Masahiko Nakase | Engineering | Research Excellence Award

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Kicheol Lee | Engineering | Best Researcher Award

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Dr. Kicheol Lee | Engineering | Best Researcher Award

Dr. Kicheol Lee | Halla University/RISE Project Group | South Korea

Dr. Kicheol Lee is a research professor specializing in civil and structural engineering, with a strong record in foundation engineering, numerical modelling, and new technology development. His work spans artificial intelligence (machine learning, deep learning), probabilistic and statistical methods, field applications in geotechnical/tunnel/foundation engineering, and reliability-based design (LRFD). He has been recognized with multiple best paper and presentation awards from the Korea Geosynthetics Society and the Korea Geotechnical Society. His expertise in numerical simulation (particularly via ABAQUS), and integration of AI/ML with civil engineering systems, has made him a leading figure in predictive modeling, anomaly detection, and structural reliability. Dr. Lee’s contribution lies in bridging advanced computational methods with practical engineering challenges, especially in ensuring safety, resilience, and sustainability of infrastructure. Dr. Lee’s current research is deeply interdisciplinary, merging geotechnical engineering, structural health monitoring, and intelligent systems to create safer, data-driven infrastructure solutions.His ongoing work under the Gangwon RISE Project aims to transform urban safety and sustainability by employing augmented and virtual reality technologies for real-time disaster visualization and early warning.

Author’s Profile

Scopus | Orcid

Early Academic Pursuits

Dr. Kicheol Lee began his academic journey in Civil and Environmental Engineering at Incheon National University, where he earned his Bachelor’s degree (2015), Master’s degree (2017), and Doctorate (Ph.D., 2021). His early research concentrated on geotechnical and foundation engineering, particularly the mechanical behavior of pile groups and the evaluation of soil–structure interactions through numerical and experimental methods. His doctoral dissertation, “Evaluation of Resistance Factors of Pile Groups Consisting of Drilled Shafts Embedded in Sandy Ground under Axial Load through Numerical Analysis,” established his expertise in reliability-based foundation design (LRFD) and computational modeling using ABAQUS, laying the groundwork for his later innovations in smart infrastructure systems.

Professional Endeavors

Dr. Lee’s professional career seamlessly bridges academia, industry, and national research initiatives, reflecting his commitment to advancing digitally enhanced civil infrastructure technologies. He currently serves as a Research Professor at Halla University under the RISE Project Group (since September 2025), where he leads the Gangwon RISE Project focused on developing advanced safety and green city technologies through the integration of Digital Twin and 3D data. Prior to this role, he was a Principal Researcher at the Korea Institute of Structural Integrity Research (2024–2025), where he led national R&D projects centered on innovative construction technologies and safety inspection systems. From 2021 to 2024, he served as Research Director at UCI Tech Co., Ltd., managing government-funded initiatives that merged IoT and augmented reality (AR) technologies for infrastructure maintenance and smart monitoring applications. Across these roles, Dr. Lee has demonstrated a clear progression from applied geotechnical engineering toward the fusion of engineering mechanics, intelligent systems, and data science to create more resilient, sustainable, and intelligent civil infrastructure.

Contributions and Research Focus

Dr. Lee’s interdisciplinary research bridges geotechnical engineering with artificial intelligence, probability, and information technologies to develop data-driven and intelligent systems for the monitoring, design, and maintenance of civil infrastructures. His expertise spans artificial intelligence—particularly the application of convolutional and recurrent neural networks (CNNs and RNNs) for anomaly detection, predictive modeling, and data-driven decision-making in structural health monitoring—as well as foundation and tunnel engineering, focusing on advanced modeling and soil–structure interaction analysis. He is also skilled in numerical analysis using ABAQUS to simulate complex geotechnical phenomena and evaluate soil–structure responses. In addition, Dr. Lee integrates reliability and probabilistic design principles through statistical modeling, Monte Carlo simulations, and Bayesian inference within LRFD-based design frameworks. His innovative contributions extend to smart infrastructure and safety systems, including the development of AI-enabled inspection robots, reversible thermochromic materials for black-ice prevention, and UAV-based soil monitoring systems utilizing hyperspectral imaging. He has led or contributed to 11 major national R&D projects funded by various Korean ministries—including those of Education, Environment, Land, Transport, Industry, and SMEs & Startups—addressing challenges in smart cities, environmental protection, and disaster prevention, all aimed at advancing sustainable and resilient civil infrastructure.

Impact and Influence

Dr. Lee’s scholarly influence is reflected in his prolific publication record, with over 50 peer-reviewed journal papers—15 indexed in SCI/SCI(E), 34 in Korean journals, and 2 in Scopus. His research has appeared in leading international journals such as Applied Sciences, Sustainability, Remote Sensing, Polymers, and Tunnelling and Underground Space Technology. His academic excellence has been recognized through several prestigious awards, including the Best Paper Presentation Awards from the Korea Geosynthetics Society and the Korea Geotechnical Society in 2020, and the Best Paper Award from the Korea Geosynthetics Society in 2019. Complementing his scholarly achievements, Dr. Lee holds 15 registered patents in the Republic of Korea, showcasing his technological innovation in civil engineering through the development of smart barriers, reversible paints for road safety, and advanced pile systems. Beyond research, he actively contributes to the professional community as an Editorial Board Member of the Korea Geosynthetics Society (2024–Present), and as Assistant Administrator of both the Low-Carbon Construction Committee and the Incheon Regional Committee of the Korean Geotechnical Society (since 2023). Through these roles, Dr. Lee fosters academic collaboration, encourages the dissemination of innovation, and advances sustainable engineering practices in the civil infrastructure domain.

