Dr Erfu Yang

Reader

Design, Manufacturing and Engineering Management

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Personal statement

Dr Erfu Yang is a Reader in Robotics and Autonomous Systems (RAS) Group within the Department of Design, Manufacturing and Engineering Management (DMEM) at the University of Strathclyde. He is the Co-lead of the RAS Group, program lead of MSc in Mechatronics and Automation, Vertically Integrated Projects (VIP) champion, Mechatronics theme champion of both UG and MSc.   In 2008, he received his Ph.D. degree in robotics from the University of Essex, Colchester, UK, within the School of Computer Science and Electronic Engineering.  Before joining the DMEM in May 2014, he was a research fellow in the Cognitive Signal Image and Control Processing Research (COSIPRA) Laboratory at the University of Stirling, UK. Previously, as a research fellow he also worked in the Department of Mechanical and Control Systems Engineering (Tokyo Institute of Technology, Japan) and School of Engineering (University of Edinburgh, UK). His main research interests include robotics, autonomous systems, human-robot collaborations, computer vision, image/signal processing, mechatronics, manufacturing automation, and applications of machine learning and artificial intelligence. He has over 200 publications in these areas, including more than 100 journal papers and 10 book chapters. He is Stanford’s Top 2% Scientist for 2024 & 2025. Dr Yang has been awarded over 15 research grants as PI (principal investigator) or CI (co-investigator). He is the Fellow of the UK Higher Education Academy, Member of the UK Engineering Professors’ Council,  Senior Member of the IEEE Society of Robotics and Automation, IEEE Control Systems Society, IEEE Systems, Man, and Cybernetics Society, Publicity Co-Chair (pre-April 2024) and now Engagement Chair of the IEEE UK and Ireland Industry Applications Chapter. Dr Yang serves as an associate editor, and editorial board member for many international journals, including Cognitive Computation (Springer), Sensors, Manufacturing Review, Frontiers in Robotics and AI, etc.

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Publications

Robotic teleoperation in hazardous environments : A review of feedback architectures, stability, and learning-based adaptation
Khedr Mohamed, Le Quang Dan, Cameron-Robson Tye, Morsi Nour, Yang Erfu, Luo Chaomin
Complex Engineering Systems (2026)
Engineering design through dialogue : a method for analysing speech-based human-AI conversation
Gunn Kieran, Brisco Ross, Holliman Freddie, Yang Erfu, MacFie Rebecca
Proceedings of the Design Society Vol DESIGN 2026 (2026)
SMART: Semantic Merging Adaptive Regional Transformer for Image Captioning
Jiang Fengling, Cao Yujin, Zou Le, Yang Erfu, Li Chenglong, Luo Chaomin
IEEE Transactions on Multimedia (2026)
KMPS : a reinforcement learning scheduler for Kubernetes edge-cloud systems
Huang Congyue, Tan Wei, Ou Miaohua, Yang Erfu, Li Yun
IEEE Internet of Things Journal Vol 13, pp. 16021-16034 (2026)
https://doi.org/10.1109/jiot.2026.3658608
Human-autonomy teaming in robot navigation using bioinspired approach for search and rescue
Sellers Timothy, Lei Tingjun, Luo Chaomin, Yang Erfu, Bi Zhuming
IEEE Transactions on Human-Machine Systems Vol 56, pp. 311-320 (2026)
https://doi.org/10.1109/thms.2026.3651248
A neural field approach to robot navigation with brain-inspired goal-directed cognitive maps
Hicks Matthew, Lei Tingjun, Sellers Timothy, Luo Chaomin, Yang Erfu
2025 IEEE International Conference on Robotics and Biomimetics (ROBIO) 2025 IEEE International Conference on Robotics and Biomimetics (ROBIO) 2025 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 269-276 (2026)
https://doi.org/10.1109/robio66223.2025.11377267

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Professional Activities

The 30th International Conference on Automation and Computing
Chair
29/8/2026
Examiner
Examiner
16/6/2026
Examiner
Examiner
5/6/2026
DMEM Research Seminar on Connecting Researchers, Systems, and Communities: IEEE SMC and AI in One Health
Organiser
5/6/2026
International Journal on Interactive Design and Manufacturing (Journal)
Guest editor
1/5/2026
MDPI UK Editors' Forum (Event)
Editor
29/4/2026

