Liang Li | Robot System | Best Researcher Award

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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.

Heung-Shik Lee | Robotics | Best Researcher Award

Published on by Computer Scientists Awards

Prof. Heung-Shik Lee | Robotics | Best Researcher Award

Professor, Joongbu University, South Korea

Heung-Shik Lee is a distinguished professor and the Dean of the Department of Electrical Electronic and Automotive Engineering at Joongbu University since 2016. 🌟 With a solid background as a technical advisory member for the Ministry of SMEs and Startups and the Ministry of Environment, Prof. Lee has made significant contributions to the field. Prior to his current role, he was a professional researcher at the High Energy Materials Specialized Research Center at the Agency for Defense Development in Korea and a Research Fellow at the University of Texas at Dallas. 🌐

Profile

Strengths for the Award:

  1. Innovative Research Focus: Prof. Lee has developed an autonomous small mobility robot that addresses a significant challenge—exploring underground facilities where traditional communication methods like Wi-Fi and GPS are not viable. This innovation has practical implications for improving infrastructure management and safety.
  2. Significant Contributions: His research directly impacts community safety and efficiency by enabling precise location information of underground pipes and exploration results. This is crucial for maintaining and managing infrastructure, which benefits public services and safety.
  3. Professional Expertise: Prof. Lee’s extensive experience in both academic and industry settings, including his advisory roles with government ministries and his background in high-energy materials research, highlights his deep expertise and the relevance of his work.
  4. Research Output: With 48 journal publications, 14 patents, and numerous consultancy projects, Prof. Lee demonstrates a high level of productivity and impact in his field. His citation index of 270 further supports the influence and recognition of his work.
  5. Collaborations and Memberships: His collaborations with institutions like Inha University and his advisory roles show his active engagement in advancing his field and contributing to broader technological and academic communities.

Areas for Improvement:

  1. Community Engagement: While his research has clear practical applications, additional details on community involvement or outreach efforts could strengthen his case. Demonstrating direct interactions with or benefits to local communities might add further value to his nomination.
  2. Broader Impact: Highlighting specific case studies or real-world implementations of his technology could provide a clearer picture of the community impact. Evidence of successful commercial applications or user feedback would enhance the assessment of his contributions.
  3. Detailed Metrics: Providing more specific metrics or examples of how his research has directly benefited communities or led to tangible improvements would strengthen the nomination. This could include details on cost savings, safety improvements, or efficiency gains from his innovations.

Education

Prof. Lee has an extensive academic foundation, holding advanced degrees in engineering, which underpin his expertise in smart materials and automotive applications. 📚

Experience

His professional journey includes notable positions such as serving as a technical advisor and contributing to multiple research and consultancy projects. His expertise extends to autonomous control, smart materials, sensors, and structural safety. 🚀

Research Interests

Prof. Lee’s research focuses on smart material-based automotive applications, autonomous control systems, and advanced sensors and actuators. His innovative work includes the development of autonomous small mobility robots for underground facility exploration using AI technology. 🤖

Awards

Prof. Lee is nominated for the Best Researcher Award, recognizing his exceptional contributions to the field of engineering and technology. 🏆

Publications

Mask R-CNN-Based Stone Detection and Segmentation for Underground Pipeline Exploration Robots

An Inverse Perspective Mapping-Based Approach for Generating Panoramic Images of Pipe Inner Surfaces

Analysis of Used Cars Price Determinant Factors Using IPA | IPA

Multiple IMU sensor fusion using resolution refinement method to reduce quantization error