Academic Cites

Dr. Lee’s work is frequently cited in research concerning geotechnical reliability, foundation engineering, and smart civil technologies. His papers on hyperspectral soil analysis and negative skin friction in piles have become valuable references in data-integrated geotechnical research. By bridging machine learning with traditional civil engineering models, his methodologies have influenced new approaches to predictive maintenance and risk-based infrastructure management in both academia and industry.

Legacy and Future Contributions

Dr. Kicheol Lee embodies a new generation of civil engineers who seamlessly integrate artificial intelligence, sustainability, and resilience into traditional infrastructure systems. His pioneering work on AI-driven monitoring, Digital Twin simulations, and smart geotechnical materials is reshaping the future of infrastructure safety and environmental protection. Looking ahead, Dr. Lee aspires to expand the application of augmented reality (AR) and digital twin technologies for real-time disaster prediction and response, develop autonomous robotic systems for structural inspection and maintenance, and contribute to global initiatives promoting smart and sustainable urban development in the face of climate change. His long-term vision is centered on building data-informed, intelligent, and resilient civil infrastructure systems that not only enhance public safety and operational efficiency but also minimize environmental impact—paving the way for the realization of next-generation smart and sustainable cities.

Featured Publications

Lee, K. (2024). Verification of construction method for smart liners to prevent oil spill spread in onshore. Sustainability, 16(23), 10626. https://doi.org/10.3390/su162310626

Lee, K. (2023). Proposal of construction method of smart liner to block and detect spreading of soil contaminants by oil spill. International Journal of Environmental Research and Public Health, 20(2), 940. https://doi.org/10.3390/ijerph20020940

Lee, K. (2022). Spectrum index for estimating ground water content using hyperspectral information. Sustainability, 14(21), 14318. https://doi.org/10.3390/su142114318

Lee, K. (2022). Prediction of ground water content using hyperspectral information through laboratory test. Sustainability, 14(17), 10999. https://doi.org/10.3390/su141710999

Lee, K. (2021). Analysis of vertical earth pressure acting on box culverts through centrifuge model test. Applied Sciences, 12(1), 81. https://doi.org/10.3390/app12010081

Lee, K. (2020). Numerical analysis of the contact behavior of a polymer-based waterproof membrane for tunnel lining. Polymers, 12(11), 2704. https://doi.org/10.3390/polym12112704

Lee, K. (2020). Analysis of effects of rock physical properties changes from freeze–thaw weathering in Ny-Ålesund region: Part 2—Correlations and prediction of weathered properties. Applied Sciences, 10(10), 3392. https://doi.org/10.3390/app10103392

Lee, K. (2020). Analysis of effects of rock physical properties changes from freeze–thaw weathering in Ny-Ålesund region: Part 1—Experimental study. Applied Sciences, 10(5), 1707. https://doi.org/10.3390/app10051707

Omar Soufi | Engineering | Best Researcher Award

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Mr. Omar Soufi | Engineering | Best Researcher Award

Dr. of Mohammed V University of Rabat Mohammadia School of Engineering, Morocco

Dr. Omar Soufi 🎓, born on May 13, 1993, in Casablanca, is a distinguished expert in AI, Data Science, and GIS 🌐. With a Doctorate from EMI Rabat, his research excels in enhancing satellite imagery using deep learning 🛰️. Fluent in Arabic, French, English, and Spanish 🌍, he has held roles such as Project Manager and Head of BI & Decision Support Tools 📈. Certified in AI, ML, and data analytics 📜, Dr. Soufi continues to drive innovation and strategic advancements 🚀.

Professional Profile:

Education🎓

Dr. Omar Soufi 🎓 holds a Doctorate in AI from EMI Rabat (2023), focusing on improving satellite image quality using deep learning 🛰️. He also completed his engineering studies at Polytechnique Grenoble, ENSIMAG (2020) in Information Systems Engineering, and at EMI Rabat in Software Engineering and Quality 💻. Prior to this, he earned a Diploma in University Studies (2015) and a Bachelor’s in Mechanical Engineering Sciences and Techniques from ARM Merkèns (2014) 🔬. His academic journey began with a Baccalaureate in Life and Earth Sciences (2011) 🌍.

 

Professional Experience 📚

 

Dr. Omar Soufi 🎓 has a rich professional background in AI, Data Science, and GIS 🌐. Starting as a Project Manager in IT (2016), he advanced to Team Leader at the Decision Support Center (2017) 📊. By 2020, he became Head of BI & Decision Support Tools, and in 2022, he led the Geomatics & Decision Support Tools division 🚀. His latest role in 2024 is AI Missions Manager. Dr. Soufi’s expertise includes creating data-driven solutions and improving organizational performance 📈.

