Dan Uchimura | Engineering | Best Researcher Award

Published on by Award and Honors

Mr. Dan Uchimura | Engineering | Best Researcher Award

Mr. Dan Uchimura|Kajima Corporation | Japan

Dan Uchimura is an emerging professional in nuclear power plant structural design, currently serving as a designer in the Kajima Corporation Nuclear Power Department. With a Master’s Degree in Architecture from Waseda University, he has swiftly transitioned from academia to industry, applying his expertise in structural systems, safety analysis, and computational modeling. During his graduate studies in Tokyo, he focused on enhancing the resilience and sustainability of energy facilities, developing technical skills in MATLAB, Python, and Excel to simulate structural integrity under extreme conditions. Since joining Kajima, Dan has contributed to the planning and design of nuclear power facilities while spearheading research on integrating non-destructive inspection techniques—especially infrared thermography—into plant systems to detect structural anomalies without operational interruptions. Known for his analytical thinking, precision, and interdisciplinary approach, he collaborates with engineers, material scientists, and safety analysts to deliver reliable, innovative design solutions aligned with stringent safety regulations. His research interests center on advancing inspection technologies, modeling structural behavior under thermal and seismic loads, and exploring AI-driven predictive maintenance systems to enhance safety and efficiency in nuclear infrastructure. Though early in his career, Dan has already earned recognition for his innovative contributions, including commendations for his thesis on resilient energy infrastructure and praise from senior engineers for merging theoretical concepts with practical design solutions.

Profile : ORCID

Featured Publication 

Uchimura, D. (2024). Application of infrared thermography for non-destructive structural inspection in nuclear power facilities. Journal of Structural Engineering and Technology.

Uchimura, D. (2023). Resilient architectural design framework for nuclear power plants. International Journal of Sustainable Energy Infrastructure.

Uchimura, D. (2023). Computational modeling of seismic loads in nuclear plant structures. Journal of Advanced Structural Engineering.

 

Shangshang Wu | Engineering | Best Researcher Award

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Dr. Shangshang Wu | Engineering | Best Researcher Award

Tianjin university | China

Wu Shangshang is a mechanical engineer pursuing her Ph.D. at the School of Mechanical Engineering, Tianjin University in China, where she also completed her B.S. and M.S. in Mechanical Engineering. Her research focuses on underwater gliders, emphasizing hydrodynamic identification, motion behavior analysis, and front-end data processing for acoustic communication. Since her master’s studies, she has worked as a graduate researcher, contributing to both experimental sea trials and theoretical modeling, and has published journal articles and conference papers in marine robotics, acoustics, and signal processing. Wu’s doctoral work advances model-based and data-driven methods to improve hydrodynamic prediction and control under uncertain underwater conditions, supporting the development of reliable seabed vehicles and underwater communication systems. She collaborates closely with colleagues at Tianjin University, including researchers such as Guangwei Lv and Shaoqiong Yang, and her early contributions are gaining citations. Her interests also include neural network–based hybrid modeling, online estimation, and mitigating the effects of environmental factors like sea currents and noise on underwater navigation and sensor performance. While no specific awards are publicly documented, Wu shows strong potential in combining experimental insights with computational techniques to enhance the design, control, and stability of underwater gliders.

Profile : Scopus| ORCID  

Featured Publications

AuthorLastName, A. A., & AuthorLastName, B. B. Model and data-driven hydrodynamic identification and prediction for underwater gliders. Physics of Fluids.

AuthorLastName, A. A., & AuthorLastName, B. B. An enhanced variational mode decomposition method for processing hydrodynamic data of underwater gliders. Measurement.

AuthorLastName, A. A., & AuthorLastName, B. B. Multi-body modelling and analysis of the motion platform for underwater acoustic dynamic communication. Applied Mathematical Modelling.