Jinting Huang | Intelligent construction | Best Researcher Award

Mr Jinting Huang | Intelligent construction | Best Researcher Award

Master, Huazhong University of Science and Technology, China

Huang Jinting is a distinguished civil engineer specializing in intelligent construction and sustainable project management. He is currently pursuing a graduate degree in Civil Engineering at Huazhong University of Science and Technology, focusing on data-driven optimization and artificial intelligence in construction. With extensive experience in strategic planning and large-scale infrastructure projects, including Kuala Lumpur Metro phases, Huang has developed expertise in tunnel engineering, structural design, and construction management. His work has been published in reputed journals, emphasizing innovative engineering applications.

PROFILE

Scopus

STRENGTHS FOR THE AWARD

  1. Extensive Academic Background: Huang Jinting has pursued advanced studies in Civil Engineering, with a focus on intelligent construction. His education is enriched with expertise in artificial intelligence, safety management, and energy-saving construction principles, providing a solid foundation for innovative research.
  2. Professional Experience: With diverse roles in multinational projects, including strategic planning, site management, and tunnel engineering, Huang has demonstrated a practical understanding of complex civil engineering challenges. His leadership roles underline his ability to manage high-stakes projects.
  3. Published Research Contributions: His publications in reputable journals, such as Engineering Applications of Artificial Intelligence and Engineering, Construction and Architectural Management, highlight cutting-edge advancements in excavation efficiency and cost optimization.
  4. Integration of AI in Engineering: Huang’s focus on integrating AI to optimize construction processes addresses modern engineering challenges, aligning with trends in smart construction and sustainability.

AREAS FOR IMPROVEMENT

  1. Research Diversity: Expanding the scope of research to encompass additional areas of intelligent construction, such as sustainability metrics and lifecycle analysis, could further strengthen his contributions.
  2. Collaborations and Funding: Enhancing collaborations with global research institutions and securing grants could elevate the impact and visibility of his work.
  3. Citation Metrics: Improving citation counts by actively promoting research findings through conferences, workshops, and interdisciplinary collaborations would add weight to his candidacy for the award.

EDUCATION

  • 2022.09–2025.06: Graduate Student in Civil Engineering, Huazhong University of Science and Technology, Wuhan, China πŸ“˜
    • Focus: Intelligent Construction
    • Courses: Advanced Engineering Mathematics, AI in Civil Engineering, Energy-Saving Construction Principles
  • 2010.09–2014.06: Undergraduate in Civil Engineering and Hubei Institute of Engineering πŸŽ“
    • Focus: Road and Bridge Engineering
    • Courses: Structural Mechanics, Pavement Engineering, Bridge Construction

EXPERIENCE

  • 2018.1–2020: Country Development Team Leader, China Railway Oriental International Group 🌏
    • Spearheaded projects in the Indonesian market, strategic planning, and technical marketing.
  • 2016.8–2018.1: Site Manager, Kuala Lumpur Metro Phase II Project πŸ—οΈ
    • Managed tunnel construction design, quality control, and safety.
  • 2015.6–2016.8: Assistant Structural Engineer, Kuala Lumpur Metro Phase I Project πŸ› οΈ
    • Optimized designs for MRT stations and related infrastructure.
  • 2014.7–2015.6: Trainee, Nanyang Tunnel Company, China Railway Oriental International Group πŸ›€οΈ

AWARDS AND HONORS

  • Recognized for innovative design and execution in metro tunnel construction. πŸ…
  • Honored for excellence in the strategic planning and market development for Indonesian projects. πŸŽ–οΈ
  • Achieved commendations for contributions to intelligent construction methodologies. πŸ†

RESEARCH FOCUS

Huang Jinting’s research revolves around intelligent construction and particularly data-driven optimization in tunnel excavation and high-rise building project management. His Intelligent Construction work integrates artificial intelligence and modern construction techniques to enhance efficiency, reduce costs, and manage uncertainty.

PUBLICATION TOP NOTES

  • Data-driven optimization for enhanced excavation efficiency in tunnel construction: A case study” πŸ“„
  • “Schedule-cost optimization in high-rise buildings considering uncertainty” πŸ“Š

CONCLUSION

Huang Jinting is a highly promising candidate for the Best Researcher Award due to his strong academic credentials, impactful professional experience, and innovative research contributions. With a focus on intelligent construction and AI-driven optimization, he demonstrates significant potential for influencing the future of civil engineering. Intelligent Construction addressing minor areas for improvement could further solidify his position as an outstanding researcher in his field.

Dong Zikai – TBM Intelligent construction – Best Researcher Award

Dong Zikai - TBM Intelligent construction - Best Researcher Award

Beijing Jiaotong University - China

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Dong Zikai embarked on his academic journey with a Bachelor's degree in Civil Engineering from Southwest Jiaotong University, Chengdu, China, in 2015. He continued his studies with a Master's degree in Architecture and Civil Engineering from Beijing Jiaotong University in 2019. Currently, he is pursuing a Ph.D. in Civil Engineering at Beijing Jiaotong University, where his research focuses on intelligent assistance technology for Tunnel Boring Machine (TBM) tunnelling.

PROFESSIONAL ENDEAVORS

As a doctoral student in the Department of Geotechnical Engineering at Beijing Jiaotong University, Dong Zikai has made significant contributions to his field. Under the guidance of Professor Li Xu, he has been involved in several research projects and has demonstrated exceptional academic performance. Dong has also participated in competitions such as the TBM competition and the "Huawei Cup" Chinese Graduate Students Artificial Intelligence Innovation Competition, where he achieved notable success.

