Zhaochun Li | Intelligent Material Systems And Control | Best Researcher Award

Prof. Zhaochun Li | Intelligent Material Systems And Control | Best Researcher Award

Nanjing Forestry University | China

Dr. Li is a distinguished professor in the College of Mechanical and Electronic Engineering at Nanjing Forestry University, where she has built a strong reputation for her pioneering work in intelligent material systems and advanced control techniques. Her academic journey and professional achievements reflect a deep commitment to innovation in engineering research, particularly in areas that address critical challenges in mechanical performance and structural reliability. With a primary focus on intelligent material systems, Dr. Li has explored how these innovative materials can be effectively integrated into modern engineering applications to enhance efficiency and adaptability. A major part of her research is dedicated to passive and active vibration control, an area that plays a crucial role in ensuring stability, safety, and precision in a wide range of engineering systems. By advancing methods to mitigate vibrations, her work contributes to improving structural durability and performance in both industrial and technological contexts. Over the course of her career, Dr. Li has authored more than 60 peer-reviewed journal articles, providing valuable insights and shaping discourse within her field. Her scholarly contributions not only strengthen academic understanding but also open pathways for practical applications, positioning her as a respected leader and innovator in engineering research.

Profile: Orcid

Featured Publication

Hou, M., Xu, X., Ouyang, Q., & Li, Z. (2025, September 30). Research on model predictive control of magnetorheological impact buffer system considering driver modeling. Engineering Research Express.

Zheng, Z., Zhan, J., Li, Z., Wang, Y., Xu, C., & Wang, X. (2025, September 15). Data-driven twisted string actuation for lightweight and compliant anthropomorphic dexterous hands. Biomimetics.

Zheng, J., Xu, C., Li, Z., Gu, C., Li, X., Li, Z., Li, Y., Lou, G., & Chen, Y. (2024). Growing bimetallic CoNi-MOF derivatives between MXene layers with hierarchically coral-like interfaces for enhanced electromagnetic wave absorption. Journal of Materials Chemistry A.

Zheng, J., Zhao, J., Wang, L., Li, Z., Dong, W., & E, S. (2022, November). Optimal control for soft-landing in elevator emergency crash using multiple magnetorheological shock absorbers. Journal of Intelligent Material Systems and Structures.

Zhang, J., Li, Z., & Liu, X. (2021, November 8). Intelligent tea-picking system based on active computer vision and Internet of Things. Security and Communication Networks.

Dr. Wenli yang – Computer Science and Artifical intelligence – Best Researcher Award 

Dr. Wenli yang - Computer Science and Artifical intelligence - Best Researcher Award 

University of Tasmania  - Australia

Author Profile 

GOOGLE SCHOLAR

🎓 Early academic pursuits

Dr. Wenli yang’s academic journey is rooted in strong interdisciplinary training, having earned dual phds that laid the foundation for her career in artificial intelligence. her early focus on knowledge representation and algorithmic modeling sparked her interest in scalable systems. through rigorous academic training and research exposure, she developed a deep understanding of power electronics, data engineering, and image analysis. this multidisciplinary education shaped her distinctive approach to solving real-world ai challenges using technically grounded methodologies.

👩‍🏫 Professional endeavors

Currently a lecturer at the school of ict, university of tasmania, dr. yang has quickly become a recognized figure in the artificial intelligence research community. she has actively led and contributed to over 10+ research projects and 8+ consultancy/industry projects, showcasing her technical capabilities across domains. her dedication extends beyond academia, with involvement in field-based data collection initiatives and industry-driven sustainability projects. her expertise also spans power electronics, where her data-driven methodologies enhance system efficiency and smart energy solutions.

🧠 Contributions and research focus

Dr. Yang’s research areas include knowledge representation, ai-powered image analysis, explainable ai, and generative ai. she is passionate about building interpretable and robust ai Computer Science and Artifical intelligence models that perform reliably under real-world conditions. having authored 29 peer-reviewed publications, with 20 as first author, she has made consistent contributions to high-impact q1 journals. her recent studies integrate power electronics with intelligent systems, creating scalable algorithms for energy-efficient computing, smart imaging, and automation across scientific domains.

🌐 Impact and influence

Wenli yang’s work has impacted both academic and applied sectors. her h-index of 9 (scopus) and h-index of 12 (google scholar), with over 647 citations, highlight her growing influence in the ai research community. her collaborative initiatives with australia seafood industries (asi), imas, csiro, and sense-t reflect her commitment to applying ai for public good. through ai- Computer Science and Artifical intelligencedriven oyster genotyping and sustainable fisheries management, she has contributed to ecological and operational advancements across australia’s marine industries.

🔮 Legacy and future contributions

Dr. Wenli yang’s vision is to create scalable, transparent, and adaptable ai systems that serve real-world applications. she continues to expand her research in explainable ai and data Computer Science and Artifical intelligence engineering, with future goals focused on integrating power electronics into intelligent systems for sustainable smart environments. her legacy lies in bridging theoretical research with field impact, inspiring future generations to pursue responsible and innovative ai solutions across multidisciplinary domains.

Notable Publications 

  • Title: A survey on blockchain-based internet service architecture: requirements, challenges, trends, and future
    Author(s): W. Yang, E. Aghasian, S. Garg, D. Herbert, L. Disiuta, B. Kang
    Journal: IEEE Access

  • Title: Survey on explainable AI: From approaches, limitations and applications aspects
    Author(s): W. Yang, Y. Wei, H. Wei, Y. Chen, G. Huang, X. Li, R. Li, N. Yao, X. Wang, X. Gu, ...
    Journal: Human-Centric Intelligent Systems

  • Title: Blockchain: Trends and future
    Author(s): W. Yang, S. Garg, A. Raza, D. Herbert, B. Kang
    Journal: Knowledge Management and Acquisition for Intelligent Systems: 15th Pacific …

  • Title: Design of intelligent transportation system supported by new generation wireless communication technology
    Author(s): W. Yang, X. Wang, X. Song, Y. Yang, S. Patnaik
    Journal: International Journal of Ambient Computing and Intelligence (IJACI)

  • Title: A decision model for blockchain applicability into knowledge-based conversation system
    Author(s): W. Yang, S. Garg, Z. Huang, B. Kang
    Journal: Knowledge-Based Systems