Role

Dr. Reza Barenji is a Principal Lecturer in the Engineering Department at Nottingham Trent University (NTU) and a member of the department’s senior leadership team. He serves as the Subject Manager for the postgraduate portfolio, contributing to the strategic development, quality enhancement, and effective delivery of postgraduate engineering programmes.

In this role, he supports curriculum design, programme development, and academic planning across the postgraduate portfolio, while also contributing to departmental leadership activities, postgraduate recruitment, and quality assurance processes. He serves as the departmental lead for Generative AI in education, supporting the responsible integration of AI technologies into teaching and learning practices. He also contributes to postgraduate open days and student engagement activities, and supports academic teams through line management and curriculum development activities.

In addition, Dr. Barenji acts as an External Examiner at Oxford Brookes University and serves as an academic advisor on quality assurance at Girne American University, Cyprus.

Teaching and Learning

Dr. Barenji is the module leader for the Level 6 optional module Fundamentals of Industry 4.0 and leads the postgraduate Individual Research and Industry Project module.

Research

Dr. Barenji’s research interests focus on the digitalisation of complex engineering systems, with an emphasis on modelling, simulation, and optimisation. His work explores the development and application of digital twin technologies to represent and analyse real-world industrial systems in real time. He is also interested in the integration of artificial intelligence methods for decision support, predictive analytics, and system optimisation, particularly within manufacturing, smart engineering, and Industry 4.0 contexts.

He is currently supervising five PhD researchers as Director of Studies or Co-Supervisor across advanced digitalisation and AI-driven engineering domains:

• Sina Khoshgoftar (DoS): Developing digital twin frameworks for anomaly detection and management in traffic infrastructure systems.
• Rajapakse ADS Arunasiri (DoS): Developing digital twin approaches for extending the lifespan and enabling second-life utilisation of used batteries.
• Molly Ogilvie (Co-Supervisor): Investigating humanoid applications in dynamic work systems with a focus on adaptive behaviour modelling and system interaction.
• Demet  Ozturk (Co-Supervisor): Developing multi-modal agentic AI systems for optimisation of energy distribution networks.
• Al hussein abu-jalala (Co-Supervisor): Developing intelligent smart charging systems using agentic AI for adaptive and efficient energy management.

Dr. Barenji has led and contributed to research projects with a total value of approximately £3 million as Principal Investigator (PI), Co-Investigator (Co-I), and academic advisor. His research outputs include more than 70 peer-reviewed journal publications with over 2,800 citations.

He has also contributed to major international projects, including a €2.2 million EU-funded project focused on sustainable artificial stone materials using recycled PET.

He is a member of the editorial boards of the Journal of Enterprise Information Management and Discover Robotics, and is regularly invited to deliver keynote presentations at international conferences.

Industry Consultancy and Engagement

Dr. Barenji actively engages with industry through consultancy and applied research, supporting organisations in digital transformation, automation strategy, and manufacturing optimisation. His work focuses on translating research outcomes into practical industrial applications, particularly in smart manufacturing, AI-enabled systems, and process optimisation.

He has established long-term collaborations with organisations including Mercedes-Benz, Beko, Karel, and Hidromek, contributing to automation, robotics, and manufacturing execution system projects. He has also supported facility localisation studies, including academic contributions to early-stage planning for Volkswagen’s manufacturing operations in Turkey.

To strengthen industry engagement, he initiated Industry 4.0 workshops that evolved from small-scale knowledge exchange events into large professional training programmes with up to 300 participants. These activities have supported knowledge transfer and industry–academia collaboration across multiple sectors.

In the pharmaceutical sector, he contributed to the development of a Cyber-Physical Process Analytical Technology (CPS-PAT) system to address production quality variability across distributed manufacturing sites, resulting in improved efficiency and reduced waste.

He has also supported digital transformation initiatives for SMEs through the development of cloud-based manufacturing platforms aimed at improving productivity and digital integration across industrial clusters.

He is an academic member of Hello Tomorrow, a global deep-tech innovation platform connecting researchers with industry and investors, and was endorsed as a “Global Talent” in smart manufacturing by the Royal Academy of Engineering in 2021. He also received the 2020 First-Class Research Award from TÜBİTAK.