Digital Twin Dynamics: A Multi‑Disciplinary Debate

Adnan Khattak (aka Eddy) presently works for Siemens Healthineers in the United Kingdom and is the Vice Chair of the IET Particle Accelerators Engineering Network (PAEN).

In the past, he held engineering and technical management roles, with primary expertise in medical particle accelerators and superconducting high field MRI systems engineering support.

He has a keen interest in emerging and collaborative developments in industrial AI and the digital twinning of complex systems in the MedTech Industry, particularly where these are informed by domain-specific expertise. 

He holds a BSc. Electrical Engineering from University of Engineering and Technology, Pakistan, MBA in Entrepreneurship from the University of Wolverhampton and pursues CPD at Siemens, the University of Oxford and Imperial College London. 

Dr. Jon Stammers is a researcher and leader at the University of Sheffield, specialising in the intersection of advanced manufacturing and digital intelligence.

With a background in Electronic Engineering (MEng and PhD), his career at the University has focused on the practical application of data and machine learning to solve complex industrial challenges.

At the AMRC, Jon leads the Data, Connectivity and AI theme, within the Integrated Manufacturing Group, researching methods for integrating data and analytics into the core of modern advanced manufacturing.

In September 2025, Jon was appointed as the Joint Theme Lead in AI for Engineering and Manufacturing for the University’s Centre for Machine Intelligence (CMI). In this capacity, he acts as a bridge between fundamental AI research and its real-world application in manufacturing. 

Ian Nock is a leading consultant and entrepreneur in the Media & Entertainment industry, specializing in technology strategy, product development, and delivery.

As Managing Consultant of Fairmile West, he has helped launch over 20 major video entertainment services across Europe since the late 1990s, providing specific expertise to startups, small, medium and large companies.

Ian is also a key figure in advancing next-generation video and audio technologies, serving as Chair of the Ultra HD Forum Interoperability Group and Vice Chair of the IET Media Technical Network. A Fellow of the SCTE and a member of the IET, SMPTE, and IEEE BTS, Ian actively promotes sustainability and innovation through his writing, public speaking, and industry leadership.

Marc Thomas is an engineer and researcher at NATS, the UK's primary air traffic services provider, specialising in digital twins and machine learning for complex operational systems.

He is currently Digital Twin Lead on Project Bluebird, an industry-academic collaboration developing a probabilistic digital twin of UK airspace to evaluate AI air traffic control agents against real-world traffic scenarios. His work focuses on how high-fidelity simulation, uncertainty modelling and operational data can support the development and evaluation of emerging AI systems.

Marc's background spans air traffic management, rail technology, data science, physics and medicine. He is a Visiting Professor at Queen Mary University of London and holds degrees in data science, physics and medicine.

Dr Zhouxiang Fei is a Lecturer in Computer Science at Liverpool Hope University, a Fellow of the Higher Education Academy (FHEA), and holds a PhD in Electrical Engineering and Electronics from the University of Liverpool. His expertise spans artificial intelligence, machine learning, computational modelling, and digital technologies for critical infrastructure applications.

Prior to joining Liverpool Hope University, he worked as a Postdoctoral Research Associate at the University of Strathclyde, leading research in predictive modelling, anomaly detection, data analytics, and explainable AI for safety-critical sectors including nuclear energy and infrastructure monitoring.

Dr Fei has extensive experience translating advanced computational research into industrial applications, including the development of AI-driven inspection systems, predictive maintenance frameworks, and data-driven decision support tools. His current research interests include digital technologies for critical infrastructure, knowledge-driven AI, anomaly detection, and the safe adoption of disruptive technologies through intelligent systems and digital twins.

John Easton is Professor of Sustainable Transport at Heriot-Watt University in Edinburgh, where his research focuses on the use of digital twins as a decision support tool in the decarbonisation of urban transport systems as part of the UKRI-funded TransiT project.

Before moving to Heriot-Watt in the summer of 2025, John spent over 20 years at the University of Birmingham, where he led the “data, information, and cyber security” research theme in the Birmingham Centre for Railway Research and Education.

A past chair of the IET Railway Technical Network, John believes in maintaining a strong link between academia, industry and policy makers; he is a member of DfT’s College of Experts, and sits on the Rail Safety and Standards Board’s Data and Information Systems Interface Committee (DISIC).

Mark is a high technology venture capitalist with industrial, financial, scientific, and engineering skills, focusing on supporting new technology businesses. 

He has worked at BAC, Xerox, the Kaye Organisation, Prutec, Charterhouse, managed Central European privatisations, and worked with the University of Exeter to create start-ups and build bridges to companies. Mark has raised and managed hands-on early-stage venture funds, investing in the UK, Europe and the US. 

He now specialises in derisking early-stage investments and developing ways of accelerating growth, partnerships and exits for innovation-led companies. 

He is a director of several technology companies, a graduate of Imperial College and City University, a Chartered Engineer and Physicist and is on the Committees of the IET’s Management of Innovation Technical Network and the IoP’s Business and Innovation Growth Group

Oluwatobi Ajayi, MSc, MIET, is a full stack developer at Severn Trent limited. Oluwatobi works on the end to end development of enterprise AI platforms within the business capital delivery AI and digital transformation team.

Dr. Terry Douglas Jayasuriya-Gomes is a Chartered Engineer (ECUK-MIET) with nearly four decades of experience across academia, industry, and government, distinguished by his commitment to engineering excellence, innovation, and lifelong learning.

He holds a PhD in Artificial Intelligence and Engineering Technology, along with postgraduate and undergraduate degrees in systems and electrical engineering from leading UK institutions.

As Founder and Principal Consultant of TDJ Consultancy Group, he leads initiatives in AI-driven analytics, engineering design, process safety (IEC 61511 compliance), sustainability, and industrial–academic collaboration.

His career includes senior leadership roles at Brunei Shell Petroleum, where he advanced HSSE frameworks, engineering training, and AI-enabled process optimisation, as well as Director of Enforcement at SHENA (Brunei’s safety regulator), where he shaped national safety policies aligned with Brunei Vision 2035.

Dr. Jayasuriya-Gomes currently serves as Chair of the IEEE SA Committee on the Digital Twin of the Earth (DTE). He contributes to global engineering standards through leadership roles with the IET and as a contributing author to ISA88 standards. He is actively engaged in academia as a mentor, board chairman, and part-time lecturer, alongside his support for community development initiatives. A prolific researcher with over 30 publications, his work focuses on AI applications in energy, safety, and digital transformation. His contributions have earned prestigious recognition, including a Global Shell HSSE Award and major research funding, reflecting his impact on innovation, safety, and operational excellence. His expertise spans AI and machine learning, process safety, engineering design, and regulatory policy, underpinning a career dedicated to advancing sustainable, intelligent, and resilient engineering systems.