Mehran Akhavan | Tall building | Best Researcher Award

Posted on by Civil Engineering Awards

Dr. Mehran Akhavan | Tall building | Best Researcher Award

Islamic Azad University | Iran

Dr. Mehran Akhavan Salmassi is a dedicated structural engineering researcher whose work focuses on advancing the safety, resilience, and performance of modern infrastructure systems. Holding a Ph.D. in Structural Engineering from the Islamic Azad University, Semnan Branch, he has developed a strong academic and research profile grounded in innovation, analytical rigor, and global engagement. His core areas of expertise include tall building engineering, structural control, and the development of high-performance structural systems capable of withstanding dynamic loads and extreme environmental conditions. Over the years, Dr. Salmassi has contributed significantly to the field through 18 peer-reviewed publications, reflecting both theoretical advancements and practical engineering solutions. His research also includes three recognized novelties, demonstrating his commitment to pioneering new methods and expanding current engineering knowledge. Dr. Salmassi actively contributes to the scientific community as a reviewer for three international journals, supporting the peer-review process and ensuring high-quality scholarly dissemination. His reputation as a knowledgeable and engaging scholar has earned him invitations as a speaker and distinguished speaker in more than 20 international conferences, where he has presented research findings, shared technical insights, and collaborated with experts across the globe. Through his growing academic footprint, he continues to foster meaningful collaborations that bridge research, industry practice, and societal needs. His work emphasizes the importance of innovation in structural engineering, particularly in the design of safe and sustainable tall buildings for rapidly developing urban environments. Driven by a passion for scientific excellence and public safety, Dr. Salmassi aims to contribute solutions that not only advance engineering practice but also inspire emerging researchers in the field.

Profile: Google Scholar
Publications

Akhavan Salmassi, M., Kheyroddin, A., & Hemmati, A. (2020). Seismic behavior of end walls in RC tall buildings with torsional irregularity. Magazine of Civil Engineering, 97(07).

Salmassi, M. A., Kheyroddin, A., & Hemmati, A. (2024). Enhancement of the performance of two tall buildings with end shear walls using nonlinear time history analysis: A case study. Iranian Journal of Science and Technology, Transactions of Civil Engineering.

Akhavan Salmassi, M., Kheyroddin, A., & Hemmati, A. (2023). Evaluation of reinforced concrete tall buildings with end shear walls subjected to sequences far from the fault. Scientia Iranica.

Kheyroddin, A., & Akhavan Salmassi, M. (2018). Effect of end walls in tall buildings with square plan and flexural concrete frames under earthquake. In 7th National and 3rd International Conference on Modern Materials and Structural Systems.

Akhavan Salmassi, M., Kheyroddin, A., & Hemmati, A. (2021). Seismic behavior of tall buildings with end shear walls and opening. Journal of Seismology and Earthquake Engineering, 23(2), 55–70.

Akhavan Salmassi, M., Gerami, M., & Heidari Tafreshi, A. (2019). Evaluation of flexible steel frame structures with post-tensioned cables to sequences far from fault. Journal of Structural and Construction Engineering, 6(Special Issue 3), 221–234.

Adrien Gallet – Structural Engineering – Best Researcher Award

Posted on by Civil Engineering Awards

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.