Masahiro Nishida | Space Engineering | Excellence in Innovation

Prof. Masahiro Nishida | Space Engineering | Excellence in Innovation

Professor, Nagoya Institute of Technology, Japan.

Prof. Masahiro Nishida is a distinguished professor at the Nagoya Institute of Technology and a renowned researcher in the field of mechanical engineering. His expertise spans dynamic responses of solid structures and hypervelocity impact on advanced materials. With over 61 publications in English, Prof. Nishida is recognized for his significant contributions to material science, specifically in the shock compression of condensed matter. He currently serves as the General Manager of the Quality Innovation Techno-Center at the institute.

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Education 🎓

Prof. Masahiro Nishida holds a Bachelor of Engineering (1991) and a Master of Engineering (1993) from the Tokyo Institute of Technology, where he studied in the Department and Graduate School of Mechanical Engineering, respectively. He completed his Doctor of Engineering degree in 1996, with a thesis titled “Evaluation Method of Mechanical Properties for Material by Phase-Sensitive Acoustic Microscope,” under the supervision of Prof. H. Matsumoto. During his doctoral studies, he also gained international experience as a visiting researcher at Pennsylvania State University in 1995, working in the Acoustic Microscopy Lab. His research focuses on advanced material evaluation techniques, particularly in mechanical properties analysis through acoustic microscopy.

Experience 🛠️

Prof. Masahiro Nishida began his academic career as a Research Associate in the Department of Mechanical Science at Tokyo Institute of Technology from 1996 to 1997, before transitioning to the Nagoya Institute of Technology, where he served as a Research Associate in the Department of Mechanical Engineering from 1997 to 2001. He then became a Lecturer from 2001 to 2004 and an Associate Professor from 2004 to 2018 in the same department. Since 2018, he has held the position of Professor in the Department of Mechanical Engineering at Nagoya Institute of Technology. In 2022, he took on additional responsibilities as the General Manager of the Quality Innovation Techno-Center at the institute. Prof. Nishida also gained international experience as a visiting researcher at Luleå University of Technology, Sweden, in 2009.

Research Interests 🔬

Prof. Nishida’s research focuses on the dynamic properties of materials, particularly in hypervelocity impact and shock compression of various materials. His key areas of interest include:

Hypervelocity impacts on metal and plastic materials, with applications to space debris bumpers.

Dynamic strength of advanced materials, especially recycled aluminum alloys and additive manufacturing materials.

Dynamics of heterogeneous materials, studying the behavior of aggregated soft particles.
He integrates both experimental and computational approaches in his research.

Awards & Memberships 🏆

Japan Society of Mechanical Engineers (JSME)

Society of Materials Science, Japan (JSMS)

Japan Society for Aeronautical and Space Sciences (JSASS)

Japanese Society for Experimental Mechanics (JSEM)

Society for Experimental Mechanics (SEM)

Hypervelocity Impact Society (HVIS)

Publications Top Notes📚

Anand Pai, et al. “Computational studies on hypervelocity impact of spherical projectiles on whipple shield with hybrid Newtonian fluid-filled core,” Acta Astronautica, 2024, Cited by 2. Link

Slim Djebien, et al. “Strain rate and notch radius effects on evaluating the stress-strain relations using the stepwise modeling method,” Journal of Dynamic Behavior of Materials, 2024. Link

Daichi Kimura, et al. “Effects of Temperature on Crater Size and Ejecta Resulting from Ultra-high Molecular Weight Polyethylene Fiber Composites/Aluminum Alloy Plates,” Journal of Evolving Space Activities, 2023. Link

Ziyi Su, et al. “Evaluation of flow stress in nylon 66 via digital image correlation method and response surface method,” Journal of Mechanical Engineering Science, 2023. Link

Masahiro Nishida, et al. “Effects of Strain Rate on Stress-Strain Curves in 2024 Aluminum Alloy After Solution Heat Treatment,” Materials Transactions, 2022, Cited by  4. Link

 

 

 

 

Haowei Zhang | Engineering | Best Researcher Award

Dr. Haowei Zhang | Engineering | Best Researcher Award

Ph.D student, The University of Hong Kong, Hong Kong.

👨‍🔬 Haowei Zhang is a dynamic researcher specializing in structural health monitoring, concrete structure damage detection, and computer vision-based bridge Weight-In-Motion (WIM) systems. With a Ph.D. in progress at The University of Hong Kong, he has made significant contributions through cutting-edge research and impactful publications in top-tier journals. Haowei’s work spans deep learning, machine learning, and advanced imaging techniques for infrastructure health assessment, making him a standout researcher in civil engineering.

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Education 🎓

Dr. Haowei Zhang is a current Ph.D. student in Civil Engineering at The University of Hong Kong, under the supervision of Prof. Ray Kai Leung Su. His doctoral research builds on his expertise in bridge safety performance and vehicle non-contact weigh-in-motion (WIM) technology. He holds a Master’s degree in Civil Engineering from Southeast University, where he focused on the safety performance of bridges, supervised by Prof. Gang Wu and Prof. Kang Gao. Prior to that, he earned his Bachelor’s degree from Northeastern University in China, with a thesis on experimental building design supervised by Prof. Zhechao Wang. During his undergraduate studies, he also attended a summer training program at the University of Oxford, where he explored micromechanics and its applications in liquid metal 3D printing.

Experience 💼

Dr. Haowei Zhang is currently pursuing a Ph.D. in Civil Engineering at The University of Hong Kong, supervised by Prof. Ray Kai Leung Su. He holds a Master’s degree in Civil Engineering from Southeast University, where his research focused on vehicle non-contact weigh-in-motion (WIM) technology and the safety performance of bridges. Additionally, he earned his Bachelor’s degree from Northeastern University, specializing in experimental building design.

Professionally, Dr. Zhang serves as a Junior Researcher at Dongqu Intelligent Transportation Infrastructure Technology (2023-present), where he contributes to the development of computer vision models and equipment for transportation infrastructure. He has also led research projects on bridge monitoring, concrete structure damage detection, and deep learning algorithms for weight identification. During his master’s studies, he worked as a part-time college psychological counselor at Southeast University, providing psychological support and managing data files for graduate students.

His work uniquely combines civil engineering, intelligent transportation systems, and mental health advocacy.

Research Interests 🔬

Haowei Zhang’s research interests lie in structural health monitoring, computer vision-based WIM systems, deep learning, machine learning applications in civil engineering, and non-contact vehicle weight identification. His work focuses on developing innovative solutions for monitoring the integrity of concrete structures and enhancing safety through advanced image processing and data analysis.

Awards 🏆

International Exhibition of Inventions of Geneva – Silver Prize (2024)
Honor of Individual Academic Innovation – Southeast University (2023)
First-Class Academic Scholarship – Southeast University (2021)
Outstanding Undergraduate Student of Liaoning Province (2021)
National Scholarship (2020)

Publications Top Notes 📄

Automatic crack detection on concrete and asphalt surfaces using semantic segmentation network with hierarchical Transformer, Engineering Structures, 2023 Cited by: 45. link

Non-contact vehicle weight identification method based on explainable machine learning models and computer vision, Journal of Civil Structural Health Monitoring, 2023 Cited by: 20. link

Fully decouple convolutional network for damage detection of rebars in RC beams, Engineering Structures, 2023 Cited by: 25. link

A machine learning and game theory-based approach for predicting creep behavior of recycled aggregate concrete, Case Studies in Construction Materials, 2022 Cited by: 35. link