Zuizhi Lu | Luminescent Material | Best Researcher Award 

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Dr. Zuizhi Lu | Luminescent Material | Best Researcher Award 

Dr. Zuizhi Lu | Guangxi Minzu University | China

Author Profile

Scopus

Early Academic Pursuits

Dr. Zuizhi Lu began his academic journey in 2012 at Central South Minzu University, where he pursued a Bachelor’s Degree in Chemical Engineering and Technology. His dedication to academic excellence was evident early on, as he developed a strong foundation in materials chemistry and engineering. Continuing his education, he obtained his Master’s Degree in Chemical Engineering from Guangxi University in 2018, where his outstanding performance earned him the First-Class Academic Scholarship and the Excellent Graduation Thesis Award. Driven by a passion for research and innovation, Dr. Lu advanced to the Doctoral Program in Chemical Engineering and Technology at Guangxi University, completing his Ph.D. in 2023 with remarkable distinction.

Professional Endeavors

Following his academic achievements, Dr. Zuizhi Lu has established himself as a promising researcher in the field of chemical engineering and materials science. He currently leads multiple research projects at Guangxi Minzu University, including the Guangxi Middle-Aged and Young Teachers’ Basic Competence Enhancement Project and the 2024 Talent Introduction Scientific Research Initiation Project, funded with 80,000 yuan. His professional endeavors emphasize the synthesis, optimization, and application of luminescent materials, advancing both academic understanding and technological development in the field.

Contributions and Research Focus

Dr. Lu’s research primarily focuses on inorganic luminescent materials, exploring their chemical composition, structural characteristics, and potential applications in photonics, display technologies, and sensors. He has published 10 academic papers as the first author or corresponding author, contributing significant findings to the scientific community. His innovative work in luminescent materials enhances the development of high-efficiency and eco-friendly materials for modern optical applications. Dr. Lu’s meticulous approach to experimentation and theoretical modeling has helped deepen the understanding of luminescent mechanisms at the atomic level.

Impact and Influence

Dr. Zuizhi Lu’s impact on the field of luminescent materials research is increasingly recognized both nationally and internationally. His studies have influenced emerging directions in materials chemistry and photonic technology. His achievements, including the prestigious National Scholarship for Doctoral Students (China) in 2019, underline his exceptional academic performance and research potential. Through mentorship, collaboration, and conference participation, Dr. Lu continues to inspire young scientists to pursue excellence in chemical engineering and luminescent material science.

Academic Cites

The academic community has taken keen interest in Dr. Lu’s published works, which are frequently cited for their originality and technical depth. His contributions to luminescent materials are serving as foundational references for ongoing studies in inorganic phosphors, optical coatings, and light-emitting technologies. The steady growth of his citation record highlights his rising influence in the global materials research landscape.

Legacy and Future Contributions

Looking to the future, Dr. Zuizhi Lu aims to further expand his research on luminescent materials, developing next-generation optical materials with enhanced energy efficiency and environmental sustainability. His ongoing projects and commitment to innovation promise to strengthen China’s leadership in advanced materials science. As a mentor and researcher, he is shaping a new generation of scholars while building a lasting legacy in luminescence research. His future endeavors are expected to yield breakthroughs in high-performance luminescent materials that will benefit both academia and industry.

Luminescent Materials

Dr. Zuizhi Lu’s pioneering research in luminescent materials has significantly advanced the understanding of inorganic phosphors and optical mechanisms. His academic and professional work continues to drive innovations in luminescent materials synthesis and applications. The future of luminescent materials research under Dr. Lu’s guidance promises remarkable contributions to energy-efficient technologies and material science development.

Featured Publications

Crystallographic site engineering enables long-wavelength broadband near-infrared emission in Ni²⁺-activated Sr₂MNbO₆ (M = Ga and Sc) phosphors with improved thermal stability. Ceramics International.

Integrated “all-in-one” strategy toward boosting photoluminescence performance in Cr³⁺-activated garnet phosphors. Journal of Luminescence.

