Dr. Adrien Gallet - Structural Engineering - Best Researcher Award
Computational Structural Engineering | Unipart Construction Technologies | United Kingdom
Adrien Gallet is a trilingual doctoral researcher in structural engineering with strong expertise in parametric modelling, Python programming, and structural design, currently pursuing a PhD at the University of Sheffield. Research focuses on machine-learned structural design models from the inverse problem perspective, producing multiple journal articles and data repository contributions. Professional experience spans academia and industry, including doctoral research and teaching roles at Sheffield, a design engineering placement at AKT II in London contributing to Google’s KGX1 office project, consulting work at BE Design Partnership on warehouse projects, and contracting engineering internship at Max Boegl. Research achievements involve the development of physics-informed neural network training pipelines, Grasshopper support scripts, and optimisation programs in Python and MATLAB, reflecting a strong integration of engineering and computational methods. Recognition includes prestigious awards such as the Outstanding Teaching Delivery Award, IStructE Young Researcher Conference Poster Award, Royal Academy of Engineering Scholarship, and multiple academic prizes from the University of Sheffield, demonstrating consistent academic excellence and leadership potential. Extracurricular activities highlight involvement in orienteering, long-distance running, and fencing, alongside leadership in founding the USIS Trading Division, encouraging financial market exposure for students. Technical proficiency covers advanced software tools like Rhino/Grasshopper, Karamba3D, Robot, Peregrine, and AutoCAD, combined with coding expertise in Python and MATLAB. Fluent in English, German, and French, Adrien demonstrates strong international and collaborative potential. A balance between research, teaching, engineering practice, and extracurricular engagement reflects adaptability, innovation, and leadership in both academic and professional settings, positioning Adrien as a highly capable researcher whose work advances the integration of computational intelligence with structural engineering, while maintaining strong interdisciplinary and practical contributions to the field.
Profile: Scopus | ORCID
Publications
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Zhuang, B., Gallet, A., & Smyl, D. (2025). Inverse structural design with generative and probabilistic autoencoders and diffusion models. Engineering Applications of Artificial Intelligence.
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Smyl, D., Zhuang, B., Rigby, S., Bruun, E., Jones, B., Kastner, P., Tien, I., & Gallet, A. (2025). OpenPyStruct: Open-source toolkit for machine learning-driven structural optimization. Engineering Structures.
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Gallet, A., Liew, A., Hajirasouliha, I., & Smyl, D. (2024). Influence zones of continuous beam systems. Structures.
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Gallet, A., Smyl, D. (2024). IZ kmax: Influence zone results and design datasets. Dataset.
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Gallet, A., Liew, A., Hajirasouliha, I., & Smyl, D. (2024). Machine learning for structural design models of continuous beam systems via influence zones. Inverse Problems.