CONTRIBUTIONS AND RESEARCH FOCUS

Dong Zikai's research is centered on TBM intelligent construction, with a specific focus on developing intelligent assistance technology. His work has led to the publication of several academic papers in reputable journals, including Automation in Construction and Georisk. His research contributions extend to the development of convolutional neural network-based models for recognizing TBM rock chip gradation, denoising methods in TBM rock fragmenting data, and classification prediction of surrounding rock based on TBM muck images.

IMPACT AND INFLUENCE

Dong Zikai's research has made a significant impact on the field of geotechnical engineering, particularly in the realm of TBM intelligent construction. His innovative approaches and methodologies have advanced our understanding of TBM tunnelling processes and have practical implications for improving construction efficiency and safety. Dong's publications have garnered attention within the academic community, further solidifying his influence and recognition in the field.

ACADEMIC CITES

Dong Zikai's research findings have been published in prestigious academic journals and have been cited by fellow scholars and researchers. His work on TBM intelligent construction has contributed to the body of knowledge in geotechnical engineering and has been referenced in related studies and publications. Dong's citations reflect the relevance and impact of his research on the broader academic community.

LEGACY AND FUTURE CONTRIBUTIONS

As Dong Zikai continues his doctoral studies and research endeavors, he is poised to make further contributions to the field of geotechnical engineering, particularly in the area of TBM intelligent construction. His innovative research methodologies and technological advancements have the potential to revolutionize TBM tunnelling practices, leading to safer, more efficient, and sustainable infrastructure development. Dong's commitment to academic excellence and his dedication to advancing the field ensure a promising legacy and future contributions in geotechnical engineering.

NOTABLE PUBLICATION

Experimental Study on Instant Grouting with Formwork for Tunnels 2022 (2)

Classification Prediction of Surrounding Rock Based on TBM Muck Images 2023

Experimental Investigation on Mechanical Characteristics of Waterproof System for Near-Sea Tunnel: A Case Study of the Gongbei Tunnel 2020 (11)

Xu Li – TBM Intelligent construction – Best Researcher Award

Xu Li - TBM Intelligent construction - Best Researcher Award

Beijing Jiaotong University - China

AUTHOR PROFILE

Scopus
ORCID

EARLY ACADEMIC PURSUITS

Dr. Xu Li embarked on his academic journey with a Bachelor's degree in Hydraulic and Hydropower Engineering from Tsinghua University, Beijing, China, in 2001. He continued his studies with a Master's degree in Hydraulic Structure Engineering from Tsinghua University in 2004. Dr. Li further pursued a Ph.D. in Civil Engineering at The University of Science and Technology, Hong Kong, graduating in 2009. His academic pursuits laid a solid foundation for his future endeavors in the field of geotechnical engineering, with a focus on special soil mechanics and TBM automatic control algorithms.

PROFESSIONAL ENDEAVORS

Dr. Xu Li has accumulated a wealth of professional experience throughout his career. He served as a Post-Doctoral Fellow at The University of Science and Technology, Hong Kong, from January to June 2009, where he conducted research on the failure mechanisms of rainfall-induced landslides. Subsequently, he worked as an Associate Professor at the Department of Geotechnical Engineering, School of Civil Engineering, Beijing Jiaotong University, China, from September 2009 to November 2016, and later as a Professor from December 2016 to the present. His responsibilities included teaching undergraduate and postgraduate courses in soil mechanics, consulting on geotechnical engineering projects, and supervising student research.

CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Xu Li's research primarily focuses on TBM (Tunnel Boring Machine) intelligent construction and special soil mechanics. He has made significant contributions to the field through his publications and projects. His research endeavors have led to advancements in the prediction of TBM performance, real-time perception methods for rock conditions in TBM construction, and cross-project utilization of TBM construction data. Dr. Li's work has not only enhanced our understanding of geotechnical engineering but also contributed to the development of innovative technologies for infrastructure projects.

IMPACT AND INFLUENCE

Dr. Xu Li's research has had a notable impact on the field of geotechnical engineering. His publications have been widely cited in academic literature, indicating the relevance and significance of his work. Moreover, Dr. Li's involvement in professional societies and committees, such as the International Society of Soil Mechanics and Geotechnical Engineering (ISSMGE), underscores his influence and recognition within the global geotechnical community. His contributions to TBM intelligent construction and special soil mechanics continue to shape the future of geotechnical engineering practice.

ACADEMIC CITES

Dr. Xu Li's research findings have been published in reputable journals and conference proceedings, garnering citations from scholars and researchers worldwide. His work on TBM construction methods, rock condition characterization, and soil mechanics has contributed to the advancement of knowledge in geotechnical engineering. The impact of his research is evident in the numerous citations his publications have received, highlighting the significance of his contributions to the field.

LEGACY AND FUTURE CONTRIBUTIONS

Dr. Xu Li's dedication to TBM intelligent construction and special soil mechanics positions him as a leading figure in geotechnical engineering. His ongoing research and collaborations are poised to further expand our understanding of underground construction methods and soil behavior. Through his continued efforts, Dr. Li aims to address emerging challenges in infrastructure development and pave the way for sustainable and efficient construction practices.

NOTABLE PUBLICATION

MDG: A Multi-Task Dynamic Graph Generation Framework for Multivariate Time Series Forecasting 2024