Interview with Dr. Yang Yu—Winner of the Materials 2024 Best Paper Award
All papers published in 2022 in Materials (ISSN: 1996-1944) were considered for this award. After a thorough evaluation of the originality and significance of the papers, citations, and downloads, the winner was selected:
“Back-Propagation Neural Network Optimized by K-Fold Cross-Validation for Prediction of Torsional Strength of Reinforced Concrete Beam”
by Zhaoqiu Lyu, Yang Yu, Bijan Samali, Maria Rashidi, Masoud Mohammadi, Thuc N. Nguyen and Andy Nguyen
Materials 2022, 15(4), 1477; https://doi.org/10.3390/ma15041477
Available online: https://www.mdpi.com/1996-1944/15/4/1477
The winners will receive CHF 300 and a chance to publish a paper free of charge after peer review in Materials in 2024.
Dr. Yang Yu is currently a Research Fellow at the Centre for Infrastructure Engineering and Safety, School of Civil and Environmental Engineering, University of New South Wales, Australia. His research focuses on (1) sustainable construction materials, (2) digital transformation of civil infrastructure, and (3) smart materials for resilient structures. He has authored or co-authored over 120 journal articles that are indexed in the Web of Science, including eight ESI Highly Cited Papers and six ESI Hot Papers. Dr. Yu is serving as an Associate Editor for the journal Frontiers in Materials. Additionally, he has been included consecutively in the World's Top 2% Scientists list since 2022, published by Elsevier and developed by scientists from Stanford University, USA.
The following is an interview with Dr. Yang Yu:
1. Could you please briefly introduce the main content of the winning paper?
This paper introduces a novel approach for predicting the torsional strength of reinforced concrete (RC) beams by combining the advantages of the genetic algorithm (GA) and neural networks, specifically using a BP neural network optimized with K-fold cross-validation. This method addresses the challenge of limited sample size in conventional prediction methods by leveraging machine learning to enhance prediction accuracy. The study employs various metrics such as RMSE, MAE, MSE, MAPE, and R2 to evaluate the performance of the proposed model. A comparative analysis with existing empirical formulas from design codes demonstrates the enhanced prediction capability of the BP neural network after optimization with K-fold cross-validation and the GA, suggesting its potential for practical application in the optimal design of RC beams.
2. What is your current research and why did you choose this research field?
My current research focuses on sustainable construction materials, an area I chose due to its critical importance in addressing environmental challenges and promoting sustainable development within the construction industry. As global awareness of environmental issues grows, the need for sustainable practices in all sectors, including construction, becomes increasingly paramount. This field offers the opportunity to innovate and develop materials that not only reduce the environmental footprint of construction projects but also enhance efficiency, durability, and cost-effectiveness. By exploring alternative materials, recycling waste products, and improving existing material sustainability, my research aims to contribute to building practices that are more in harmony with our environment. The potential for a significant positive impact on both the industry and the planet is what drives my passion and commitment to this area of study.
3. What appealed to you about our journal that made you want to submit your paper? What benefits do you think authors can gain when publishing their articles in Materials?
Publishing in Materials not only offers authors a broad and interdisciplinary platform to showcase their work but also significantly boosts the research’s visibility and impact through its inclusion in prestigious databases, such as Web of Science and Scopus. This can lead to higher citation rates, amplifying the influence of the research in the field. The journal's commitment to open access is a pivotal advantage, providing unrestricted global access to the research, which enhances its dissemination and engagement potential across the scientific community and beyond. Furthermore, the rigorous peer review process ensures the credibility and quality of the published work, affirming its contribution to the field of materials science. The journal's efficient publication timeline ensures that cutting-edge research is shared promptly, keeping pace with the rapid advancement in materials science. Moreover, exposure to a diverse audience fosters interdisciplinary collaboration and innovation, potentially leading to new research avenues and applications.
4. We are an open access journal. How do you think open access impacts the authors?
Open access significantly benefits authors by enhancing the visibility and accessibility of their research, ensuring wider dissemination across disciplines and beyond the academic community, which can lead to increased citations and a broader impact. It facilitates compliance with funding mandates that require open dissemination of research findings, fostering interdisciplinary collaborations and public engagement. While open access shifts publication costs to authors in the form of article processing charges (APCs), institutions and funders often cover these expenses, recognizing the value of open and accessible research. Thus, open access presents a compelling model for authors looking to maximize the reach and influence of their work in the scientific community and the broader public sphere.