Prof. Dr. Lei Geng | Data Analysis | Best Researcher Award

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Prof. Dr. Lei Geng | Data Analysis | Best Researcher Award

Prof. Dr. Lei Geng, Tiangong University, China

Prof. Dr. Lei Geng is a distinguished professor at the School of Life Sciences, Tiangong University, with a focus on computer vision, machine learning, and measurement technology. He received his Ph.D. in 2012 from Tianjin University and has since made significant contributions to the fields of AI, machine vision, and medical technology. With over 80 published papers, Dr. Geng has played a pivotal role in the development of advanced imaging and measurement technologies for industrial and medical applications. His research includes applications in image analysis, 3D dimensional measurement, and hemostatic medical equipment. As a leader in his field, he has led more than 10 national and provincial-level projects and received numerous awards for his technological innovations. 🚀

Professional Profile:

Scopus
Orcid

Suitability for the Award

Prof. Dr. Lei Geng is highly suitable for the Best Researcher Award due to his groundbreaking work in AI, machine vision, and medical technology. His research has led to the development of advanced image analysis techniques and high-precision measurement tools, with far-reaching implications for both industrial and healthcare applications. Dr. Geng’s leadership in national and provincial projects, combined with his three provincial-level awards, highlights his ability to drive technological advancements that have a direct impact on society. His contributions to AI-based diagnostics, particularly in otolaryngology, underscore his dedication to improving healthcare through cutting-edge technologies. Prof. Geng’s consistent excellence in research, innovation, and application makes him an ideal candidate for this prestigious award. 🏅

Education

🎓 Dr. Lei Geng earned his Ph.D. in 2012 from Tianjin University, specializing in areas at the intersection of computer vision, machine learning, and measurement technology. His academic journey laid the foundation for his extensive contributions to these fields, including the development of cutting-edge applications in industrial and medical sectors. Dr. Geng’s deep understanding of both theoretical and practical aspects of machine vision and artificial intelligence has made him an expert in creating innovative solutions across multiple industries. His education has fueled his ongoing research and contributions to advancements in AI-driven healthcare and precision measurement technologies. 📘

Experience

🧑‍🏫 Prof. Dr. Lei Geng has extensive teaching and research experience, currently serving as a professor at the School of Life Sciences at Tiangong University. He has been involved in both undergraduate and postgraduate education, teaching courses such as Machine Vision and Deep Learning. Over his career, Dr. Geng has undertaken more than 10 national, provincial, and ministerial-level projects, focusing on industrial and medical applications of machine vision and AI. His experience includes pioneering work in hemostatic medical equipment and high-precision 2D/3D measurement systems. This broad range of expertise positions Dr. Geng as a leader in his field, particularly in the integration of AI technologies with practical, real-world applications. 🌍

Awards and Honors

🏅 Dr. Lei Geng’s excellence in research and technological innovation has been recognized through several prestigious awards. He has received three provincial-level awards, including the Tianjin Second Prize for Technological Invention and the Special Prize of the National Award for Business Science and Technology Progress. These accolades are a testament to his significant contributions to the fields of AI, computer vision, and medical technology. Dr. Geng’s ability to bridge the gap between advanced scientific research and practical applications in industries such as healthcare and manufacturing has made him a highly respected figure in the scientific community. 🌟

Research Focus

🔬 Dr. Lei Geng’s research focuses on four key areas:

  1. Image Analysis & Understanding: Developing AI-based systems for image classification, object detection, and segmentation for industrial and medical applications.
  2. Dimensional Measurement: Applying machine vision and 3D scanning technology for high-precision industrial measurement and target positioning.
  3. Hemostatic Medical Equipment: Innovating in extracorporeal compression and intravascular interventional devices for medical bleeding control.
  4. AI in Otorhinolaryngology: Applying deep learning for disease diagnosis in ear, nose, and throat (ENT) medicine.

