Prof. Hong Zheng | Computational Mechanics | Best Researcher Award

Prof. Hong Zheng | Computational Mechanics | Best Researcher Award

Prof. Hong Zheng | Computational Mechanics – Beijing University of Technology, China

Prof. Hong Zheng is a highly accomplished academic and researcher in the field of geotechnical and computational civil engineering. With more than three decades of research experience, he has become a key figure in the development of numerical modeling methods for rock and soil mechanics. His scholarly work integrates traditional engineering models with modern computational approaches, particularly artificial intelligence and numerical manifold methods, making his research widely applicable and forward-looking in civil infrastructure and geomechanical analysis.

Profile Verified:

Orcid | Scopus 

Education:

Prof. Zheng earned his Ph.D. in Civil Engineering from Beijing University of Technology. His doctoral training focused on structural and geotechnical modeling, providing him with a strong foundation in both theoretical and applied mechanics. His academic excellence during this period shaped the trajectory of his research in advanced numerical techniques for solving complex civil engineering problems.

Experience:

Prof. Zheng’s professional experience spans several renowned institutions. He began his research career at the Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, where he worked for over two decades (1988–2013), contributing extensively to slope stability and rock mechanics research. From 2001 to 2014, he was affiliated with China Three Gorges University, participating in research projects related to dam safety and hydropower infrastructure. Since 2013, he has been a full-time faculty member at Beijing University of Technology, where he is actively involved in teaching, supervising Ph.D. students, and leading research initiatives in computational geomechanics.

Research Interests:

Prof. Zheng’s research interests center around advanced computational methods for civil and geotechnical engineering problems. He specializes in the Numerical Manifold Method (NMM), Finite-Discrete Element Method (FDEM), and deep learning applications for slope and tunnel stability analysis. His recent work includes physics-informed neural networks for 3D seepage prediction and hybrid numerical-AI models for complex unconfined flow problems. His interdisciplinary approach addresses real-world engineering challenges with innovative computational techniques.

Awards:

While not formally listed with individual honors, Prof. Zheng’s recognition comes through consistent publications in prestigious international journals, extensive citation by peers, and influential roles in large-scale engineering projects. His sustained academic output, institutional leadership, and role as a mentor to numerous graduate students underscore his eligibility for high-level research recognition.

Selected Publications:

  • 🧠 “The pre-trained explainable deep learning model with stacked denoising autoencoders for slope stability analysis” (2024, Engineering Analysis with Boundary Elements) – cited by 12 articles.
  • 🌊 “Three-dimensional seepage analysis for the tunnel in nonhomogeneous porous media with physics-informed deep learning” (2025, Engineering Analysis with Boundary Elements) – cited by 8 articles.
  • 🧱 “Modeling variably saturated flows in porous media using the numerical manifold method” (2024, Engineering Analysis with Boundary Elements) – cited by 10 articles.
  • 🧩 “Boundary settings for seismic dynamic analysis of rock masses using the nodal-based continuous-discontinuous deformation analysis method” (2025, Computer Methods in Applied Mechanics and Engineering) – cited by 7 articles.
  • ⚙️ “Preconditioned smoothed numerical manifold methods with unfitted meshes” (2023, International Journal for Numerical Methods in Engineering) – cited by 15 articles.
  • 🔍 “A new procedure for locating free surfaces of complex unconfined seepage problems using fixed meshes” (2024, Computers and Geotechnics) – cited by 6 articles.
  • 🧮 “Shear band static evolution based on complementarity method and the improved numerical manifold method” (2024, Engineering Analysis with Boundary Elements) – cited by 9 articles.

Conclusion:

In summary, Prof. Hong Zheng exemplifies the profile of a highly innovative, dedicated, and impactful researcher. His extensive career in academia, combined with deep technical knowledge and modern interdisciplinary integration, positions him as an ideal candidate for the Best Researcher Award. His research has not only advanced the academic understanding of geomechanical processes but also contributed to the safety and sustainability of large civil infrastructure. His commitment to excellence, mentorship, and research leadership continues to shape the field and inspire emerging engineers worldwide.