Nirmal Varghese Babu | Artificial Intelligence | Best Researcher Award 

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Dr. Nirmal Varghese Babu | Artificial Intelligence | Best Researcher Award 

Dr. Nirmal Varghese Babu | Karunya Institute of Technology and Sciences | India

Author Profiles

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Early Academic Pursuits

Dr. Nirmal Varghese Babu began his academic journey with a strong inclination toward computer science and technology. He completed his B.Tech in Information Technology from Karunya Institute of Technology and Sciences, Coimbatore, in 2017 with a CGPA of 8.0. His passion for research and innovation in computing led him to pursue an M.Tech in Computer Science & Engineering from Amal Jyothi College of Engineering, Kanjirappally (2017–2019), graduating with an impressive CGPA of 8.72. Currently, he is pursuing a Ph.D. in Computer Science & Engineering from Karunya Institute of Technology and Sciences, expected to be completed in 2025. His academic excellence was rooted in his formative years at Mathews Mar Athanasius Residential School, Chengannur, where he built a strong foundation in analytical and computational thinking.

Professional Endeavors

Dr. Nirmal Varghese Babu is currently serving as an Assistant Professor at the School of Computer Science and Technology, Karunya Institute of Technology and Science, Coimbatore (since July 26, 2022). His professional endeavors include teaching, research, and mentoring in various areas of computer science and Artificial Intelligence. He has delivered lectures on Artificial Intelligence: Principles and Techniques, Cloud Computing for Data Analytics, AI for Games, AI for Food Processing Engineering, AI for Biotechnology, and MLOps. Alongside teaching, he mentors undergraduate students, coordinates final-year projects, and supervises academic research initiatives. His teaching methodology emphasizes experiential learning, guiding students to bridge theoretical knowledge with real-world technological applications.

Contributions and Research Focus

Dr. Nirmal’s research contributions revolve around Artificial Intelligence, machine learning, data analytics, and real-time systems. His M.Tech project, Multiclass Sentiment Analysis of Social Media Data using Neural Networks, explored advanced deep learning algorithms like CNN and RNN for classifying sentiment across social media platforms, specifically Twitter. This study integrated text and emoticon data for multiclass classification using one-hot encoding and neural networks. His earlier project, Real-Time Traffic Incident Detection using Social Media Data, demonstrated innovative use of Natural Language Processing to detect and analyze traffic incidents using Twitter data, integrating AI for real-time decision-making. His work exemplifies how Artificial Intelligence can transform data into actionable insights for societal and industrial benefit.

Impact and Influence

Dr. Nirmal Varghese Babu’s impact as an educator and researcher extends across academia and applied technology. At Karunya Institute, he plays a vital role in shaping the next generation of AI-driven engineers and data scientists. As a mentor and coordinator, he has successfully guided numerous B.Tech projects, fostering innovation in the domains of Artificial Intelligence, MLOps, and machine learning. His pedagogical style emphasizes research-based learning, promoting creative problem-solving and real-world application of AI. Through his leadership in academic project coordination and curriculum development, he has significantly influenced the integration of AI-based methodologies into modern engineering education.

Academic Cites

Dr. Nirmal’s academic contributions are recognized through his published works, research projects, and student-guided studies. His projects on sentiment analysis and traffic incident detection have been well-cited and appreciated within the AI and data analytics community. The relevance of his research is reflected in growing academic references to his work in areas such as neural networks, data mining, and sentiment classification. His scholarly achievements continue to inspire students and researchers pursuing advanced studies in Artificial Intelligence and computational learning.

Legacy and Future Contributions

Looking ahead, Dr. Nirmal Varghese Babu aims to expand his research in Artificial Intelligence, focusing on its integration with real-time analytics, smart systems, and cognitive computing. His future contributions are expected to advance the use of AI in multidisciplinary fields such as biotechnology, healthcare, and environmental systems. As an educator, his legacy lies in his ability to inspire and mentor young researchers, promoting a culture of innovation and ethical AI development. His ongoing research and academic leadership will undoubtedly continue to shape the evolution of AI-driven solutions and their transformative potential across industries.

Artificial Intelligence

Dr. Nirmal Varghese Babu’s expertise in Artificial Intelligence is evident through his teaching, research, and innovation in deep learning, neural networks, and data analytics. His projects and mentorship highlight the transformative role of Artificial Intelligence in addressing real-world challenges. The continued advancement of Artificial Intelligence under his guidance promises to create meaningful impact in both academic and applied technological domains.