His work in these areas aims to integrate AI and machine vision to solve real-world problems, particularly in medical diagnostics and industrial automation. 💡

Publication Top Notes:

  • Direct May Not Be the Best: An Incremental Evolution View of Pose Generation
    • Year: 2024
    • Citations: 1
  • Multi-parametric investigations on the effects of vascular disrupting agents based on a platform of chorioallantoic membrane of chick embryos
    • Year: 2024
  • Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification
    • Year: 2024
  • Cross-scale contrastive triplet networks for graph representation learning
    • Year: 2024
    • Citations: 4
  • Objective rating method for fabric pilling based on LSNet network
    • Year: 2024
    • Citations: 3

Prof. Wan Quan Liu | Big Data Analysis | Best Researcher Award

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Prof. Wan Quan Liu | Big Data Analysis | Best Researcher Award

Prof. Wan Quan Liu, Sun Yat-sen University, China

Prof. Wan Quan Liu is a prominent professor at the School of Intelligent System Engineering at Sun Yat-sen University, where he has been serving since 2021. He earned his Ph.D. in Electrical Engineering from Shanghai Jiaotong University (1991-1993) and holds a Master of Science in Operational Research and Control from the Institute of Systems Science at the Chinese Academy of Science (1985-1988), as well as a Bachelor’s degree in Mathematics from Qufu Normal University (1981-1985). Previously, he was an ARC Fellow and Senior Lecturer at Curtin University of Technology from 2000 to 2021. Prof. Liu’s research focuses on computer vision, deep learning networks, optimization, and intelligent control systems, where he has made significant contributions that advance these fields.

Professional Profile

Scopus
Orcid

Suitability for the Best Researcher Award:

Prof. Wan Quan Liu’s combination of an extensive educational background, significant research contributions, and recognition in the form of awards makes him an excellent candidate for the Best Researcher Award. His work in computer vision, deep learning, and intelligent control systems is highly relevant in today’s technology-driven landscape, with implications for various sectors including robotics, automation, and artificial intelligence.

The recognition he has received, both at the national and provincial levels, further solidifies his status as a leading researcher in his field. His ongoing research and publications contribute to advancements in critical technologies, making a tangible impact on both academia and industry.

Educational Background:

Prof. Wan Quan Liu earned his PhD in Electrical Engineering from Shanghai Jiaotong University (1991-1993). He holds a Master of Science in Operational Research and Control from the Institute of Systems Science at the Chinese Academy of Science (1985-1988) and a Bachelor’s degree in Mathematics from Qufu Normal University (1981-1985).

Academic Experience:

Currently, Prof. Liu is a professor at the School of Intelligent System Engineering at Sun Yat-sen University (2021-present). Prior to this, he held various positions, including ARC Fellow and Senior Lecturer at Curtin University of Technology (2000-2021).

Research Interests:

Prof. Liu specializes in computer vision, deep learning networks, optimization, and intelligent control systems, contributing significantly to advancements in these fields.

Awards and Recognition:

His exceptional work has earned him several accolades, including:

  • 2023: National Talented Researcher from the National Education Committee
  • 2022: Pearl Leading Researcher from Guangdong Province

Publication Top Notes:

  • Title: AFS-FCM with Memory: A Model for Air Quality Multi-dimensional Prediction with Interpretability
    • Publication Year: 2024
  • Title: Efficient and Fast Joint Sparse Constrained Canonical Correlation Analysis for Fault Detection
    • Publication Year: 2024
  • Title: Efficient and Robust Sparse Linear Discriminant Analysis for Data Classification
    • Publication Year: 2024
  • Title: FedREM: Guided Federated Learning in the Presence of Dynamic Device Unpredictability
    • Publication Year: 2024
  • Title: Invertible Residual Blocks in Deep Learning Networks
    • Publication Year: 2024

 

Mrs. Marta Zorrilla | Big data Award | Best Researcher Award

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Mrs. Marta Zorrilla | Big data Award | Best Researcher Award