More professional activities

Projects

Inclusive Network Pathways for Human-Robot-AI Healthcare Research and Knowledge Exchange
Yang, Erfu (Principal Investigator) McGeown, William (Co-investigator) Buchanan, Sarah (Co-investigator) Ait Ameur, Mohamed Adlan (Post Grad Student)
This project will build CONNECT-HRC-AI Healthcare as an inclusive, visible and sustainable RKEI culture network for human-robot-AI healthcare research and knowledge exchange at Strathclyde. The purpose is to use conference engagement as an evidence-gathering and external-learning stage that informs a wider programme to connect existing expertise, make contributions visible, and create practical collaboration pathways. The project responds directly to the RKEI culture challenge identified at Strathclyde: relevant activity already exists, but people, capabilities, opportunities and everyday contributions are often fragmented, unevenly visible and difficult to connect.
The network will build on initial collaborative work between DMEM and the Department of Psychology, using existing MICA/social robotics and AI-in-the-loop healthcare research as a concrete anchor (Ait Ameur et al., 2025). However, the purpose of the network is to broaden this collaboration beyond a single doctoral project, laboratory, or discipline. Human-robot-AI healthcare brings together engineering and robotics, computer science and AI, psychology and cognitive science, health and wellbeing research, ethics, design, data governance, technical support, professional services and knowledge exchange, clinicians, formal care partners, and lived-experience or community voices. It therefore provides a strong test case for the kind of inclusive, visible, and sustainable collaborative research culture that the RKEI Network aims to enable.
The project will build on existing Strathclyde activity rather than create a disconnected new group. It will follow a structured mapping approach inspired by existing institutional network analysis: identify relevant people, themes, projects, facilities, datasets, methods and gaps; validate this map through expert-led workshops; and convert it into collaboration pathways, pitch ideas and future grant routes. Participants will be selected through a combination of targeted invitations across faculties and roles, open expressions of interest, doctoral/researcher networks, KE contacts and existing health, cognitive science, digital, design and robotics links.
01-Jan-2026 - 14-Jan-2026
Cobot-enabled Nondestructive Quality Control in Production Lines with Advanced Vision and Machine Learning for Smart Manufacturing
Yang, Erfu (Principal Investigator) Millar, Richard (Co-investigator) Cameron-Robson, Tye (Researcher)
The overall research aim of this project is to fundamentally investigate the novel Cobot-enabled nondestructive quality control strategies by enabling holistic control and interactions of collaborative robots in complex human-robot collaborative manufacturing environments such that safety and interaction of nearby humans/operators can be maintained while the in-process inspection and quality control are being done. It is also critical to understand how to ensure the efficiency and flexibility of the manufacturing process can be achieved when process variations or environmental changes occur in advanced manufacturing systems. It is important that the Cobot-enabled nondestructive quality control is able to work collaboratively in a safe manner around a designated area of production lines, such as automated egg packaging stations. In a busy manufacturing environment, there can be no errors leading to production down.
01-Jan-2025 - 30-Jan-2028
Bio-Inspired Robotics Design and Development (BioRobotics)
Yang, Erfu (Principal Investigator)
The Bio-Inspired Robotics Design and Development (BioRobotics) is led by Queen's University Belfast in collaboration with University of Liverpool and Strathclyde to explore the fundamental science (low TRL:1-2) and to develop a standard framework that facilitate the transformation from biological mechanisms to robotics design and operation, especially forced on new sciences of robotics assembly, navigation in fluid environment, and multi-agent collaboration.
06-Jan-2024 - 30-Jan-2026
KTP - Glenrath Farms Ltd. Development of an intelligent collaborative robot system for smart farm manufacturing (iCoBOTS).
Yang, Erfu (Principal Investigator) Maier, Anja (Co-investigator) Masood, Tariq (Co-investigator)
01-Jan-2024 - 31-Jan-2026
Intelligent Human-Robot Collaboration for Future Advanced Healthcare Applications
Yang, Erfu (Principal Investigator) Liang, Sha (Co-investigator) Ait Ameur, Mohamed Adlan (Researcher)
The aim of this project is to investigate an intelligent human-robot interaction for advanced healthcare applications, which will leverage advanced computer vision, robotics, artificial intelligence to enable patent-oriented medical and health functions. Together with the cutting-edge human friendly robot system such as cobots to form a new advanced intelligent human-robot system, realise the robot healthcare applied in patients’ home, hospitals and other complex environments to achieve autonomous activities, active identification, assistance and emergency treatment, and alarm functions of sudden diseases, and remote coordination with caregivers and doctors to provide accurate support and assistance for their care, and complete the care and treatment of the elderly and patients.
01-Jan-2023 - 30-Jan-2026
Adaptive Path Planning and Visual Navigation of Autonomous Inspection Robots in Challenging Environments
Yang, Erfu (Principal Investigator) Dobie, Gordon (Co-investigator) Jiang, Meiling (Researcher)
This project aims to fundamentally investigate the novel adaptive path planning and visual navigation of robots (such as an industrial robot manipulator, Cobot, UAV etc.) for autonomous inspection by enabling holistic control and interactions of robots in complex, dynamic and changing environments such that safety and interaction of nearby humans/operators/other objects etc. can be maintained while the inspection tasks are taking place. At the same time, the efficiency and flexibility of the inspection process is also achieved when process variations or environmental changes take place.
01-Jan-2022 - 30-Jan-2025

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Contact

Dr Erfu Yang
Reader
Design, Manufacturing and Engineering Management

Email: erfu.yang@strath.ac.uk
Tel: 574 5279