Qiang Yue | Big Data Analytics | Global Data Innovation Recognition Award

Posted on by ScienceFather

Prof. Qiang Yue | Big Data Analytics | Global Data Innovation Recognition Award

College of Water Conservancy and Civil Engineering, Shandong Agricultural University | China

Publication Profile

Scopus

PROF. QIANG YUE – A LEADER IN BIG DATA ANALYTICS AND WATER CONSERVANCY RESEARCH 🌐💧

INTRODUCTION 🌟

Prof. Qiang Yue is a prominent academic and researcher at the College of Water Conservancy and Civil Engineering, Shandong Agricultural University, China. Specializing in Big Data Analytics, Prof. Yue has contributed significantly to the field of water conservancy and civil engineering, focusing on the integration of data science and engineering for sustainable solutions. His interdisciplinary approach is helping shape the future of water management systems and infrastructure development.

EARLY ACADEMIC PURSUITS 🎓

Prof. Yue’s academic journey began with a strong foundation in civil engineering and water conservancy. After completing his undergraduate degree, he pursued advanced studies in related fields, obtaining a Master’s and PhD with a focus on big data analytics and its applications in civil engineering and water resources management. His rigorous academic training set the stage for his future contributions to both engineering and data science.

PROFESSIONAL ENDEAVORS 💼

As a faculty member at Shandong Agricultural University, Prof. Yue has played a key role in developing research programs and teaching in the fields of water conservancy and civil engineering. His work bridges the gap between traditional engineering methods and modern data analytics, incorporating advanced technologies like machine learning and AI in the optimization of water resources and infrastructure planning. Prof. Yue has also collaborated with national and international research institutions, contributing to various large-scale projects focused on water management and sustainable civil engineering practices.

CONTRIBUTIONS AND RESEARCH FOCUS ON Big Data Analytics 🔬

Prof. Yue’s research interests lie at the intersection of Big Data Analytics and civil engineering, particularly in the optimization of water conservancy systems. His work focuses on the application of machine learning algorithms, predictive analytics, and real-time data collection to improve the efficiency of water resource management, flood control, and infrastructure development. Additionally, his research aims to enhance the sustainability of civil engineering projects through data-driven decision-making, making significant strides toward smart cities and sustainable environmental practices.

IMPACT AND INFLUENCE 🌍

Prof. Yue’s research has had a profound impact on both the academic community and the industry. His innovative use of Big Data Analytics in water conservancy and civil engineering has transformed how data is used in real-time decision-making, helping optimize water resource management on a large scale. His work influences policy decisions, infrastructure development projects, and sustainability strategies, improving water conservation efforts in China and beyond. Prof. Yue has also mentored a generation of engineers and researchers, sharing his knowledge and experience to cultivate future leaders in the field.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Prof. Yue has authored numerous papers in high-impact journals, with a focus on Big Data Analytics and its applications in water management and civil engineering. His publications cover topics such as predictive modeling, real-time water quality monitoring, and optimization of water distribution systems using machine learning. His research is widely cited in the academic community, reflecting the significance of his work in the integration of Big Data with engineering practices.

HONORS & AWARDS 🏆

Prof. Yue’s exceptional contributions to Big Data Analytics and water conservancy have earned him various honors and awards, including:

  • Best Paper Award, International Conference on Water Management and Engineering (2022)
  • Outstanding Researcher Award, Shandong Agricultural University (2021)
  • Excellence in Teaching Award, College of Water Conservancy and Civil Engineering (2020)
  • Innovation in Data Science Award (2019)

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Prof. Yue’s work is paving the way for the next generation of engineers who will rely on data analytics to create sustainable and efficient infrastructure solutions. His future contributions promise to further the development of smart cities, improve water resource management, and enhance the overall resilience of urban environments to climate change. As he continues to innovate and mentor young engineers, his legacy will endure, shaping the future of civil engineering and environmental sustainability.

FINAL NOTE 📌

Prof. Qiang Yue’s career has been defined by his commitment to applying cutting-edge technology to real-world problems in water conservancy and civil engineering. His research is reshaping how engineers and policymakers approach water management and sustainability. His ability to blend Big Data Analytics with traditional engineering disciplines is a testament to his vision for the future of infrastructure and environmental protection.

