Kejin Wang | Cement and concrete materials | Best Researcher Award

Prof. Kejin Wang | Cement and concrete materials | Best Researcher Award

Wilson Professor of Engineering | Iowa State University | United States

Prof. Kejin Wang’s research profile reflects extensive leadership across more than 70 funded projects advancing cutting-edge civil engineering materials, particularly cementitious and concrete technologies, with a strong emphasis on performance, durability, and sustainability. Her work spans cement and concrete chemistry, microstructure evolution, hydration processes, and rheological behavior, contributing to improved understanding of workability, thixotropy, and long-term performance in diverse environmental conditions. She has conducted major investigations into concrete durability, focusing on freezing–thawing resistance, alkali–silica reaction mitigation, and reinforcement corrosion control, while pioneering advancements in sustainable concrete through alternative cements, biochar integration, solid-waste incorporation, carbonation curing, and carbon-sequestration pathways. Her expertise extends to high-performance and advanced concretes, including ultra-high-performance systems, self-healing materials, phase-change materials, and pervious concrete technologies. Additional contributions include innovative work in 3D printing concrete, particularly mix design and performance characterization, as well as significant studies on nanomaterial applications such as nano-silica, nano-clay, and nano-limestone for microstructure refinement and property enhancement. Her ongoing research portfolio features projects on UHPC-based 3D printing, LC3 concrete systems, multi-waste concrete formulations, biochar cement development, performance of concrete overlays, hydration heat prediction in mass concrete, internal curing of high-performance mixes, and vacuum mixing effects in UHPC. She has published more than 240 peer-reviewed journal papers, edited seven books and conference proceedings, guided 52 graduate students and 26 post-doctoral or visiting scholars, and delivered invited lectures globally. Her service includes editorial leadership for leading journals, participation on numerous international technical committees, and involvement in proposal review panels, dissertation evaluations, and major engineering events. Collectively, her research experience, project leadership, and technical expertise demonstrate a comprehensive and sustained contribution to the advancement of innovative, durable, and sustainable concrete technologies.

Profile: Scopus | Google Scholar
Publications:

Wang, K., Jansen, D. C., Shah, S. P., & Karr, A. F. (1997). Permeability study of cracked concrete. Cement and Concrete Research, 27(3), 381–393.

Zhang, P., Zheng, Y., Wang, K., & Zhang, J. (2018). A review on properties of fresh and hardened geopolymer mortar. Composites Part B: Engineering, 152, 79–95.

Wang, X., Li, W., Luo, Z., Wang, K., & Shah, S. P. (2022). A critical review on phase change materials (PCM) for sustainable and energy-efficient building: Design, characteristic, performance and application. Energy and Buildings, 260, 111923.

Schaefer, V. R., & Wang, K. (2006). Mix design development for pervious concrete in cold weather climates. Iowa Department of Transportation, Highway Division.

Hou, P., Kawashima, S., Wang, K., Corr, D. J., Qian, J., & Shah, S. P. (2013). Effects of colloidal nanosilica on rheological and mechanical properties of fly ash–cement mortar. Cement and Concrete Composites, 35(1), 12–22.

Adrien Gallet – Structural Engineering – Best Researcher Award

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
  • Zhuang, B., Gallet, A., & Smyl, D. (2025). Inverse structural design with generative and probabilistic autoencoders and diffusion models. Engineering Applications of Artificial Intelligence.

  • 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.

  • Gallet, A., Liew, A., Hajirasouliha, I., & Smyl, D. (2024). Influence zones of continuous beam systems. Structures.

  • Gallet, A., Smyl, D. (2024). IZ kmax: Influence zone results and design datasets. Dataset.

  • Gallet, A., Liew, A., Hajirasouliha, I., & Smyl, D. (2024). Machine learning for structural design models of continuous beam systems via influence zones. Inverse Problems.