Research Interest 🔍

Dr. Omar Soufi 🎓 is deeply passionate about AI, Data Science, and GIS 🌐. His research interests focus on enhancing satellite imagery quality using deep learning 🛰️, spatial remote sensing, and big data analytics 📊. Dr. Soufi is dedicated to advancing computational methods for improved data visualization, decision-making tools, and innovative applications in geomatics and spatial data analysis 🚀. His work aims to drive technological innovation and strategic insights, contributing significantly to these cutting-edge fields 📈.

Award and Honor🏆

Dr. Omar Soufi 🎓 has received numerous awards and honors for his contributions to AI, Data Science, and GIS 🌐. Notably, he was recognized for his groundbreaking research in enhancing satellite imagery using deep learning 🛰️. His accolades include prestigious certifications in AI, ML, and data analytics 📜, and he has been honored for his leadership roles in IT and decision support tools 📈. Dr. Soufi’s commitment to innovation and excellence has earned him a reputation as a leading expert in his field 🚀.

Research Skills🌟

Dr. Omar Soufi 🎓 possesses exceptional research skills in AI, Data Science, and GIS 🌐. He excels in deep learning applications for enhancing satellite imagery 🛰️ and has extensive experience in big data analytics, data visualization, and computational methods 📊. Proficient in developing innovative decision-making tools and systems, Dr. Soufi’s expertise extends to creating distributed systems for real-time data processing 🚀. His analytical abilities and strategic insights drive technological advancements and practical solutions in his research fields 📈.

Achievements🏅

  • 🛰️ Enhanced satellite imagery quality using deep learning in his doctoral research.
  • 🌐 Specialized in AI, Data Science, and GIS with significant contributions.
  • 📊 Developed innovative big data analytics and decision-making tools.
  • 💻 Led successful projects in IT and decision support as a Project Manager and Team Leader.
  • 🚀 Headed the Geomatics & Decision Support Tools division.
  • 📈 Recognized for leadership roles and strategic advancements in data-driven solutions.
  • 📜 Earned prestigious certifications in AI, ML, and data analytics.
  • 🌍 Multilingual proficiency in Arabic, French, English, and Spanish.
  • 👨‍🏫 Created educational platforms and e-learning solutions during his academic projects.
  • 🔍 Published research and received accolades in AI and data science communities.

Projects🏅

  • 📚 E-learning Platform: Designed and implemented an e-learning platform at EMI.
  • 📊 Big Data Architecture: Developed a big data architecture for data analysis and processing.
  • 🎓 Recommendation System: Created a platform for recommending educational resources.
  • 🌐 Data Visualization Web App: Built a web application for data visualization and processing.
  • 🖥️ Distributed Data Processing System: Implemented a distributed system for streaming data using Kafka, Flink, Cassandra, and Grafana.
  • 🛰️ Satellite Super-Resolution: Worked on super-resolution of satellite images using deep learning during his final-year internship at CRTS Rabat.
  • 🚀 Space Station Management: Designed a management platform for a space station during an engineering internship at CRERS Rabat.
  • 🌾 Agricultural Bulletin Platform: Developed a platform for disseminating agricultural bulletins for CRTS Rabat.

Publications🏅📚

  • Study of deep learning-based models for single image super-resolution🏅📚
    • Author(s): Soufi, O., Belouadha, F.Z.
    • Year: 2022
    • Journal: Revue d’Intelligence Artificielle
    • Volume: 36
    • Issue: 6
    • Pages: 939-952
    • DOI: 10.18280/ria.360616

 

  • FSRSI: New deep learning-based approach for super-resolution of multispectral satellite images🏅📚
    • Author(s): Soufi, O., Belouadha, F.Z.
    • Year: 2023
    • Journal: Ingénierie des Systèmes d’Information
    • Volume: 28
    • Issue: 1
    • Pages: 113-132
    • DOI: 10.18280/isi.280112

 

  • Deep learning technique for image satellite processing🏅📚
    • Author(s): Soufi, O., Belouadha, F.Z.
    • Year: 2023
    • Journal: Intell Methods Eng Sci
    • Volume: 2
    • Issue: 1
    • Pages: 27-34
    • Month: March
    • DOI: Not provided

 

  • Enhancing Accessibility to High-Resolution Satellite Imagery: A Novel Deep Learning-Based Super-Resolution Approach🏅📚
    • Author(s): Soufi, O., Belouadha, F.Z.
    • Year: 2023
    • Journal: Journal of Environmental Treatment Techniques
    • Volume: 11
    • Issue: 2
    • Pages: 44-49
    • DOI: Not provided

 

  • An intelligent deep learning approach to spacecraft attitude control: the case of satellites🏅📚
    • Author(s): Soufi, O., Belouadha, F.Z.
    • Year: 2023
    • Status: Under evaluation