Featured Publications

Babu, N. V., & Kanaga, E. G. M. (2022). Sentiment analysis in social media data for depression detection using artificial intelligence: A review. SN Computer Science, 3(1), 1–15. https://doi.org/10.1007/s42979-021-00921-2

Babu, D. E. G. M. K. N. V. (2022). Sentiment analysis in social media data for depression detection using artificial intelligence: A review. SN Computer Science, 3, 350.

Babu, N. V., & Rawther, F. A. (2021). Multiclass sentiment analysis in text and emoticons of Twitter data: A review. Proceedings of the Second International Conference on Networks and Advances in Computational Technologies (NetACT).

Prince, S. C., & Babu, N. V. (2024). Advancing multiclass emotion recognition with CNN-RNN architecture and illuminating module for real-time precision using facial expressions. Proceedings of the 2024 International Conference on Advances in Modern Age Technologies for Sustainable Development (AMATS).

Babu, N. V., Kanaga, E. G. M., Kattappuram, J. T., & Benny, R. V. (2023). AI-based EEG analysis for depression detection: A critical evaluation of current approaches and future directions. Proceedings of the 2023 International Conference on Computational Intelligence and Sustainable Technologies (CIST).

Babu, D. E. G. M. K. N. V. (2022). Depression analysis using electroencephalography signals and machine learning algorithms. Proceedings of the Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT).

Adityasai, B., & Babu, N. V. (2024). Advancing Alzheimer’s diagnosis through transfer learning with deep MRI analysis. Proceedings of the 2024 International Conference on Advances in Modern Age Technologies for Sustainable Development (AMATS).

Babu, N. V., & Kanaga, E. G. M. (2023). Multiclass text emotion recognition in social media data. In Machine Intelligence Techniques for Data Analysis and Signal Processing (pp. 123–135). Springer.

Rawther, F. A., & Babu, N. V. (2019). User behavior analysis on social media data using sentiment analysis or opinion mining. International Research Journal of Engineering and Technology (IRJET), 6(6), 3081–3085.

Hanin Othman | Environmental Science and Smart Technology | Young Researcher Award 

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Ms. Hanin Othman | Environmental Science and Smart Technology | Young Researcher Award 

Ms. Hanin Othman | Pennsylvania State University | United States

Author Profiles

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Early Academic Pursuits

Ms. Hanin Othman began her academic journey with a strong foundation in architecture and design. She earned her Bachelor of Science in Architectural Engineering from The Hashemite University, Jordan in 2014, where she graduated among the top students in her class and received multiple honors, including the Best Graduation Project Award. Her academic excellence continued through her Master of Science in Architectural Engineering from The University of Jordan in 2019, where her thesis publication earned the Best Master Thesis Published Paper Award. Building upon these achievements, she is currently pursuing a Ph.D. in Architecture (Sustainability) at Pennsylvania State University, USA. Her educational path reflects a consistent dedication to research and innovation at the intersection of environmental science and smart technology.

Professional Endeavors

Ms. Othman’s professional journey is marked by her deep involvement in academia, research, and creative technology. At Penn State University, she serves as a Graduate Teaching Assistant, instructing courses such as Basic Design and Research and Sustainable Architecture I & II. She is also the Artist and Maker in Residence at the Learning Factory, where she designs and leads workshops on low-cost IoT-based environmental monitoring systems using Arduino. Her earlier professional experience includes working as an Architect and Design Studio Supervisor at The Hashemite University, and as an Architect at Ruba Hosuah for Engineering. These roles allowed her to integrate sustainability principles with modern design methods, reinforcing her commitment to environmental science and smart technology.

Contributions and Research Focus

Ms. Hanin Othman’s research lies at the dynamic intersection of environmental science and smart technology, with a particular focus on sustainability, digital fabrication, and sensing technologies in architecture. Her doctoral research emphasizes the development of IoT-based indoor air quality monitoring systems, integrating mobile platforms, robotic sensing, and data-driven optimization techniques. She also explores urban microclimates, vegetation impacts, and thermal comfort using simulation tools such as ENVI-met, Design Builder, and CFD modeling. Additionally, her work in robotic fabrication bridges computational design with traditional craftsmanship, pushing the boundaries of sustainable architectural innovation.

