Dr. JOONSOO KIM | Digital Transformation | Best Researcher Award

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Dr. JOONSOO KIM | Digital Transformation | Best Researcher Award

Postdoctoral Researcher, Korea Institute of Construction Technology (KICT), South Korea.

Dr. Joon-Soo Kim is an innovative and skilled researcher in Construction Management, with a strong command of advanced data analytics, machine learning, and environmental sustainability. His academic and research work uniquely integrates engineering with cutting-edge technologies such as text mining and big data to enhance construction safety and efficiency. Currently serving as a Postdoctoral Researcher at the Korea Institute of Civil Engineering and Building Technology (KICT), Dr. Kim is highly regarded for developing reliable decision-making models tailored to complex engineering challenges. His expertise spans from eco-friendly engineering solutions to smart waste management systems, making him a vital contributor to sustainable civil engineering research. 🏗️📊🌿

Publication Profile

Scopus

🎓 Education Background

Dr. Kim earned his Ph.D. in Construction Environment and Energy Engineering from Kyungpook National University, where his dissertation explored road construction environmental load and cost estimation using machine learning. He also holds a Master’s in Construction Systems Engineering with a specialization in Geotechnical and Road Engineering, and a Bachelor’s degree in Civil Engineering—all from the same university. His academic path reflects a strong commitment to applying data-driven insights to real-world infrastructure problems. 🎓📚

💼 Professional Experience

Dr. Kim is currently a Postdoctoral Researcher at KICT, contributing to advancements in civil infrastructure and environmental solutions. Prior to this, he worked at the Intelligent Construction Automation Research Center, Kyungpook National University, for over three years. He also shared his expertise as a lecturer at Daegu University, teaching courses such as Basic Statistics and Construction Management. His combined academic and field experience empowers him to lead high-impact research in civil engineering. 🏢👨‍🏫

🏅 Awards and Honors

Dr. Kim holds registered intellectual property rights, including a software-based Construction Waste Information Management (CWIM) system using QR codes (2023), and a patented Eco-Friendly Value Engineering Decision Analysis System (Patent No. 10-1745567, registered in 2017). These innovations underscore his commitment to enhancing efficiency and sustainability in construction engineering through smart technologies. 🏆📜💡

🔍 Research Focus

Dr. Kim’s primary research areas include construction safety, environmental load management, and project efficiency, with a strong focus on big data, machine learning, and geospatial analysis. He specializes in Value Engineering (VE), Life Cycle Assessment (LCA), and advanced image processing techniques like YOLO for object detection. His multidisciplinary approach supports disaster prevention and promotes green building practices. 🔎🌱📈

📘 Conclusion

Combining strong academic foundations with hands-on innovation, Dr. Joon-Soo Kim continues to make significant strides in the civil and construction engineering fields. His work not only enhances safety and environmental responsibility but also sets a benchmark in leveraging AI-driven methodologies for engineering problem-solving. 👏🌐🚧

📚 Top Publications with 

  1. Image Processing and QR Code Application Method for Construction Safety Management
    Kim, J.-S., Yi, C.-Y., & Park, Y.-J., 2021, Applied Sciences
    📑 Cited by: 18 articles (as per Google Scholar)

  2. Impact Evaluation of Water Footprint on Stages of Drainage Works
    Chen Di, Kim, J.-S., Batagalle V., & Kim, B.-S., 2020, Journal of the Korean Society of Civil Engineers
    📑 Cited by: 6 articles

  3. Characteristics Analysis of Seasonal Construction Site Fall Accident using Text Mining
    Kim, J.-S., & Kim, B.-S., 2019, Journal of the Korea Institute of Construction Engineering and Management
    📑 Cited by: 11 articles

  4. Analysis of the Environmental Load Impact Factors for IPC Girder Bridge Using PCA
    Kim, J.-S., Jeon, J.-G., & Kim, B.-S., 2018, Journal of the Korea Institute of Construction Engineering and Management
    📑 Cited by: 9 articles

