Dr. Liu Ying | Engineering | Research Excellence Award

Dr. Liu Ying | Engineering | Research Excellence Award

East China Jiaotong University | China

Dr. Liu Ying is a dedicated researcher and lecturer in the field of mechanical and vehicle engineering, recognized for her growing scholarly contributions and interdisciplinary expertise that bridges intelligent control, computer vision, image detection, and reinforcement learning. With an academic foundation shaped through rigorous training in mechanical design, manufacturing, automation, and advanced mechanical engineering, she has developed a strong research trajectory supported by both theoretical depth and applied innovation. Her scholarly record reflects an emerging yet impactful academic presence, demonstrated through 6 published documents, 15 citations, and an h-index of 2, highlighting the relevance and early influence of her work within the scientific community. Dr. Liu’s research explores visual perception, target localization, and intelligent analysis, forming an integrated framework that advances algorithmic design and real-world technical applications. She has contributed to multiple scientific research projects, including national-level initiatives and collaborative programs with substantial funding volumes, underscoring her active role in large-scale, multidisciplinary research environments. Her output also includes seven journal publications indexed in major scholarly databases and more than twenty patents that showcase her drive for innovation and technological development. Beyond academic publishing, she has completed numerous consulting and industry-related projects, translating her research insights into practical solutions for engineering challenges. As a young academic, she has already taken lead roles in talent programs and continues to expand her impact by addressing key problems in vehicle engineering and intelligent systems. With a professional approach grounded in scientific rigor and a commitment to future-oriented advancements, Dr. Liu Ying exemplifies the qualities of an emerging research leader whose contributions continue to shape the evolving landscape of intelligent engineering and applied computational methodologies.

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Featured Publication

Zhi-Qiang Tao | Mechanical Engineering| Best Researcher Award

Dr .Zhi-Qiang Tao | Mechanical Engineering| Best Researcher Award

Research Contributions:
  • With over 20 peer-reviewed technical papers published in international journals and conference proceedings, Dr. Tao has significantly contributed to the understanding and advancement of his specialized research areas. His publications reflect the breadth of his knowledge and dedication to his field.
 Dr . Zhi-Qiang Tao, Zhejiang Ocean University, China

Profile

Scopus

🎓Early Academic Pursuits

  • Zhi-Qiang Tao received his Ph.D. in Mechanical Engineering from Beijing University of Technology in 2018. During his doctoral studies, Tao focused on mechanical dynamics and fatigue-related phenomena, laying the foundation for his future research in fatigue mechanisms, particularly in multiaxial and very high cycle fatigue.

💼Professional Endeavors

  • After completing his Ph.D., Zhi-Qiang Tao became a Research Assistant at the Robotics College of Beijing Union University. Here, he collaborated with colleagues on cutting-edge research in robotics and mechanical engineering, contributing significantly to the development of fatigue analysis tools and technologies. His role also involved mentoring students and assisting in various research projects.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

  • Zhi-Qiang Tao has focused extensively on:
    • Mechanical Dynamics
    • Multiaxial Fatigue
    • Very High Cycle Fatigue (VHCF)

    His research investigates how materials respond under extreme conditions over extended periods, helping industries understand material durability and mechanical resilience. His work has applications across sectors such as automotive, aerospace, and robotics, providing critical insights into the longevity and safety of components.

🏆IMPACT AND INFLUENCE

  • Tao’s research on very high cycle fatigue is of particular importance, as it addresses the need for understanding how materials behave under more than one million cycles of loading. His work helps improve the design of mechanical systems to avoid failures, thus enhancing safety and reliability in critical infrastructures. With over 20 peer-reviewed technical papers published in international journals and conference proceedings, his work has been widely cited and recognized. His contributions serve as a foundation for ongoing studies in fatigue failure mechanisms.

🏅ACADEMIC CITES

  • Zhi-Qiang Tao has received numerous citations in the fields of mechanical dynamics and fatigue studies, underscoring his impact on the academic community. His contributions have been referenced in studies related to material resilience, fatigue life prediction, and failure analysis, emphasizing his role in advancing the understanding of fatigue phenomena in engineering materials.

🔮LEGACY AND FUTURE CONTRIBUTIONS

  • Zhi-Qiang Tao’s legacy in the field of mechanical engineering is one of persistence and innovation. His future contributions are expected to continue influencing how industries approach material fatigue and structural design. As fatigue becomes an increasingly crucial aspect of robotic systems, Tao’s work will play a pivotal role in ensuring mechanical components can withstand extreme conditions and prolonged use. Through his research, he has not only contributed to academia but also provided valuable insights for industry applications that focus on extending the life cycle of mechanical components, enhancing both safety and performance.

📰PUBLICATIONS

  • A new probabilistic control volume scheme to interpret specimen size effect on fatigue life of additively manufactured titanium alloys
    Authors: Tao, Z.-Q., Wang, Z., Pan, X., Qian, G., Hong, Y.
    Journal: International Journal of Fatigue, 2024, 183, 108262
  •  Surface roughness prediction and roughness reliability evaluation of CNC milling based on surface topography simulation
    Authors: Zhang, Z., Lv, X., Qi, B., Zhang, M., Tao, Z.
    Journal: Eksploatacja i Niezawodnosc, 2024, 26(2), 183558
  •  Life prediction method based on damage mechanism for titanium alloy TC4 under multiaxial thermo-mechanical fatigue loading
    Authors: Li, D.-H., Shang, D.-G., Mao, Z.-Y., Cong, L.-H., Tao, Z.-Q.
    Journal: Engineering Fracture Mechanics, 2023, 282, 109206
  • Multiaxial fatigue life estimation based on weight-averaged maximum damage plane under variable amplitude loading
    Authors: Tao, Z.-Q., Qian, G., Li, X., Zhang, Z.-L., Li, D.-H.
    Journal: Journal of Materials Research and Technology, 2023, 23, pp. 2557–2575
  •  Multiaxial fatigue life prediction by equivalent energy-based critical plane damage parameter under variable amplitude loading
    Authors: Tao, Z.-Q., Qian, G., Sun, J., Zhang, Z.-L., Hong, Y.
    Journal: Fatigue and Fracture of Engineering Materials and Structures, 2022, 45(12), pp. 3640–3657