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Professor Lee Margetts holds the UKAEA Chair of Digital Engineering for Fusion Energy in the Department of Mechanical and Aerospace Engineering within the School of Engineering at the University of Manchester. He earned a Bachelor of Science in Geology from the University of Durham in 1994, a Master of Science in Geotechnical Engineering from the University of Manchester in 1998, a Doctor of Philosophy in Civil Engineering from the same institution in 2002, and a Master of Business Administration in International Engineering Business Management from Alliance Manchester Business School in 2011. After an early career in highways, transportation, and materials management, Margetts pursued postgraduate studies in geotechnical and civil engineering, subsequently transitioning to high-performance computing and engineering simulation. He serves as Director of the Fusion Engineering Centre for Doctoral Training and led the University of Manchester's Mechanical Engineering programmes from 2020 to 2026, achieving accreditation from the Institution of Mechanical Engineers and doubling overseas applications. Margetts initiated the open-source software ParaFEM for parallel finite element analysis and is a co-author of the textbook 'Programming the Finite Element Method' published by Wiley in 2016, which is also available in Chinese translation.
His research focuses on fusion engineering, digital engineering, high-performance computing, finite element methods, and computational methods in engineering, contributing to UN Sustainable Development Goals including quality education, affordable and clean energy, and industry innovation. Key publications include 'Surrogate model development using simulation data to predict weld residual stress: A case study based on the NeT-TG1 benchmark' (Miao et al., 2023, cited 24 times), 'Recent advances on microstructural characterization and modeling of nuclear graphite' (Arregui-Mena et al., 2021), 'Development of fusion reactor digital twins in the Metaverse' (Margetts et al., 2022), and recent works such as 'Calibration of a novel self adaptive dynamic heat source model using an autoencoder neural network' (Miao et al., 2026) and 'How transparent is water? Addressing ethical concerns in AI surrogate development for nearshore wave modelling' (Stella et al., 2026). Margetts has received the Best Paper Prize for Most Innovative Use of Simulation Technology in 2019, the CIUK Best Poster Prize in 2024 (shared), and the Teaching Excellence Award in 2021. He is an academic expert member of NAFEMS Ltd since 2019, has served as visiting faculty at Oak Ridge National Laboratory, and supports student initiatives like the MancheSTAR Fusion Society through collaborative engineering education.
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