  5. Analysis of Fire-Accident Factors Using Big-Data in Construction Areas
    Kim, J.-S., & Kim, B.-S., 2017, KSCE Journal of Civil Engineering
    📑 Cited by: 34 articles

  6. Eco-Friendly Design Evaluation Model Using PEI for Construction Facilities
    Kim, J.-S., & Kim, B.-S., 2017, Journal of the Korean Society of Civil Engineers
    📑 Cited by: 10 articles

  7. Definition of Environmental Cost and Eco-VE Model for Construction Facility
    Kim, M.-J., Kim, J.-S., & Kim, B.-S., 2016, Journal of the Korean Society of Civil Engineers
    📑 Cited by: 7 articles

  8. A Proposal of NIA Model for Eco VE Decision of Construction Facilities
    Kim, J.-S., & Kim, B.-S., 2015, Journal of the Korean Society of Civil Engineers
    📑 Cited by: 12 articles

 

Assoc. Prof. Dr. Yun-Cheng Tsai | Data Analytics | Best Researcher Award

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Assoc. Prof. Dr. Yun-Cheng Tsai | Data Analytics | Best Researcher Award

Associate Professor, National Taiwan Normal University, Taiwan

Dr. Yun-Cheng Tsai is a distinguished researcher and educator specializing in blockchain technology, financial vision, artificial intelligence, and educational analytics. He is currently a faculty member at the National Taiwan Normal University, Department of Technology Application and Human Resource Development. With a strong background in computer science and information engineering, Dr. Tsai has contributed significantly to various domains, including educational metaverse environments, reinforcement learning in finance, and data privacy protection. His interdisciplinary research integrates technology and human resource development, making a substantial impact on academia and industry. 🌏💡

Publication Profile

🎓 Education

Dr. Tsai earned his Ph.D. in Computer Science and Information Engineering from National Taiwan Normal University (2009-2016) 🎓. His academic journey also includes prestigious research stays at the Max Planck Institute for the History of Science and Humboldt-Universität zu Berlin, where he collaborated on pioneering technological advancements in data science and blockchain applications. 🌍📖

💼 Experience

With a rich academic career spanning multiple institutions, Dr. Tsai has held faculty positions at several esteemed universities in Taiwan. Before joining National Taiwan Normal University in 2022, he was affiliated with Soochow University (2019-2022), National Taiwan University (2017-2019), and National Taipei University of Business (2016-2017). His expertise in blockchain and AI applications has also led to extensive research collaborations globally. 🏫🔬

🏆 Awards and Honors

Dr. Tsai’s contributions to blockchain technology, financial data security, and educational analytics have earned him recognition in the research community. His invited research positions at the Max Planck Institute and Humboldt-Universität zu Berlin highlight his international reputation. 🏅📜

🔬 Research Focus

Dr. Tsai’s research spans blockchain applications in financial systems, reinforcement learning for trading strategies, and AI-driven educational environments. He has developed innovative solutions for transparency in carbon credit markets, interactive learning tools for blockchain education, and privacy-preserving financial vision models. His work is widely cited and influences both academic and industry advancements. 🚀📊

🔍 Conclusion

Dr. Yun-Cheng Tsai is a leading academic in blockchain technology, AI, and educational analytics, making significant contributions to transparency in financial markets, metaverse learning, and AI-powered trading strategies. His global collaborations and impactful research continue to shape the future of technology and education. 🌟📡

🔗 Publications

Enhancing Transparency and Fraud Detection in Carbon Credit Markets Through Blockchain-Based Visualization Techniques – Electronics (2025) 🔗 DOI: 10.3390/electronics14010157

Empowering Young Learners to Explore Blockchain with User‐Friendly Tools: A Method Using Google Blockly and NFTs – IET Blockchain (2024) 🔗 DOI: 10.1049/blc2.12055

Empowering Students Through Active Learning in Educational Big Data Analytics – Smart Learning Environments (2024) 🔗 DOI: 10.1186/s40561-024-00300-1

