Guoqiang Li | Engineering | Innovative Research Award

Published on by China Scientist

Dr. Guoqiang Li | Engineering | Innovative Research Award 

Dr. Guoqiang Li is a Lecturer and Master’s Supervisor at the School of Marine Engineering. He received his Ph.D. in Mechanical Engineering from Huazhong University of Science and Technology, following a Bachelor’s degree from Dalian Maritime University. His research focuses on the reliability analysis, anomaly detection, and intelligent fault diagnosis of offshore electromechanical equipment. He has led several national and provincial research projects and has expertise in industrial big data, AI algorithms, and smart operation platforms. Dr. Li is also a recipient of multiple science and teaching awards and has authored officially published textbooks.

Dr. Guoqiang Li | Jimei University | China

Profile

SCOPUS ID

Education

  • Dr. Guoqiang Li holds a Bachelor’s degree from Dalian Maritime University and earned both his Master’s and Doctoral degrees in Mechanical Engineering from Huazhong University of Science and Technology. His advanced training laid a strong foundation in engineering principles, particularly in the context of mechanical reliability and intelligent systems applied to offshore environments.

Experience

  • Dr. Li is currently serving as a Lecturer and Master’s Supervisor at the School of Marine Engineering. Since joining academia, he has been involved in teaching, mentoring graduate students, and spearheading innovative research. His contributions extend beyond his university role, having participated in national and provincial-level research initiatives and collaborated with major institutions such as Wuhan University of Technology. He has played both principal and collaborative roles in a variety of R&D projects focusing on marine power systems and intelligent control technologies.

Awards and Recognition

  • Dr. Li has received multiple accolades throughout his academic and research journey. These include prestigious Science and Technology Awards, recognition for Teaching Achievements, and the authorship of officially published textbooks. These honors underscore his excellence in both academic instruction and scientific innovation.

Skills and Certifications

  • His core competencies lie in reliability analysis, intelligent fault diagnosis, and predictive maintenance of offshore electromechanical systems. He is proficient in applying industrial big data analytics, artificial intelligence algorithms, and edge-cloud collaborative computing. Dr. Li is also skilled in the development of intelligent operation platforms and industrial internet systems that support real-time monitoring, diagnostics, and equipment self-regulation.

Research Focus

  • Dr. Li’s research centers on the intelligent monitoring and fault management of offshore equipment. He is especially interested in anomaly detection, condition assessment, and data-driven fault prediction. His work integrates cutting-edge technologies such as generative AI, deep reinforcement learning, and multi-source data fusion to enhance the autonomy and intelligence of marine mechanical systems. His goal is to develop systems capable of zero-sample learning, predictive maintenance, and self-healing control in complex maritime environments.

Conclusion

  • Dr. Guoqiang Li is a forward-thinking researcher and educator whose work lies at the intersection of artificial intelligence and marine engineering. With a firm academic grounding and an expanding portfolio of impactful projects, he continues to contribute to the advancement of intelligent fault diagnostics and system automation in offshore industries. His research and innovations are well-positioned to address the growing demand for smart, reliable, and efficient marine technologies.

Publications

  • Zero-sample fault diagnosis of rolling bearings via fault spectrum knowledge and autonomous contrastive learning
    Authors: Guoqiang Li, Meirong Wei, Defeng Wu, Yiwei Cheng, Jun Wu
    Journal: Expert Systems with Applications

  • Wavelet knowledge-driven transformer for intelligent machinery fault detection with zero-fault samples
    Authors: Guoqiang Li, Meirong Wei, Haidong Shao, Pengfei Liang, Chaoqun Duan
    Journal: IEEE Sensors Journal

  • Zero-fault sample wavelet knowledge-driven industrial robot fault detection
    Authors: Guoqiang Li, Meirong Wei, Defeng Wu, et al.
    Journal: Journal of Instrumentation

  • Deep reinforcement learning-based online domain adaptation method for fault diagnosis of rotating machinery
    Authors: Guoqiang Li, Jun Wu, Chao Deng, Xuebing Xu, Xinyu Shao
    Journal: IEEE/ASME Transactions on Mechatronics

