Luo Liang | Intelligent Construction | Best Research Award

Dr.Luo Liang , Harbin Institute of Technology , China.

Dr.Luo Liang is an Assistant Researcher specializing in intelligent construction and bridge engineering. he is a member of the Chinese Communist Party. He is currently pursuing a Ph.D. in Civil Engineering at Harbin Institute of Technology (HIT), focusing on AI-driven sustainable bridge maintenance and intelligent construction. Luo has published over ten high-impact SCI papers and has contributed to key national research projects. His expertise includes AI-driven decision-making for structural health monitoring and high-performance building connections. Luo is skilled in MATLAB, Python, CAD, and simulation software like Abaqus and ANSYS.

Publication Profile

Orcid

Scopus

Google Scholar

Education & Experience

Ph.D. in Civil Engineering (2021.09–2025.01) – Harbin Institute of Technology (C9)
- Research: Sustainable bridge assessment, AI-driven maintenance
- Advisors: Prof. Lü Dagang, Prof. Jia Mingming
- GPA: 3.56/4
M.Sc. in Civil & Transportation Engineering (2018.09–2021.06) – South China University of Technology (985)
- Research: High-performance building connections
- Advisor: Prof. Wang Zhan
- GPA: 3.54/4
B.Sc. in Civil Engineering (2014.09–2018.06) – East China Jiaotong University
- GPA: 3.86/4 (Top 5%)
- Courses: Concrete & Steel Structure Design, Bridge Engineering
Research Projects:
- National Key R&D Program (2022-2025) – AI-based dynamic maintenance for bridges
- National Natural Science Foundation Key Project (2017-2021) – High-performance structural connections
Industry Experience:
- Research Assistant (2021-Present) – Assists in national research & academic awards
- China Resources Land Guangzhou (2019-2021) – Participated in project planning & design

Suitability Summary

Dr. Liang Luo’s research in Intelligent Construction and Bridge Engineering exemplifies cutting-edge advancements in sustainable infrastructure and structural performance analysis. With over 10 high-impact publications in renowned journals such as Engineering Structures, Construction and Building Materials, and the Journal of Cleaner Production, his work has significantly contributed to the evolution of civil engineering methodologies. His award-winning study, “Experimental Study and Theoretical Prediction of Axial Compression Behavior in PMC-Reinforced CFST Columns with Void Defects”, recognized with the Best Research Award, underscores his expertise in enhancing structural resilience and efficiency. His contributions align perfectly with the pursuit of innovative, eco-friendly construction solutions that redefine the future of intelligent engineering.

Professional Development

Dr.Luo Liang is dedicated to advancing intelligent construction through AI and digital modeling. His Ph.D. research focuses on integrating AI-driven maintenance strategies for bridge structures, leveraging big data analytics, IoT sensing, and structural health monitoring. Luo’s expertise extends to high-performance structural connections, enhancing infrastructure resilience. He has hands-on experience with simulation tools like Abaqus, ANSYS, and Midas Civil, as well as programming languages such as Python and MATLAB. Additionally, he actively contributes to national research projects, optimizing AI-driven decision-making in civil engineering. His work bridges the gap between traditional structural engineering and emerging intelligent technologies.

Research Focus

Dr.Luo Liang specializes in Intelligent Construction & Bridge Engineering, integrating AI-driven decision-making into infrastructure maintenance. His research revolves around:

Sustainable Bridge Assessment – AI-powered maintenance strategies
Smart Infrastructure Monitoring – IoT-based predictive analytics
Structural Health Diagnosis – Digital modeling & 3D reconstruction
High-Performance Structural Connections – Experimental studies & simulations
Lifecycle Structural Analysis – Failure probability & serviceability evaluations
His work aims to improve infrastructure safety, sustainability, and efficiency through advanced computational models and intelligent monitoring technologies.

Awards & Honors

National Ph.D. Scholarship & Inspirational Scholarship
Outstanding Graduate & Excellent Party Member
Top 3 in University Bridge Design Competition
Outstanding Student Leader & Three-Good Student Award
Reviewer for SCI-indexed Journals – Conducts annual peer reviews for top research publications

Publication Top Notes

“Exploration of the behavior and evolution features of beam-column joints with T-stub using the structural strain energy method” (2024)
“Experimental study and analytical modeling of tensile performance of ultra-high-performance concrete incorporating modified recycled aggregates” (2024)
“Experimental study and theoretical prediction of axial compression behavior in PMC-reinforced CFST columns with void defects” (2024)
“The treated recycled aggregates effects on workability, mechanical properties and microstructure of ultra-high performance concrete co-reinforced with nano-silica and steel fibers” (2024)
“Seismic behavior of reduced beam section joints considering concrete floor effect” (2024)
“Evolution characteristics and performance evaluation of extended end-plate joints with single and double side connections under cyclic loading” (2024)

Yang Yang | Intelligent Construction | Best Researcher Award

Assoc.Prof.Dr. Yang Yang, Chongqing University , China.

