation systems Design of superconducting components (machines, cables, fault current limiters) for aviation Application of AI, machine learning, and big data in engineering and superconductivity Hydrogen electrolysis, production, and integration in aerospace and power networks His recent publications demonstrate a strong trend toward intelligent modeling and AI-driven solutions in superconducting technologies, with a focus on electric aircraft, fault protection, and thermal management using cryogenic fluids. Dr. Yazdani-Asrami has received notable scientific recognition, including: UK Royal Academy of Engineering Global Talent (2021) Young Professional of the Year, Cryogenic Society of America (2023) He actively supervises PhD students and hosts visiting researchers. His advising portfolio includes Alireza Sadeghi, Kerr Smith, Dedao Yan, Giacomo Russo, and Fábio Gregório. He has secured funding from the EPSRC, University of Glasgow, and CSC for PhD students. He also supports postdoctoral fellowships from the Royal Academy of Engineering, Leverhulme Trust, and Marie Skłodowska-Curie actions. He is involved in several research groups and collaborations, particularly within the Aerodynamics, Propulsion and Electrification group. His editorial roles include serving on the boards of Superconductor Science and Technology , World Journal of Engineering , Aerospace Systems , and others. He regularly contributes to major conferences such as the Applied Superconductivity Conference and the International Conference on Magnet Technology.

• Electrification of Transportation
• Cryo-electrification
• Applied Superconductivity
• +12 more

Professor Geraint Jewell is affiliated with the University of Sheffield , serving as Director of the Rolls-Royce University Technology Centre in Advanced Electrical Machines (since 2006) and Director of the EPSRC Future Electrical Machines Manufacturing Hub (since 2019). He is a graduate of the university (BEng 1988, PhD 1992) and has held academic roles since 1994. EPSRC Advanced Research Fellowship (2000-2005) Royal Society Industry Fellowship at Rolls-Royce (2006-2008) Former Faculty Director of Research and Innovation (2008-2011) Former Head of Department (2013-2019) His research focuses on power-dense electrical machines for aerospace applications , including permanent magnet machines , switched reluctance machines , and linear actuators . He has supervised ~20 PhD students and led collaborations with Rolls-Royce on high-temperature devices (up to 800°C) and aero-engine starter-generators. Recent publications analyze stator insulation thermal degradation , eddy current control in additively manufactured materials , and magnetic loss prediction in silicon steel. His work spans electromagnetic modeling , core loss calculation , and advanced manufacturing techniques for electrical machines. EPSRC Advanced Research Fellowship (2000-2005) Royal Society Industry Fellowship (2006-2008) He has advised PhD students across topics like consequent-pole PM machines , doubly salient SynRMs , and core loss characterization . His Electrical Machines and Drives Research Group explores modular motor design and magnetic material optimization for aerospace and electric vehicles.

• Electrical Machines
• Electromagnetic Modeling
• Aerospace Applications
• +10 more

Michael Galea is a Professor of Electrical and Electronic Engineering at the University of Nottingham and serves as Co-director of the Propulsion Futures Beacon. His research focuses on advanced electrical machines and drives, emphasizing thermal management, reliability, and insulation degradation. Research Areas: Design and analysis of electrical machines Thermal management strategies Reliability engineering for electrical systems Insulation degradation and lifetime prediction

• Electrical Engineering
• Electronic Engineering
• Thermal Management
• +3 more

Majid Taghavi is a Research Fellow at the Department of Bioengineering, Faculty of Engineering, Imperial College London. He leads the Soft Robotic Transducer Lab, focusing on developing advanced soft actuators for healthcare and robotics applications. Previously, he held a postdoctoral position at the University of Bristol’s SoftLab, where he pioneered artificial muscle technologies. He earned his PhD in BioRobotics from Scuola Superiore Sant'Anna with highest honors and an Italian Institute of Technology (IIT) scholarship. His research interests include soft robotics, materials engineering, and actuator design. Key projects involve creating monolithic soft robots with self-sensing, variable stiffness, and high contraction actuators. Recent work explores applications in wearable, implantable, and surgical robotics. Notable achievements include developing electric actuators with 98% contraction and human-muscle-equivalent power density. His articles highlight advancements in electrostatic actuators, dielectric elastomers, and biomimetic designs. Awards include the IIT scholarship and academic honors for doctoral work. He advises on open positions in his lab and collaborates across disciplines. His labs (Soft Robotic Transducers Lab and Robotics Forum) drive innovations in soft robotics systems and transducers.

• Soft Robotics
• Materials Engineering
• Mechanical Engineering
• +5 more