Mrs. Marta Zorrilla, University of cantabria, Spain

Mrs. Marta Zorrilla is a distinguished academic with a Ph.D. in Telecommunication Engineering from Universidad de Cantabria, Spain, complemented by a Bachelor’s and Master’s in the same field. With an H-Index of 10 on Web of Science and 19 on Google Scholar, and 1232 citations, her research has significantly impacted Learning Analytics, Educational Data Mining, and Big Data Technologies. She has developed frameworks for MOOCs, a reference architecture for Big Data, and leads a national R&D project on data stream mining for Industry 4.0. Mrs. Zorrilla has held various teaching and management roles, including Vice-Dean and Director of the Teaching Staff Area at Universidad de Cantabria. She is also a key member of the Software Engineering and Real-Time Group (ISTR), contributing to software engineering, real-time systems, and data science.

🌍 Professional Profile

Orcid

Suitability for the Best Researcher Award

  1. Academic and Research Impact: Mrs. Zorrilla’s research contributions in document databases, learning analytics, big data technologies, and data governance have had a significant impact. Her high citation count and substantial H-index reflect the influence and recognition of her work.
  2. Innovative Contributions: Her pioneering work in developing frameworks for data governance and learning analytics, as well as her contributions to big data technologies, demonstrate innovation and practical applications in critical areas of technology and industry.
  3. Leadership and Mentorship: Mrs. Zorrilla has played a key role in mentoring PhD researchers and has been involved in numerous national and European research projects. Her leadership in these areas highlights her commitment to advancing research and supporting the next generation of scholars.
  4. Teaching Excellence: Her long-standing teaching role and management positions at Universidad de Cantabria showcase her dedication to education and academic administration, further enhancing her profile as a distinguished researcher.
  5. Proven Track Record: Her extensive list of publications, including articles in high-impact journals, and her role in major research projects demonstrate a robust and successful research career.

Academic Qualifications:

She holds a Bachelor in Telecommunication Engineering, a Master in Telecommunication, and a PhD in Telecommunication Engineering, all from Universidad de Cantabria, Spain. 🎓

Research Indicators:

With an H-Index of 10 (Web of Science) and 19 (Google Scholar), and 1232 citations, Mrs. Zorrilla has made substantial contributions to her field. She has 5 Quinquenios and 2 Sexenios. 📈

Research Achievements:

Her early career saw the development of a neural network engine and the founding of Predictia. She has made significant contributions to Learning Analytics and Educational Data Mining, including frameworks for MOOCs and a European project. Her work in Big Data Technologies includes a reference architecture and benchmarks for technology configuration. She has also developed a data governance framework and is the Principal Investigator for a national R&D project on data stream mining for Industry 4.0. 📊

Teaching and Management Roles:

Mrs. Zorrilla has extensive teaching experience in database technologies and data management. She has held management roles including Vice-dean, head of studies, and Director of the Teaching Staff Area at Universidad de Cantabria. 👩‍🏫

Research Group CV Summary:

She is active in the Software Engineering and Real-Time Group (ISTR), focusing on software engineering, real-time systems, databases, and data science, contributing to numerous projects and publications. 🛠️

Publication Top Notes:

  • Title: Fleet Management Systems in Logistics 4.0 Era: A Real-Time Distributed and Scalable Architectural Proposal
    • Year: 2023
  • Title: An I4.0 Data Intensive Platform Suitable for the Deployment of Machine Learning Models: A Predictive Maintenance Service Case Study
    • Year: 2022
  • Title: A Reference Framework for the Implementation of Data Governance Systems for Industry 4.0
    • Year: 2022
  • Title: A Big Data-Centric Architecture Metamodel for Industry 4.0
    • Year: 2021
  • Title: A Data Governance Framework for Industry 4.0
    • Year: 2021

 

 