Impact and Influence

Ms. Othman has made a remarkable impact both as a researcher and an educator. Her innovative approach to integrating environmental science and smart technology into architecture has influenced sustainable design practices and academic pedagogy. She has been recognized through numerous awards, including the ICDS Rising Researcher Award (2025–2026), Fox Scholar Award (2025), Sustainability Graduate Student Award Nomination (2024–2025), and the Artists and Makers in Residence Program (2024–2025). Her teaching contributions at Penn State University have inspired many students to embrace interdisciplinary and environmentally responsive design approaches.

Academic Cites

Ms. Othman’s research contributions have been featured in conferences, workshops, and institutional publications, reflecting the growing academic acknowledgment of her work. Her studies in environmental science and smart technology have attracted attention for their real-world applicability and technological innovation. Through her participation in Penn State’s Institute for Computational and Data Sciences (ICDS) and Hamer Center for Community Design, she has collaborated on projects that integrate digital twins, IoT networks, and data-driven environmental monitoring   all contributing to the broader academic discourse on sustainable and smart architectural systems.

Legacy and Future Contributions

Looking forward, Ms. Hanin Othman’s legacy will be defined by her contributions to sustainable architectural research and the advancement of environmental science and smart technology. Her ongoing projects, such as TwinSight: A Data-Driven Digital Twin Framework for Human-Centric Health Monitoring, highlight her vision for human-centered, data-driven, and equitable environmental design. As she continues to mentor students and collaborate across disciplines, her influence will extend to shaping the next generation of architects and environmental technologists. Her long-term goal is to pioneer scalable, low-cost sensing and smart systems that redefine sustainability in architecture.

Environmental Science and Smart Technology

Ms. Hanin Othman’s research integrates Environmental Science and Smart Technology through IoT-based sensing systems, robotic fabrication, and data-driven environmental design. Her interdisciplinary approach to Environmental Science and Smart Technology bridges architecture, engineering, and sustainability, redefining how design responds to ecological and technological challenges. The future of Environmental Science and Smart Technology continues to evolve through her innovative contributions, academic leadership, and commitment to global sustainable development.

Featured Publications

Othman, H., & Alshboul, A. A. (2020). The role of urban morphology on outdoor thermal comfort: The case of Al-Sharq City–Az Zarqa. Urban Climate, 34, 100706.

Othman, H., Azari, R., & Guimarães, T. (2024). Low-cost IoT-based indoor air quality monitoring. Technology|Architecture + Design, 8(2: Coding), 250–270.

Othman, H., Sieves, G., Guimarães, T., & Azari, R. (2025). A calibration chamber framework for low-cost indoor air quality sensor validation. Building and Environment, 113856.

Othman, H., Sieves, G., Guimaraes, T., & Azari, R. (2024). Development of a calibration chamber to evaluate the performance of a low-cost IAQ sensing device. In SIGraDi 2024 - Biodigital Intelligent Systems Conference 1.

Othman, H., & Azari, R. (2023). Exploring low-cost sensors for indoor air quality (IAQ) monitoring: A review of stationary and mobile sensing systems. In Proceedings of the 11th International Conference of the Arab Society 

Imam, C. A., Othman, H. A. S., & Çapunaman, Ö. B. (2023). Robotic plaster carving: Formalizing subtractive detailing of plaster surfaces for construction and crafts. In 41st Conference on Education and Research in Computer Aided Architectural

Zhenyan Xia | Physics and Astronomy | Best Researcher Award

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Mr Zhenyan Xia | Physics and Astronomy | Best Researcher Award

Mr Zhenyan Xia | Tianjin University | China

Dr. Zhenyan Xia is an associate professor at Tianjin University, China. He has presided over and participated in more than 20 major national and regional research programs, including the Science and Technology Development of Tianjin, the National High Technology Research and Development Program of China (863 Program), and industry collaborations such as Shenzhen Moore Vaporization Health & Medical Tech Co., Ltd. He has published over 80 papers in international journals and conference proceedings, contributing significantly to fluid mechanics, molecular dynamics, and biomedical applications. Dr. Xia’s research on hyaluronic acid, a typical shear-thinning fluid, has advanced biomedical applications in tissue engineering and drug delivery. His team simulated the conformational evolution of hyaluronic acid solutions under varying shear rates, analyzing hydrogen bond lengths and angles. Findings revealed that shear stress reduces the number and strength of hydrogen bonds, enhancing solution flowability, consistent with macroscopic shear-thinning behavior.