 TOP NOTES PUBLICATIONS 📚

Dynamic health prediction of plain reservoirs based on deep learning algorithms
    • Authors: Z., Zhu; Zhaohui, H.; Wu, Hao; Z., Zhang, Zhicheng; R., Wang, Rui; Q., Yue, Qiang
    • Journal: Engineering Applications of Artificial Intelligence
    • Year: 2025
Recognition and quantification of apparent damage to concrete structure based on computer vision
    • Authors: J., Liu, Jiageng; H., Sun, Hongyu; Q., Yue, Qiang; Y., Jia, Yanyan; S., Wang, Shaojie
    • Journal: Measurement: Journal of the International Measurement Confederation
    • Year: 2025

Ruihao Zeng | Intelligent Transport Systems | Best Researcher Award

Posted on by ScienceFather

Mr. Ruihao Zeng | Intelligent Transport Systems | Best Researcher Award

The University of Sydney, School of Civil Engineering, Australia

Author Profile

Orcid

Summary 📝

Ruihao Zeng is a Ph.D. candidate in Transportation Engineering at The University of Sydney, specializing in autonomous vehicles and transportation systems. His research focuses on integrating machine learning, data mining, and augmented reality to improve urban mobility, enhance traffic prediction, and explore the interaction between autonomous vehicles and human drivers. With numerous awards under his belt, his work is contributing to pioneering solutions in transportation technology.

Education 🎓

Ruihao Zeng is currently pursuing a Ph.D. in Transportation Engineering at The University of Sydney (2024-2027), where his thesis is titled Automated Etiquette: Societal Norms, Distributed Intelligence, and Prosocial Algorithms for Autonomous Vehicles. He completed an M.Phil. in the same field (2022-2023), focusing on Online Multi-Object Tracking Using LiDAR. Zeng earned his Bachelor of Engineering in Digital Media Technology from Fujian Normal University, China (2018-2022), graduating with a GPA of 85.1, ranking 1st in his class.

Professional Experience 💼

Ruihao Zeng has held various key roles, including Algorithm and Application Developer at The University of Sydney (May-Dec 2023), where he contributed to the development of augmented reality simulations for transportation systems, notably the Lego ARCity project. As a Casual Academic (Feb 2023 – Present), he leads tutorials and provides grading for transport systems courses. Additionally, he completed an IoT Product Development Internship at Xiamen YesSoft Technology Co., Ltd (Jul-Aug 2019), programming hospital monitoring devices using C++ and Arduino.

Academic Cites 📚

Zeng’s research has been showcased at prestigious conferences such as the Transportation Research Board Annual Meeting (2024) and the TRANSW Symposium (2023). His work has gained recognition in the fields of autonomous vehicle systems, urban traffic management, and the application of machine learning in transportation, earning citations from leading scholars.

Technical Skills ⚙️

Ruihao Zeng’s technical expertise is a key strength in his research. He is proficient in programming languages such as Python, MATLAB, and C++, and skilled in frameworks and tools including Keras, PyTorch, and TensorFlow for deep learning. His specializations include LiDAR-based tracking, machine learning algorithms, and the application of augmented reality to transportation solutions.

Teaching Experience 👩‍🏫

As a Casual Academic at The University of Sydney, Zeng has gained valuable teaching experience, leading tutorials and grading for courses related to transport systems. His role allows him to engage students with complex technical concepts and guide them in applying their learning to real-world transportation challenges.

Research Interests 🔬

Ruihao Zeng’s research interests are centered around autonomous vehicles, machine learning, and the development of smart cities. His work explores the use of prosocial algorithms and etiquette in human-vehicle interactions, applies machine learning algorithms to traffic prediction and urban mobility optimization, and investigates data-driven solutions for enhancing traffic systems and promoting sustainable urban development.

Top Noted Publications 📖

Huike Zeng | Smart Cities and Urban Analytics | Best Researcher Award

Posted on by ScienceFather

Mr. Huike Zeng | Smart Cities and Urban Analytics | Best Researcher Award

Mr. Huike Zeng at Shandong university, China

👨‍🎓 Profile

📝 Summary

Zeng Huike is a dedicated Ph.D. candidate in Geotechnical Engineering at Shandong University, focusing on transportation engineering, particularly in non-destructive testing and vibration control for railway infrastructure.

🎓 Education

  • B.S. in Transportation Engineering (2015-2019) from East China Jiaotong University, China
  • M.A.Sc. in Transportation Engineering (2019-2022) from Shenzhen University, China
  • Ph.D. Candidate in Geotechnical Engineering (2022-present) at Shandong University, China

💼 Professional Experience

Developed innovative phononic crystal floating slab tracks and TID-vibration-isolator systems aimed at effective vibration reduction. Established a multi-frequency data fusion method using the Non-Subsampled Contourlet Transform (NSCT) for ground penetrating radar (GPR) applications in railway infrastructure testing.