Prof. Jianfeng Guo | Big Data Analysis in Innovation | Best Researcher Award

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Prof. Jianfeng Guo | Big Data Analysis in Innovation | Best Researcher Award

Prof. Jianfeng Guo, University of Chinese Academy of Sciences, China

Prof. Jianfeng Guo is a distinguished professor at the Energy and Environmental Policy Research Center of the Institute of Policy and Management, Chinese Academy of Sciences (CAS), where he has been a key figure since 2010 and has served as a professor since 2018. He earned his Ph.D. in Mechanical Engineering and Automation from Zhejiang University in 2007 and completed postdoctoral research at Tsinghua University. Jianfeng’s research spans Energy and Environmental Policy, Big Data Analysis, Technology Foresight, Decision Support Systems, and Knowledge Management. He has led over 60 significant projects, including collaborations with Baidu Big Data Lab and Ant Financial Services Group, and has published more than 90 papers and holds multiple patents and software copyrights. His international experience includes visits to top institutions and collaborations with global software companies.

🌍 Professional Profile

Scopus

🎓 Education

Jianfeng Guo earned his Ph.D. in Mechanical Engineering and Automation from Zhejiang University in December 2007. He completed postdoctoral research at the CIMS Engineering Research Center of Tsinghua University from January 2008 to December 2009. He was a Senior Visiting Scholar at NEC China Research Institute from August 2009 to March 2010.

🔬 Research Interests

Jianfeng specializes in Energy and Environmental Policy, Big Data Analysis, Technology Foresight, Decision Support Systems, and Knowledge Management.

🏢 Current Position

Since March 2010, Jianfeng has been with the Energy and Environmental Policy Research Center of the Institute of Policy and Management, Chinese Academy of Sciences (CAS), where he has served as a professor since 2018. He is also the Director of the Research Department for Think Tank Construction at the Institutes of Science and Development, CAS.

🌐 Notable Projects & Collaborations

Jianfeng has led over 60 projects, including NSFC projects, national programs, and enterprise-commissioned projects. He has collaborated with Baidu Big Data Lab and Ant Financial Services Group, contributing to advancements in big data and financial security.

📝 Publications & Patents

He has published more than 90 papers, including over 60 in international journals, and holds 4 invention patents and 15 computer software copyrights.

🌍 International Experience

Jianfeng has visited prestigious institutions such as the University of Oldenburg, Imperial College, and Cambridge University, and worked with international software companies like ASCORA and TIE.

Publication Top Notes:

  • Title: Graph-based algorithm for exploring collaboration mechanisms and hidden patterns among top scholars
    • Cited by: 1
    • Year: 2024
  • Title: A framework of cloud-edge collaborated digital twin for flexible job shop scheduling with conflict-free routing
    • Cited by: 3
    • Year: 2024
  • Title: Simulation research on the evolution pathway planning of energy supply and demand in China under the dual carbon targets
    • Cited by: 2
    • Year: 2023
  • Title: Electric vehicle adoption and local PM2.5 reduction: Evidence from China
    • Cited by: 7
    • Year: 2023
  • Title: Pathways for municipalities to achieve carbon emission peak and carbon neutrality: A study based on the LEAP model
    • Cited by: 53
    • Year: 2023

 

 

 

Dr. Luigi De Simio | Big Data Analysis | Excellence in Research

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Dr. Luigi De Simio | Big Data Analysis | Excellence in Research

Dr. Luigi De Simio, Consiglio Nazionale delle Ricerche, Italy

👨‍🔬 Dr. Luigi De Simio, born on 11/22/1978 in Benevento, Italy, is a distinguished researcher at the Institute of Sciences and Technologies for Sustainable Energy and Mobility (STEMS) of the National Research Council. He earned his Master’s and PhD degrees in Mechanical Engineering from the University of Naples Federico II. With expertise in alternative propulsion systems, he focuses on optimizing internal combustion engines with hydrogen-based fuels and hybrid solutions. Dr. De Simio has authored over 50 technical papers and holds a European patent for a thermal-electric hybrid propulsion system. He has contributed significantly to national projects like GREEN POWERTRAIN and TRIM, as well as international endeavors such as MhyBus and BEAUTY. His dedication to sustainable energy solutions has earned him recognition as a reviewer for top journals and an evaluator for projects funded by the Italian Ministry of Economic Development. 🌱🔧📚