  • Convolutional neural network-based Bayesian Gaussian mixture for intelligent fault diagnosis of rotating machinery
    Authors: Guoqiang Li, Jun Wu, Chao Deng, Zuoyi Chen, Xinyu Shao
    Journal: IEEE Transactions on Instrumentation and Measurement

Xuanze Wang | Engineering | Best Researcher Award

Published on by China Scientist

Prof. Xuanze Wang | Engineering | Best Researcher Award

Professor Xuanze Wang is a Professor and Master’s Supervisor at the School of Mechanical Engineering, Hubei University of Technology. He earned his Doctor of Engineering in Mechanical Manufacturing and Automation from Huazhong University of Science and Technology in 2005. A recipient of the Ministry of Education’s New Century Excellent Talent award, he specializes in precision measurement, embedded systems and analog circuit design, and digital signal processing and automatic control. He has led two National Natural Science Foundation of China projects, participated in over ten national and provincial research initiatives, and published more than 50 peer-reviewed papers.

Prof. Xuanze Wang | Hubei Institute of Technology | China

Profile

🎓Education

  • Professor Xuanze Wang earned his Doctor of Engineering degree in Mechanical Manufacturing and Automation from Huazhong University of Science and Technology in 2005, laying a solid academic foundation in the field of mechanical engineering.

👨‍🏫 Experience

  • He currently serves as a Professor and Master’s Supervisor at the School of Mechanical Engineering, Hubei University of Technology. From July 2010 to July 2011, he undertook a one-year academic visit at the University of Huddersfield in the United Kingdom, expanding his international academic collaborations and exposure.

🤝 Awards

  • Professor Wang was selected as a New Century Excellent Talent by the Ministry of Education, recognizing his outstanding academic potential and contributions to engineering education and research.

💡Skills and Certifications

  • He possesses extensive expertise in precision measurement methodologies, embedded systems and analog processing circuit design, as well as digital signal processing and automatic control methods, integrating both theoretical knowledge and practical engineering skills.

🔬 Research Focus

  • His research primarily focuses on precision measurement techniques, embedded systems development, analog circuit design, and digital signal processing with applications in automatic control. He has presided over two projects funded by the National Natural Science Foundation of China and participated in more than ten national and provincial-level research initiatives. His scholarly output includes over 50 peer-reviewed papers, contributing valuable knowledge to the engineering research community.

🌎Conclusion

  • Xuanze Wang is highly suitable for the Research for Best Researcher Award. His combination of prolific research output, leadership in funded projects, international collaboration, and recognition by the Ministry of Education align well with the award’s criteria for research excellence, innovation, and impact. His contributions not only advance engineering science but also provide practical solutions across industries, making him a compelling candidate for this honor.

📖Publications

  • Robust vertical scanning interferometry at a long coherence length
    Authors: Zhao Hang, Xie Yijun, Zhu Renlong, Liu Shiyuan, Zhu Jinlong
    Journal: Optics and Lasers in Engineering, 2025

  • 3D reconstruction of a highly reflective surface based on multi-view fusion and point cloud fitting with a structured light field
    Authors: Feng Wei, Liu Qianqian, Wang Henghui, Xu Jiangtao, Wang Xuanze
    Journal: Applied Optics, 2025

  • A Micro-Current Measurement Method Based on Bidirectional Search to Eliminate Operational Amplifier Offset Voltage
    Authors: Wang Xuanze, Li Yuchen, Yang Zhenyu, Zhai Zhongsheng
    Journal: Chinese Journal of Sensors and Actuators, 2025

  • Moving sine average-based surface recovery method with enhanced noise resistance in white light interferometry
    Authors: Dong Zhengqiong, Zhu Renlong, Zhao Hang, Zhu Jinlong, Nie Lei
    Journal: Optical Engineering, 2025

  • Robust function guided color encoded single fringe pattern and unwrapping method
    Authors: Liu Da, Yu Xiatian, Li Xuelian, Zou Jianchao, Zhang Yuqing
    Journal: Optics Communications, 2025