🔍 Research Interests

Dynamic soil-structure interaction, non-destructive testing, ground penetrating radar, vibration and noise control, deep learning, and predictive methods are the key areas of exploration.

🏆 Awards

  • National Scholarship, Ministry of Education of China (2021)
  • SZU Outstanding Graduate Award, Shenzhen University (2022)
  • Academic Excellence Scholarship, Shandong University (2023)
📖  Top Noted Publications

Article Title: Study on Low-Frequency Vibration Mitigation Characteristics of TID-Vibration-Isolator Floating Slab Track

  • Authors: Sheng, X.; Zeng, H.-K.; Shi, C.; Zhang, Y.; Du, Y.-L.
    Journal: Gongcheng Lixue / Engineering Mechanics
    Volume: 40
    Issue: 5
    Pages: 49–58
    Year: 2023

Article Title: A Study on Low-Frequency Vibration-Mitigation Performance of a Phononic Crystal Floating Slab Track

  • Authors: Sheng, X.; Zeng, H.; Shi, C.; Du, Y.
    Journal: Zhendong yu Chongji / Journal of Vibration and Shock
    Volume: 41
    Issue: 12
    Year: 2022

Article Title: Numerical Study on Propagative Waves in a Periodically Supported Rail Using Periodic Structure Theory

  • Authors: Sheng, X.; Zeng, H.; Zhang, S.Y.; Wang, P.
    Journal: Journal of Advanced Transportation
    Volume: 2021
    Pages: 6635198
    Year: 2021

Jing Wang | Smart Cities and Urban Analytics | Best Researcher Award

Posted on by ScienceFather

Mr. Jing Wang | Smart Cities and Urban Analytics | Best Researcher Award

Mr. Jing Wang at Shandong University, China

👨‍🎓 Profiles

Scopus Profile

Orcid Profile

Research Gate Profile

📝 Summary

Dr. Jing Wang is the Director of the Research Centre for New Structures in Railway Transportation at Shandong University. With extensive expertise in geotechnical engineering, particularly in shield intelligent tunneling, Dr. Wang has led over 40 significant projects and contributed to more than 134 academic publications.

🎓 Education

Dr. Wang holds a PhD in Geotechnical Engineering from Shandong University, where they also completed joint PhD training at Durham University.

👔 Professional Experience

Currently, Dr. Wang serves as the Director of the Research Centre for New Structures in Railway Transportation at Shandong University. Additionally, they hold editorial positions in several prestigious journals related to tunneling and engineering.

🔬 Research Interests

Dr. Wang’s research focuses on high-end intelligent shield technology, aiming to enhance tunneling processes, as well as green and safe construction methods to promote sustainability in railway transportation.

📖  Top Noted Publications

3D imaging and temporal evolution recognition of concrete internal defects based on GPR

    • Authors: Wang, Z., Li, B., Lei, M., Wang, J., Sui, Q.
    • Journal: Measurement Science and Technology
    • Year: 2024

Deep Learning-Based Three-dimensional Reconstruction and Spatial Position Mapping of Tunnel Defect Zones

    • Authors: Wang, J., Wang, W., Xu, P., Xiao, G., Wang, Z.
    • Journal: ACM International Conference Proceeding Series
    • Year: 2024

Linear Deformation Sensing and Error Self Correction Method Based on Fiber Optic Smart Sensor Belt and Typical Error Matching

    • Authors: Wang, Z., Li, W., Zhou, X., Cui, J., Wang, J.
    • Journal: ACM International Conference Proceeding Series
    • Year: 2024

Dam Seepage Defect Area Estimation Method Based on UAV 3D Scene Reconstruction

    • Authors: Gao, S., Gao, S., Yang, Y., Yu, Y., Wang, J.
    • Journal: ACM International Conference Proceeding Series
    • Year: 2024

Development of similar materials with different tension-compression ratios and evaluation of TBM excavation

    • Authors: Wang, J., Zhang, Y., Wang, K., Cheng, S., Sun, S.
    • Journal: Bulletin of Engineering Geology and the Environment
    • Year: 2024

Review on Vibration Monitoring and Its Application during Shield Tunnel Construction Period

    • Authors: Yang, W., Fang, Z., Wang, J., Zhang, Y., Ba, X.
    • Journal: Buildings
    • Year: 2024

Menno Buisman | Smart Cities and Urban Analytics | Best Researcher Award

Posted on by ScienceFather

Mr. Menno Buisman | Smart Cities and Urban Analytics | Best Researcher Award

Mr. Menno Buisman at Delft University of Technology, Netherlands

 Profile

Google Scholar Profile

👨‍⚕️ Academic Background

Menno Buisman is a dedicated geophysicist specializing in distributed acoustic sensing (DAS) for sediment monitoring and infrastructure health. He is passionate about physics and geoscience and has extensive experience conducting experiments, performing data analysis, and applying cutting-edge techniques. Menno is also a dance enthusiast who enjoys giving salsa and bachata classes in his spare time.