 

 

Jian Qin | Structural analysis, Nonlinear calculation | Excellence in Scientific Innovation Award

Prof. Dr. Jian Qin | Structural analysis, Nonlinear calculation | Excellence in Scientific Innovation Award

Senior Technical Expert at State Grid Electric Power Engineering Research Institute Co., Ltd, China

Qin Jian is an esteemed researcher and senior technical expert specializing in power transmission and substation engineering. With a background in solid mechanics and mechanical engineering, he has contributed significantly to the advancement of transmission line equipment and nonlinear mechanical studies. His expertise lies in developing innovative solutions for complex power transmission challenges, leading several key research projects in the field. Over the years, his work has been recognized with multiple prestigious awards, demonstrating his influence in the domain of electrical power infrastructure and engineering mechanics.

Profile

Scopus

Education

Qin Jian pursued his higher education in solid mechanics at Peking University, where he earned his doctoral degree in 2009. His research during this period focused on advanced computational methods in mechanical analysis, laying a strong foundation for his later work in engineering applications. Following his PhD, he undertook postdoctoral research at the University of Science and Technology Beijing, further refining his expertise in mechanical engineering and structural analysis.

Experience

After completing his postdoctoral studies, Qin Jian joined the China Electric Power Research Institute in 2011, where he has been actively engaged in research and development related to power transmission and substation engineering. His professional journey has been marked by significant contributions to the study of nonlinear mechanics in transmission line construction and the development of specialized equipment for efficient power infrastructure deployment. As a senior technical expert, he has played a vital role in multiple national-level projects, enhancing the safety, efficiency, and reliability of electrical power networks.

Research Interests

Qin Jian’s research interests encompass power transmission line equipment, nonlinear mechanical behavior in construction, and the development of intelligent engineering solutions. His studies focus on improving the efficiency of material transport in complex terrains using cableway systems, as well as optimizing structural integrity through advanced computational modeling. His work integrates experimental research, numerical simulation, and field applications, aiming to enhance both theoretical understanding and practical implementation in transmission engineering.

Awards

Qin Jian’s outstanding contributions to power transmission engineering have been recognized through several prestigious awards. In 2021, he received the second prize in the State Grid Science and Technology Progress Awards for his pioneering work on aerial cableway systems in transmission line construction. His innovative safety assessment techniques and intelligent design systems for cable transport earned him the second prize in the China Electric Power Construction Science and Technology Progress Awards in 2020. Additionally, he has been honored with multiple accolades from the China Electric Power Research Institute for his advancements in nonlinear mechanics and engineering design, further solidifying his reputation as a leading expert in his field.

Publications

Qin Jian has authored numerous high-impact journal articles, contributing to the advancement of power transmission engineering and nonlinear mechanics. Below are seven selected publications along with their respective journals and publication years:

Qin J., Qiao L., et al. (2025). “Calculation Method and Experimental Research on Strand Breakage in Large Cross-section Conductors Considering Contact Between Strands.” Engineering Failure Analysis.

Qin Jian, Qiao Liang, et al. (2024). “Analysis, Simulation, and Experimental Research on the Mechanisms of Lantern-shaped Strand Defects in the Conductor Construction of Transmission Line.” Structures.

Qin J., Zhang Q. D., Huang K. F. (2011). “Oblique and Herringbone Buckling Analysis of Steel Strip by Spline FEM.” Journal of Iron and Steel Research (International).

Qin J., Zhang Q. D., Huang K. F. (2012). “Nonlinear Spline Finite Element Method for Ribbing of Cold-Rolled Coils.” Journal of Iron and Steel Research (International).

Qin Jian, Xia Yongjun. (2013). “Suspension Analysis Matrix Iteration Method Based on Segmented Catenary Theory.” Journal of Engineering Design.

Qin Jian, Qiao Liang, Jiang Ming, et al. (2019). “Multi-support Cableway Load Calculation Method and Tension Imbalance Effect Analysis.” China Safety Science and Technology Journal.

Qin Jian, Zhang Feikai, Li Qiying, et al. (2022). “Automatic Path Planning Method for Cargo Ropeways Based on Terrain Adaptation.” Journal of Southwest Jiaotong University.

Conclusion

Based on his academic excellence, innovative research contributions, leadership in national projects, and recognized impact in engineering sciences, Qin Jian is highly suitable for the Research for Excellence in Scientific Innovation Award. His work in power transmission, structural mechanics, and computational methodologies has significantly advanced the field, making him a strong candidate for recognition in scientific innovation.