🌐 Professional Profiles :

Scopus

Orcid

Google Scholar

🎓 Education:

Dr. Luigi De Simio is a distinguished scholar 🎓 whose academic journey has been marked by a relentless pursuit of excellence in mechanical engineering. Graduating with a Master’s degree from the prestigious University of Naples Federico II in 2006, he swiftly ascended to the realm of doctoral studies, obtaining his PhD in the same discipline in 2010. 🚀 With a foundation built upon rigorous scholarship and a passion for innovation, Dr. De Simio continues to illuminate the field with his expertise and dedication. 🌟

💼 Work:

Dr. Luigi De Simio embarked on an illustrious journey in the realm of research following his doctoral studies, undertaking impactful postdoctoral work at CNR from 2010 to 2012. 🌟 His dedication and expertise led him to transition into a full-time researcher role at CNR, where he continues to push the boundaries of knowledge in his field with unwavering determination and passion. 🔬 Dr. De Simio’s contributions stand as a testament to his commitment to advancing scientific understanding and driving innovation forward. 🚀

📝 Achievements:

Dr. Hamin Chong’s career is adorned with remarkable achievements, including the publication of over 50 technical papers, which stand as a testament to his scholarly prowess and contributions to the field of mechanical engineering 📄. Notably, his ingenuity has been recognized with the granting of a European patent in 2021 for a groundbreaking thermal-electric hybrid propulsion system, underscoring his innovative spirit and commitment to advancing sustainable technologies 🌱🚀. Dr. Chong’s achievements serve as inspiration for aspiring engineers and researchers worldwide, reflecting his unwavering dedication to driving impactful change through cutting-edge research and development.

🧠Research Interests :

Dr. Luigi De Simio’s remarkable career is adorned with numerous achievements that underscore his profound impact in the field of mechanical engineering. With a prolific output, he has authored over 50 technical papers, cementing his reputation as a leading scholar in his domain. 📄 Furthermore, his innovative spirit and groundbreaking research culminated in the granting of a European patent in 2021 for his pioneering work on a thermal-electric hybrid propulsion system, marking a significant milestone in sustainable transportation technology. 🌍⚡ Dr. De Simio’s contributions continue to shape the landscape of engineering and inspire future generations of innovators. 🌟

📚 Publication Impact and Citations :

Scopus Metrics:

  • 📝 Publications: 31 documents indexed in Scopus.
  • 📊 Citations: A total of 402 citations for his publications, reflecting the widespread impact and recognition of Dr. Luigi De Simio’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 578 📖
    • h-index: 10 📊
    • i10-index: 11 🔍
  • Since 2018:
    • Citations: 300 📖
    • h-index: 8 📊
    • i10-index: 7 🔍

👨‍🏫 A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. 🌐🔬

Publications Top Notes  :

1.  Combustion efficiency and engine out emissions of a SI engine fueled with alcohol/gasoline blends

Published  Year – 2013, Published in Applied Energy, cited by 206 articles.

2.  Numerical simulation and experimental test of dual fuel operated diesel engines

Published  Year – 2014, Published in Applied Thermal Engineering, cited by 93 articles.

3.  A numerical and experimental study of dual fuel diesel engine for different injection timings

Published  Year – 2016, Published in Applied Thermal Engineering, cited by 50 articles.

4.  Combined numerical-experimental study of dual fuel diesel engine

Published  Year – 2014, Published in Energy Procedia, cited by 43 articles.