🎓 Education

iPhD Candidate in Geophysics (2020 – expected 2024)
Delft University of Technology, The Netherlands
Thesis: “Monitoring the Water Depth in Ports and Waterways Using Distributed Acoustic Sensing.”
Supervisor: Dr. D. Draganov

Joint M.Sc. in Applied Geophysics (2017 – 2019)
Delft University of Technology, ETH Zürich, RWTH Aachen University, The Netherlands, Switzerland, and Germany
Thesis: “Seismic Analysis of Fluid Mud: Detection of Shear Parameters in Fluid Mud and the Relation Between Seismic Velocities and Yield Stresses.”

B.Sc. in Earth Sciences and Economics (2014 – 2017)
Free University, Amsterdam, The Netherlands
Thesis: “A Post Cost-Benefit Analysis of Sand Nourishment on the Walcheren Coastline.”

Pre-Science Education (2008 – 2014)
Groen van Prinstererlyceum Lentiz, Vlaardingen University
Concentration: Economy and Society

💼 Professional Experience

TenneT, Arnhem
February 2024 – Present

Develop new monitoring techniques for high voltage soil coverage and partial discharges.

Conduct pilots and surveys focused on offshore windmill park cables’ integrity.

Municipality of Rotterdam, Rotterdam
January 2024 – Present

Develop innovative monitoring techniques for infrastructure health using DAS.

Lead pilots and apply advanced techniques to continuously monitor infrastructure health using optical fibers.

iPhD Candidate, Port of Rotterdam, Rotterdam
December 2019 – December 2023

Develop monitoring techniques for nautical depth in ports and waterways.

Lead pilot projects and market analysis for DAS interrogator acquisition.

Research Intern, Port of Rotterdam, Rotterdam
April 2019 – August 2019

Conduct experiments on shear stresses and wave velocities in fluid mud.

Research Internship, Port of Rotterdam, Rotterdam
August 2018 – September 2018

Acquire and interpret acoustic data for fluid mud behavior analysis.

Research Internship, Deltares, Delft
June 2017 – August 2017

Create an ex-post analysis of sand nourishment on the Walcheren coastline.

Shop Assistant, Praxis, Vlaardingen
October 2014 – January 2018

Restock shelves and assist customers.

🔬 Research Interests

Menno Buisman’s research interests lie at the intersection of geophysics and advanced sensing technologies. He is particularly focused on the application of distributed acoustic sensing (DAS) for monitoring sediment dynamics and infrastructure health. Menno is dedicated to developing innovative techniques for real-time monitoring of water depths in ports and waterways, utilizing DAS to enhance the accuracy and efficiency of sediment monitoring. His work also explores the use of seismic data processing to understand fluid mud dynamics and their impact on marine and coastal environments. Menno is passionate about leveraging state-of-the-art technologies to address complex geophysical challenges, with a keen interest in the integration of DAS with existing infrastructure to improve maintenance and safety protocols. Additionally, his research extends to the study of acoustic wave propagation and its applications in geoscience, aiming to advance the field through experimental and theoretical approaches.

Awards

Best Conference Paper, Metrosea2023, IEEE 2023

📖 Publication

Continuous monitoring of the depth of the water-mud interface using distributed acoustic sensing

Authors: M. Buisman, E. Martuganova, T. Kiers, D. Draganov, A. Kirichek

Journal: Journal of Soils and Sediments

Year: 2022

Monitoring water column and sediments using DAS

Author: M. Buisman

Conference: 2023 IEEE International Workshop on Metrology for the Sea; Learning to …

Year: 2023

Monitoring tidal water-column changes in ports using distributed acoustic sensing

Authors: M. Buisman, D. Draganov, A. Kirichek

Conference: 84th EAGE Annual Conference & Exhibition 2023

Year: 2023

Water-depth estimation using propeller noise by distributed acoustic sensing

Authors: M. Buisman, E. Martuganova, A. Kirichek, D. Draganov

Conference: 83rd EAGE Annual Conference & Exhibition 2022

Year: 2022

Monitoring settling and consolidation of fluid mud in a laboratory using ultrasonic measurements

Authors: I. Fadel, A. Kirichek, M. Buisman, K. Heller, D. Draganov

Conference: NSG2021 27th European Meeting of Environmental and Engineering Geophysics

Year: 2021