Rate My Professor Mey Goh

Professor Mey Goh is Professor of Transdisciplinary Design Engineering at Loughborough University’s School of Mechanical, Electrical and Manufacturing Engineering, a position she has held since joining the institution in 2010. She earned a BEng (Hons) in Mechanical Engineering from Universiti Tenaga Nasional, Malaysia, and a PhD in Engineering Design from the University of Bristol, supported by a UK Overseas Research Students Award. Following her doctorate in 2005, she contributed to the University of Bath’s Innovative Design Manufacturing Research Centre as part of the EPSRC-funded Grand Challenge IITKM project, investigating through-life knowledge and information management and uncertainties in product-service systems costing.

Goh’s research pioneers transdisciplinary approaches to inclusive and sustainable industrial systems in Industry 5.0, focusing on human-centred design engineering at the nexus of people, technology, and organisational change in manufacturing. Her interests encompass human factors and behaviour, AI integration, digital twins, augmented reality, machine learning, and informatics for intelligent automation and servitisation. As Associate Director of the Intelligent Automation Centre and leader of Loughborough’s role in the EPSRC Made Smarter Innovation: Centre for People-Led Digitalisation (2021-2026), she has secured over £10 million in funding and supervised 15 PhD students. She has directed dual PhD programmes with PUCPR (Brazil) and NUAA (China), served as Visiting Professor for Rolls-Royce Submarines (2018-2022), and acts as International Special Envoy for South-East Asia. A Fellow of the Higher Education Academy, she is Associate Editor for the Journal of Integrated Design and Process Science, Board Member of the International Society for Transdisciplinary Engineering, and serves on COMEH committees. Her work has garnered 1,959 citations (Google Scholar), with notable publications including Palmer et al. (2026) “A human-centric framework for enhancing usability in a vineyard digital twin system” in Journal of Industrial Information Integration; Zareiee et al. (2026) in Computers and Electronics in Agriculture; and Goh (2020) “A variability taxonomy to support automation decision-making in manufacturing operations” in Production Planning & Control.