5.  Possible transport energy sources for the future

Published  Year – 2013,  Published in Transport Policy, cited by 27 articles.

 

 

 

 

 

Mr. Hamin Chong | Big Data Analysis | Best Researcher Award

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Mr. Hamin Chong | Big Data Analysis | Best Researcher Award

Mr. Hamin Chong, Ls Mtron, South Korea

Mr. Hamin Chong is a skilled computer vision expert with a master’s degree in Industrial Data Engineering from Hanyang University. Currently serving as a Research Engineer at LS Mtron, a major player in agricultural machinery manufacturing, he specializes in AI-based technology research and system development. Hamin has excelled in developing anomaly detection and object detection models, contributing to quality improvement in manufacturing processes. His innovative work includes creating a real-time leakage inspection support system and a lightweight engine exterior inspection model, showcasing his ability to enhance model accuracy with limited data. With a background in mechanical engineering and experience at the Advanced Manufacturing Laboratory, Hamin is dedicated to smart manufacturing systems and has actively contributed to standardizing data in continuous process industries. His expertise extends to unsupervised and integrated ensemble learning algorithms for anomaly detection, as evidenced by publications and patents. Proficient in Python, SQL, and Tableau, Hamin is a dynamic professional who continually seeks to bridge the evolving boundaries between natural language processing and computer vision.

🌐 Professional Profiles :

Scopus

🛠️ Experience:

  1. LS Mtron (Research Engineer)
    • AI-based technology research and system development.
    • Real-time leakage inspection support system with a high accuracy model (f1 score: 0.92).
    • Development of lightweight engine exterior inspection model with a 90% size reduction.
  2. Advanced Manufacturing Laboratory
    • Smart manufacturing systems developer contributing to industry competitiveness.
    • Standardization of shared data in continuous process industries.
    • Development of unsupervised and integrated ensemble learning-based automatic labeling and anomaly detection algorithm.

📚 Education:

  • Master’s degree in Industrial Data Engineering, Hanyang University.
  • Bachelor’s degree in Mechanical Engineering, Sungkyunkwan University.

📝 Paper & Patent:

  • Method for detecting welding defects and learning method for detecting welding defects (2022).
  • Data-fused and concatenated-ensemble learning for in-situ anomaly detection in wire and arc-based direct energy deposition, Journal of Manufacturing Processes (2024).

🚀 Skills:

  • Language: Python, SQL.
  • Big Data Analyst, Data Analysis Associate, SQL Developer.
  • BI: Tableau (Training Completion: Oct-Nov 2023).

🧠Research Interests :

Hamin Chong is a visionary computer vision expert with a fervent interest in transforming data landscapes. 🌐 Armed with a master’s degree in Industrial Data Engineering, he excels in developing innovative solutions for anomaly detection and object recognition. As a Research Engineer at LS Mtron, he played a pivotal role in AI-based technology research, enhancing manufacturing processes through real-time leakage inspection support systems and lightweight engine exterior inspection models. Hamin’s journey extends to the Advanced Manufacturing Laboratory, where he contributed to standardizing shared data in continuous process industries and pioneered unsupervised ensemble learning for automatic labeling and anomaly detection. 🚀 With a robust skill set in Python, SQL, and Tableau, he embraces challenges in Big Data Analysis, embodying a commitment to shaping the future of smart factories. 📊✨

Publications Top Notes  :

Title: Data-fused and concatenated-ensemble learning for in-situ anomaly detection in wire and arc-based direct energy deposition

Authors: Kim, D.B., Chong, H., Mahdi, M.M., Shin, S.-J.