Learner-Centered Analysis in Educational Metaverse Environments: Exploring Value Exchange Systems Through Natural Interaction and Text Mining – Journal of Metaverse (2023) 🔗 DOI: 10.57019/jmv.1302136

Financial Vision-Based Reinforcement Learning Trading Strategy – Analytics (2022) 🔗 DOI: 10.3390/analytics1010004

The Protection of Data Sharing for Privacy in Financial Vision – Applied Sciences (2022) 🔗 DOI: 10.3390/app12157408

Dynamic Deep Convolutional Candlestick Learner – arXiv (2022) 🔗 Scopus ID: 85123711664

A Pricing Model with Dynamic Credit Rating Transition Matrices – Journal of Risk Model Validation (2021) 🔗 DOI: 10.21314/JRMV.2021.007

Chunling Bao | Data Science | Best Researcher Award

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Ms. Chunling Bao | Data Science | Best Researcher Award

PhD Candidates, Shanghai Normal University, China

Chunling Bao is a dedicated Ph.D. candidate at Shanghai Normal University, specializing in environmental and geographical sciences 🌍. With a strong academic background and research focus on dust storms, climate change, and land surface interactions, she has contributed significantly to understanding environmental dynamics in East Asia. Her scholarly work is widely recognized, with multiple publications in high-impact journals 📚.

Publication Profile

ORCID

🎓 Education

Chunling Bao embarked on her academic journey at Inner Mongolia Normal University, earning her undergraduate degree (2014-2018) and later obtaining her master’s degree (2018-2021) 🎓. She expanded her expertise through an exchange program at the Center for Agricultural Resources Research, Chinese Academy of Sciences (2023), before pursuing her doctoral studies at Shanghai Normal University (2023-present) 🏫.

💼 Experience

With a deep passion for environmental research, Chunling Bao has explored dust storms, vegetation interactions, and land-atmosphere processes. Her experience includes field studies, satellite data analysis, and interdisciplinary research collaborations 🌪️. Her academic training at leading Chinese institutions has enriched her expertise in remote sensing, environmental monitoring, and climate analysis.

🏆 Awards and Honors

Chunling Bao has been recognized for her outstanding research contributions in environmental science 🏅. Her work has been published in top-tier journals, and she has actively participated in academic exchanges and research collaborations. Her efforts in studying dust storm dynamics have positioned her as an emerging scholar in the field 🌿.

🔬 Research Focus

Her research primarily focuses on the spatial and temporal dynamics of dust storms, their drivers, and their environmental impacts in East Asia 🌫️. Using remote sensing and geospatial analysis, she investigates the effects of land surface changes on atmospheric conditions. Her studies contribute to climate adaptation strategies and sustainable environmental management.

📌 Conclusion

As an emerging environmental researcher, Chunling Bao is making significant strides in understanding dust storm dynamics and their broader ecological implications. With her growing academic contributions and research excellence, she continues to shape the field of environmental science and atmospheric studies 🌏.

📚 Publications

Dust Intensity Across Vegetation Types in Mongolia: Drivers and Trends. Remote Sensing, 17(3), 410. 🔗 DOI

Analyses of the Dust Storm Sources, Affected Areas, and Moving Paths in Mongolia and China in Early Spring. Remote Sensing, 14, 3661. 🔗 DOI

Impacts of Underlying Surface on Dusty Weather in Central Inner Mongolian Steppe, China. Earth and Space Science, 8, e2021EA001672. 🔗 DOI

Regional Spatial and Temporal Variation Characteristics of Dust in East Asia. Geographical Research, 40(11), 3002-3015. 🔗 DOI (in Chinese)

Analysis of the Movement Path of Dust Storms Affecting Alxa. Journal of Inner Mongolia Normal University (Natural Science Mongolian Edition), 04, 39-47.

Evaluation of the Impact of Coal Mining on Soil Heavy Metals and Vegetation Communities in Bayinghua, Inner Mongolia. Journal of Inner Mongolia Normal University (Natural Science Mongolian Edition), 40(1), 32-38.