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Muhammad Ghufran
Contact: M.Ghufran@hull.ac.uk
Office: 320, Third floor, Robert Black Burn Building, University of Hull
Muhammad Ghufran is a KTP Associate at the University of Hull, working in partnership with the Humberside Engineering Training Association (HETA) and the University’s Responsible AI Group.
His work focuses on developing TRIDENT, an immersive Industry 4.0 digital learning platform. TRIDENT combines industrial process rigs, real-time data, Artificial Intelligence, the Internet of Things, and Augmented and Virtual Reality to create practical learning experiences for engineering trainees.
Muhammad’s role involves digitising HETA’s manufacturing and process rigs, integrating PLC and SCADA systems with IoT data pipelines, and supporting the development of real-time monitoring, predictive-maintenance and AI-enabled learning tools. He is also contributing to the design of AR/VR visualisations and interactive training environments that allow learners to explore industrial processes safely and effectively.
Alongside the technical development of TRIDENT, Muhammad works with HETA staff and the academic team to create Industry 4.0 teaching materials, assessments and practical learning activities. He supports usability testing, stakeholder engagement, knowledge transfer and the long-term adoption of the platform within HETA’s training provision.
Before joining the KTP, Muhammad gained professional experience in industrial control systems, PLC and SCADA environments, renewable-energy engineering, electrical systems, project delivery and technical training. He holds an MSc in Project Management from the University of the West of Scotland, an MSc in Renewable Energy Engineering from Kingston University London, and a BSc in Electrical Engineering.
RESEARCH INTERESTS
Industry 4.0 and industrial digitalisation
Responsible AI for manufacturing and engineering
Digital twins and immersive learning
PLC, SCADA and industrial control systems
Internet of Things and real-time data systems
Predictive maintenance
Industrial training and knowledge transfer
Funded Research Projects as PI/Co-I
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PhD Students/Research Staff
List of PhD students Dr. Ma supervises.
PhD in Machine Learning and Data Mining for Cancer Care
My role: Principal Supervisor
Eamonn Tuton
PhD in Digital Twin Logistics of Operations and Maintenance for Offshore Wind Farms
My role: Principal Supervisor
Lewis Petch
PhD in Machine Learning and Data Mining for Cancer Care
My role: Co-supervisor
Manuel Pinheiro
Wellcome Trust project: “3D analysis of maxillofacial growth in patients with cleft lip and palate”.
PostDoc
China Scholarship Council project “Deep learning for plant disease detection”
Visiting Researcher
Qingmao Zeng