Liang Li | Robot System | Best Researcher Award

Dr. Liang Li | Robot System | Best Researcher Award

Academic Leader of the Key Laboratory | Baoji University of Arts and Sciences | China

Dr. Li Liang is an academic scholar affiliated with the Baoji University of Arts and Sciences in Baoji, China. He has contributed to the fields of mechanical engineering, composite materials, robotics, and intelligent manufacturing through a consistent body of research. His publications demonstrate expertise in process modeling, knowledge graph construction, and optimization techniques for robotic systems. With an active research profile indexed in Scopus, Li Liang has achieved recognition with multiple works cited internationally. His academic career reflects a dedication to advancing modern manufacturing technologies and their integration with artificial intelligence methods in industrial applications.

Publication Profile

Scopus

Education Background

Dr. Li Liang pursued his higher education in engineering disciplines, developing a strong foundation in mechanical sciences and computational techniques. His academic training emphasized advanced mechanics, material science, and intelligent control systems, which enabled him to engage with cross-disciplinary research in automation and industrial technologies. Through rigorous study and research training, he cultivated proficiency in analytical methods and modern computational tools. His education was centered on building both theoretical and practical expertise, allowing him to contribute effectively to innovative solutions in machining processes, robotic trajectory optimization, and composite structural analysis across applied engineering fields.

Professional Experience

As an Associate faculty member at Baoji University of Arts and Sciences, Dr. Li Liang has actively participated in teaching, research, and collaborative projects. His professional experience spans guiding students, publishing scholarly works, and engaging in joint research efforts with national and international colleagues. He has authored and co-authored numerous papers, focusing on numerical modeling, intelligent robotics, and advanced materials. His contributions also extend to integrating artificial intelligence approaches with traditional engineering processes. In addition, he has built professional collaborations with more than thirty co-authors, reflecting his ability to work in team-driven scientific environments that promote applied industrial innovations.

Awards and Honors

While specific awards and grants are not publicly listed, Dr. Li Liang has earned academic recognition through consistent citations of his research and scholarly contributions. His studies published in reputable open-access journals such as Electronics and Processes have contributed to the international research community, further solidifying his academic standing. The impact of his work, reflected in increasing citations and collaborations, signifies recognition of his scholarly achievements. His commitment to advancing research on machining knowledge graphs, composite mechanics, and robotic arm optimization highlights his academic merit and serves as a foundation for future honors and acknowledgments.

Research Focus

Dr. Li Liang’s primary research interests lie in mechanical engineering, intelligent manufacturing, composite materials, and robotics. His recent works have explored the construction of machining process knowledge graphs for route recommendations, numerical analysis of advanced braided composites, and reinforcement learning optimization for robotic grasping. These areas collectively showcase his interdisciplinary focus, combining computational intelligence with mechanical design. By addressing challenges in trajectory planning, process optimization, and structural performance, his research contributes to advancing both theoretical insights and industrial applications. His focus is on creating smart, adaptive systems that bridge materials science, artificial intelligence, and industrial engineering.

Publication Top Notes

  • Construction of a Machining Process Knowledge Graph and Its Application in Process Route Recommendation
    Published Year: 2025
    Citation: 1

  • Numerical Analysis on Mechanical Properties of 3D Five-Directional Circular Braided Composites
    Published Year: 2025
    Citation: 1

  • Improved PPO Optimization for Robotic Arm Grasping Trajectory Planning and Real-Robot Migration
    Published Year: Not listed
    Citation: 1

Conclusion

Through his academic journey, Dr. Li Liang has built a strong reputation as a researcher contributing to intelligent manufacturing and computational engineering. His publications demonstrate expertise across multiple technical domains, and his collaborative work highlights his adaptability and scholarly engagement. With a growing number of citations and impactful studies, his career reflects both innovation and academic integrity. His dedication to teaching and research at Baoji University of Arts and Sciences ensures that his contributions will continue to influence the development of advanced robotic systems, material analysis, and smart manufacturing processes in both academic and applied industrial contexts.

Dr. zhendong zhao | robotics | Best Scholar Award

Dr. zhendong zhao | robotics | Best Scholar Award

Ph.D. graduate student, Hebei University of Technology, China

Zhendong Zhao is a passionate Ph.D. graduate student at the School of Artificial Intelligence and Data Science, Hebei University of Technology, China . With a strong foundation in control science and engineering, Zhendong is deeply involved in cutting-edge research in embodied intelligence and robotics powered by large language models (LLMs). His dedication to integrating AI with robotics has already led to the development of novel frameworks that enhance collaborative and autonomous robotic systems 🤖.

Publication Profile

ORCID

🎓 Education Background:

Zhendong Zhao is currently pursuing his Ph.D. in Control Science and Engineering at Hebei University of Technology. His academic path has been rooted in artificial intelligence, with a strong emphasis on integrating LLMs into real-world robotic applications. He has been trained in advanced AI theories, machine learning, and robotic systems that lay the groundwork for his research endeavors 📚.

💼 Professional Experience:

As a doctoral researcher at Hebei University of Technology, Zhendong Zhao has contributed to developing innovative robotic frameworks. His research focuses on leveraging large language models to enhance robot collaboration, especially in healthcare contexts like nursing robots. Despite his early career stage, Zhendong has demonstrated remarkable potential through independent research and publications in top-tier journals 🧪.

🏅 Awards and Honors:

While no formal awards have been mentioned yet, Zhendong Zhao’s impactful research and publication record already highlight his contributions to AI and robotics. His work has earned attention through prestigious platforms such as IEEE Robotics and Automation Letters and Bioengineering, positioning him as a rising researcher in the field 🏆.

🔬 Research Focus:

Zhendong’s research centers around embodied intelligence and LLM-based dual-arm robotics. He introduced a dual-agent framework named DABICO for task planning in nursing robots. This system builds a dual-agent (left-arm and right-arm) structure that emphasizes inter-agent communication and validation mechanisms. His research pushes the frontier of how LLMs can coordinate physical tasks across robotic limbs in real-time, especially for bimanual coordination tasks in caregiving robots 🦾.

✅ Conclusion:

Zhendong Zhao stands out as a forward-thinking Ph.D. researcher who merges AI theory with practical robotic implementations. With multiple publications in high-impact journals and a focused vision for advancing embodied intelligence, Zhendong is poised to become a significant contributor to the future of intelligent robotics.

📝 Top Publications :

The Multi-Agentization of a Dual-Arm Nursing Robot Based on Large Language Models
📅 Published: 2025
📚 Journal: Bioengineering
🔗 DOI: 10.3390/bioengineering12050448
🔁 Cited by: Crossref-indexed (specific citation count pending)

A Dual-Agent Collaboration Framework Based on LLMs for Nursing Robots to Perform Bimanual Coordination Tasks
📅 Published: 2025
📚 Journal: IEEE Robotics and Automation Letters
🔗 DOI: 10.1109/LRA.2025.3533476
🔁 Cited by: Crossref-indexed (specific citation count pending)