Published Year: 2024

Journal: Journal of Manufacturing Processes

 

 

 

 

Mr. Jiajun Pang | Big Data Analysis | Best Researcher Award

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Mr. Jiajun Pang | Big Data Analysis | Best Researcher Award

Mr. Jiajun Pang, University at Buffalo, United States

🎓 Mr. Jiajun Pang is an avid academician currently pursuing his Ph.D. in Transportation Engineering at the University at Buffalo, SUNY, expected to complete in July 2025. Holding a Master’s degree in Transportation Engineering from Beijing University of Technology (June 2019) and a Bachelor’s degree from the same institution (June 2016), his educational journey showcases a profound commitment to advancing knowledge in the field. 🚗🚦 As a Research Assistant in the Transportation Research Lab since February 2020, Jiajun applies his expertise to delve into winter traffic safety intricacies, contributing to the analysis of the autonomous vehicles market and exploring the impacts of the Winter Intelligent Road Information System. His diverse research spans from game theory in global maritime transportation to driving simulation data for tourism sign effectiveness evaluation. 🚗📊 Jiajun’s dynamic role illuminates his dedication to unraveling transportation dynamics, and his research interests in Big Data Analysis and Traffic Safety promise innovative contributions to data-driven decision-making in the realm of transportation. 🧠🚗✨

🎓 Education : 

🎓 Mr. Jiajun Pang is on an academic journey, currently pursuing his Ph.D. in Transportation Engineering at the University at Buffalo, SUNY, with an expected completion date in July 2025. His passion for the field is evident in his previous academic achievements, holding a Master’s degree in Transportation Engineering from Beijing University of Technology (June 2019) and a Bachelor’s degree in the same discipline from the same institution (June 2016). Jiajun’s commitment to advancing his knowledge in transportation engineering showcases a trajectory of academic excellence and dedication to the field of study. 🚗🚦

🌐 Professional Profiles : 

ORCID

Scopus

🔍 Experience :

✨ Mr. Jiajun Pang brings valuable expertise as a Research Assistant in the Transportation Research Lab within the Civil, Structural, and Environmental Engineering domain since February 2020. His dynamic role involves delving into the intricacies of winter traffic safety through the application of the random parameter hazard duration model. Jiajun also contributes to the analysis of the autonomous vehicles market, employing the random parameter ordered probit model. His innovative contributions extend to designing and exploring the potential impacts of the Winter Intelligent Road Information System on winter travel. Using paired t-tests on data from self-designed stated preference surveys, he investigates travel behaviors in winter weather. Additionally, Jiajun applies game theory to model the competition in global maritime transportation and utilizes driving simulation data to evaluate the effectiveness of tourism signs. His diverse skill set and research pursuits illuminate his dedication to advancing the understanding of transportation dynamics. 🚗📊

🧠 Research Interests 🔬🌐 :

🔍 Mr. Jiajun Pang’s research interests form a compelling intersection of Big Data Analysis and Traffic Safety. His academic pursuits reflect a commitment to unraveling insights from vast datasets, contributing to the realm of data-driven decision-making. 📊 Passionate about enhancing transportation systems, Jiajun focuses on leveraging big data to analyze and improve traffic safety. His research endeavors promise to bring innovative solutions to the dynamic landscape of transportation, ensuring safer and more efficient journeys for all. 🚗✨

Citations : 

Scopus Metrics:

  • 📝 Publications: 3 documents indexed in Scopus.
  • 📊 Citations: A total of 26 citations for his publications, reflecting the widespread impact and recognition of Mr. Jiajun Pang’s research within the academic community.

Publications Top Notes  :

1.  A temporal instability analysis of environmental factors affecting accident occurrences during snow events: The random parameters hazard-based duration model with means and variances heterogeneity

Journal: Analytic Methods in Accident Research, 2022, 34, 100215

Cited by: 22

2.  Semi-buspool: Demand-driven Scheduling for Intercity Bus Based on Smart Card Data

Conference: 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, pp. 752–757, 2019

3.  Road Network Capacity Based on the Time-Space Consumption and the Traffic Operation Efficiency Theory 

Journal: Journal of Beijing University of Technology, 2019, 45(9), pp. 895–903

Cited by: 4