Zhen Guo | Renewable Energy | Editorial Board Member

Published on by Natural Scientist Awards

Dr. Zhen Guo | Renewable Energy | Editorial Board Member

Dr. Zhen Guo | Wuhan University of Technology | China

Dr. Zhen Guo is an emerging researcher specializing in intelligent fault diagnosis, deep learning, anomaly detection, and engineering signal processing, with emphasis on developing reliable data-driven methods for modern industrial systems. His work addresses key challenges in rotating machinery, gearboxes, propellers, and wind turbines by integrating advanced machine learning models with domain-specific signal processing techniques to enhance diagnostic accuracy under real-world constraints. Dr. Guo’s research explores multi-scale wavelet decomposition, adaptive feature fusion, and high-dimensional sampling strategies to mitigate multi-level class imbalance and improve the robustness of condition-monitoring frameworks. He has introduced innovative unsupervised anomaly detection approaches using deep convolutional support generative adversarial networks, enabling effective detection in scenarios where labeled data are insufficient or costly. His contributions also include transfer-learning architectures with channel-attention residual networks and LLM-assisted fine-tuning to achieve few-shot fault recognition in complex systems such as autonomous underwater vehicle propellers. Additionally, he has advanced wavelet-random-forest methods for modeling high-dimensional imbalance samples and proposed unified pattern-fusion strategies for mining alarm data in large-scale industrial facilities using adaptive discretization and time-clustering mechanisms. Dr. Guo’s work published in leading journals such as Mechanical Systems and Signal Processing, Scientific Reports, Ocean Engineering, Measurement, and Measurement Science and Technology demonstrates his commitment to bridging the gap between theoretical advances and practical reliability engineering. Supported by competitive research funding, he continues to design predictive frameworks that improve equipment health assessment, Remaining Useful Life estimation, and maintenance decision-making across industrial environments, contributing significantly to the advancement of intelligent diagnostic technologies.

Profile: Scopus | ORCID

Featured Publications

Guo, Z. (2025). Multi-scale wavelet decomposition and feature fusion for rotating machinery fault diagnosis under multi-level class imbalance. Mechanical Systems and Signal Processing.

Guo, Z. (2025). Unsupervised anomaly detection for gearboxes based on the deep convolutional support generative adversarial network. Scientific Reports, (Published July 1, 2025).

Guo, Z. (2025). Channel attention residual transfer learning with LLM fine-tuning for few-shot fault diagnosis in autonomous underwater vehicle propellers. Ocean Engineering.

Guo, Z. (2025). Fault diagnosis of rotating machinery with high-dimensional imbalance samples based on wavelet random forest. Measurement.

Guo, Z. (2025). Alarm data mining in complex industrial facilities using adaptive discretization based on time clustering and unified pattern fusion mining. Measurement Science and Technology, (Published January 31, 2025).

Hongwei Du | Green Technology | Best Researcher Award

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Dr. Hongwei Du | Green Technology | Best Researcher Award

Dr. Hongwei Du | Inner Mongolia University of Science and Technology | China

Dr. Hongwei Du is a dedicated researcher in materials science and metallurgical engineering with a strong academic background from Henan Polytechnic University and Inner Mongolia University of Science and Technology. He has gained valuable experience through internships in metallurgy, manufacturing, and heat treatment, as well as participation in research on rare earth catalyst development under the guidance of a renowned scholar. Recognized with multiple scholarships and awards, he has also excelled in academic competitions. Alongside technical expertise, he is proficient in CAD drafting and English communication, demonstrating strong organizational skills, adaptability, and a commitment to advancing laboratory analysis and research.

Publication Profile

Orcid

Academic Background

Dr. Hongwei Du has built a strong foundation in materials science and metallurgical engineering through his academic journey at Henan Polytechnic University and Inner Mongolia University of Science and Technology. His studies covered metallurgy, heat treatment principles, materials analysis, testing technology, and physical properties of materials. He gained practical skills through internships in metallurgy, manufacturing, and heat treatment processes, further supported by hands-on research in rare earth catalyst development under the guidance of a distinguished scholar. His academic achievements, scholarships, and competition awards highlight his dedication, while his technical skills and adaptability reflect his potential for impactful research.

Professional Experience

Dr. Hongwei Du has cultivated significant professional experience through a combination of academic research, internships, and extracurricular engagements. He worked with metallurgical companies where he gained practical exposure to manufacturing, forging, and heat treatment processes, enriching his technical expertise in materials science. His research on rare earth catalyst development under the mentorship of a distinguished scholar strengthened his analytical and experimental skills. Beyond technical pursuits, he contributed actively to student organizations, competitions, and volunteer initiatives, showcasing leadership and teamwork. His professional journey reflects a balance of academic excellence, practical knowledge, and strong personal commitment to advancing materials research.

Awards and Honors

Dr. Hongwei Du has been recognized with several awards and honors that reflect his dedication to academic and professional excellence. He earned multiple scholarships for his consistent performance and was honored as an Outstanding Communist Youth League Member, highlighting both his academic and leadership qualities. His achievements in competitions, including top placements in mathematical modeling and metallography, demonstrate his problem-solving skills and innovative thinking. In addition, his certification as a senior CAD draftsman and proficiency in English communication showcase his technical and professional competencies. These accomplishments collectively illustrate his commitment to continuous growth and scholarly distinction.

Research Focus

Dr. Hongwei Du’s research focuses on advancing materials science and metallurgical engineering through both theoretical and applied approaches. His academic training has provided a deep understanding of metallurgy, heat treatment processes, materials testing, and physical properties of metals. Under the mentorship of a distinguished scholar, he contributed to the development and performance testing of rare earth catalysts, reflecting his interest in innovative materials research. He aims to integrate laboratory analysis with industrial applications to create solutions that improve efficiency and sustainability. His research focus demonstrates a commitment to bridging academic knowledge with practical advancements in material technologies.

Publication Top Notes

Phase Transformation and Si/Al Leaching Behavior of High-Silica–Alumina Coal Gangue Activated by Sodium-Based Additives
Year: 2025

Conclusion

Dr. Hongwei Du possesses a strong foundation in materials science and metallurgical engineering, combining excellent academic achievements with practical research and internship experience. His work on rare earth catalyst development under a distinguished scholar demonstrates significant research potential, while his consistent performance in scholarships and competitions reflects intellectual capability and innovation. With strong motivation, leadership, and technical skills, he is well-positioned to advance scholarly publications and collaborative projects, making him a highly deserving candidate for the Best Researcher Award.