Yang Yang is the Head of the Engineering Construction Research Institute at Chongqing University, an Associate Professor, and a Doctor of Engineering. As a national-level construction engineer and outstanding young talent, she has made significant strides in intelligent construction. Yang Yang’s expertise spans the integration of digital technologies, safety systems, and advanced construction solutions. She has led multiple key projects, published extensively in top journals, authored influential textbooks, and secured numerous patents. Her pioneering work reflects her dedication to innovation and sustainable advancements in the construction industry.

Education and Experience

Doctor of Engineering

Associate Professor and Master Tutor at Chongqing University

Head of the Engineering Construction Research Institute

National-Level Construction Engineer

Outstanding Young Talent in Intelligent Construction

Over 16 authorized patents, 35 journal publications in Web of Science, and editorial board roles.

Suitability For The Award

Assoc. Prof. Dr. Yang Yang, an accomplished academic and industry leader, is a deserving candidate for the Best Researcher Award. Serving as the Head of the Engineering Construction Research Institute at Chongqing University, Dr. Yang has made pioneering contributions to intelligent construction, safety analysis, and digital technologies. His extensive research portfolio includes 35 Web of Science-indexed publications, 16 invention patents, and numerous impactful industry collaborations. Recognized with prestigious awards such as the China Technology Market Golden Bridge Award, Dr. Yang’s work exemplifies innovation, excellence, and leadership in construction science, making him an ideal recipient of the Best Researcher Award.

Professional Development

Yang Yang has contributed immensely to advancing intelligent construction technologies. Her research focuses on safety systems, defect detection, and optimization of construction workflows using AI and BIM tools.

She has developed cutting-edge methods like intelligent safety analysis of formwork, evacuation route planning in dynamic environments, and parameter identification systems using computer vision.

Her leadership extends beyond academia to industry collaborations, where she has championed high-impact projects improving construction safety and efficiency. Through her work, she bridges the gap between research, education, and real-world applications.

Research Focus

Yang Yang’s research focuses on Intelligent Construction and digital transformation of the building industry. Her innovations include safety monitoring using AI, dynamic evacuation planning for construction sites, and defect detection with computer vision. She applies convolutional neural networks to identify key parameters in construction components, ensuring precision and quality. Her work emphasizes automation, sustainability, and safety across the life cycle of construction projects, including rail transit, wind power systems, and prefabricated structures. Her research accelerates industry adoption of smart and digital solutions for modern infrastructure development.

Awards and Honors

Second Prize – China Technology Market Golden Bridge Award, 2024
Second Prize – National Steel Structure Industry Digital Twin BIM Competition, 2023
Second Prize – Engineering Construction Micro-Innovation Technology Competition, 2024
Engineering Construction Science and Technology Award, 2024
Second Prize – Science and Technology Award, China Communications and Transportation Association, 2024
Second Prize – Qinghai Provincial Science and Technology Progress Award, 2021
Innovation Award – China Urban Rail Transit Science and Technology Innovation Competition, 2022

Publications Top Notes

Classification and Application of Deep Learning in Construction Engineering and Management – A Systematic Literature Review and Future Innovations (2024)
Analysis of Mechanical Properties during Construction Stages Reflecting the Construction Sequence for Long-Span Spatial Steel Structures (2024)
Study on the Influence of the Fully Enclosed Barrier on the Vortex-Induced Vibration Performance of a Long-Span Highway–Railway Double-Deck Truss Bridge (2024)
Research on Intelligent Prefabricated Reinforced Concrete Staircase Lifting Point Setting Method Considering Multidimensional Spatial Constraint Characteristics (2024)
Study on the Influence of Wind Fairing Parameters on the Aerodynamic Performance of Long-Span Double-Deck Steel Truss Suspension Bridge (2024)
Multiobject Real-Time Automatic Detection Method for Production Quality Control of Prefabricated Laminated Slabs (2024)
Conception Design of a Novel Vibration Damping Mechanism for Vibration Reduction of a High-Rise Wind Tower (2023)
Study on the Suppression Effect on Vortex-Induced Vibration of Double-Deck Truss Girder by the Spatial Position of the Deflector Plate (2023)