Author’s Profiles:

Scopus |  Orcid

Early Academic Pursuits

Dr. Zhenyan Xia developed a strong foundation in fluid mechanics and molecular dynamics during his doctoral and postdoctoral studies. His early research focused on the theoretical modeling of turbulent flows and the microscopic behavior of complex fluids, laying the groundwork for his later innovations in shear-thinning fluid applications and nanostructured fluid systems.

Professional Endeavors

Dr. Xia is currently an associate professor at Tianjin University, where he has led and participated in over 30 national and industry-sponsored research projects, including the National High Technology Research and Development Program of China (863 Program) and collaborations with Shenzhen Moore Vaporization Health & Medical Tech Co., Ltd. He has guided multiple interdisciplinary teams and contributed to advancing applied fluid mechanics and biomedical engineering technologies.

Contributions and Research Focus

Dr. Xia’s research integrates theoretical and applied studies on turbulent flow control, fluid instability, and molecular dynamics of fluid–micro/nano structures. Notably, he modeled hyaluronic acid solutions to reveal molecular-level mechanisms behind shear-thinning behavior. His simulations demonstrated how shear stress reduces hydrogen bond strength and alters molecular conformations, directly correlating with enhanced solution flowability observed in macroscopic experiments. This work provides critical insights for tissue engineering, drug delivery, and biomedical fluid design, bridging molecular simulations with practical engineering applications.

Impact and Influence

Dr. Xia has published more than 80 peer-reviewed papers in international journals and conferences, achieving over 500 citations across SCI, EI, and Scopus databases. He has authored 50 journal articles, supervised multiple industry-sponsored projects, and filed 10 patents, contributing both to fundamental science and practical technologies. His consultancy work with Shenzhen Moore Vaporization Health & Medical Tech Co., Ltd demonstrates the industrial relevance and societal impact of his research.

Academic Cites

  • Over 500 citations in SCI, EI, Scopus

  • 50 journal articles published in indexed journals

  • 10 patents filed/published

Legacy and Future Contributions

Dr. Xia is shaping the future of fluid mechanics and biomedical engineering through the integration of molecular-level understanding with macroscopic engineering applications. He aims to expand computational modeling of complex fluids for smart biomedical materials, enhance industrial fluid processes, and develop scalable applications of shear-thinning and nanostructured fluids. His work is expected to inspire next-generation engineers and researchers, bridging theoretical insights with tangible technological advancements in healthcare and engineering systems.

Featured Publications

Xia, Z., [Other authors if available]. (2024). An analysis of the contact time of nanodroplets impacting superhydrophobic surfaces with square ridges. Computational Materials Science,113249. https://doi.org/10.1016/j.commatsci.2024.113249

Xia, Z., [Other authors if available]. (2022). Experimental investigation of the impact of viscous droplets on superamphiphobic surfaces. Physics of Fluids, https://doi.org/10.1063/5.0080396

Xia, Z., [Other authors if available]. (2021). Research on the contact time of a bouncing microdroplet with lattice Boltzmann method. Physics of Fluids, https://doi.org/10.1063/5.0046551

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

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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

Hafiz Muhammad Raza ur Rehman | Data Science | Best Researcher Award 

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Assist. Prof. Dr. Hafiz Muhammad Raza ur Rehman | Data Science | Best Researcher Award 

Assist. Prof. Dr. Hafiz Muhammad Raza ur Rehman | Yeungnam University | South Korea

Author Profiles

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Early Academic Pursuits

Dr. Hafiz Muhammad Raza ur Rehman began his academic journey with a strong foundation in information and communication engineering, culminating in a PhD from Yeungnam University, Korea. His doctoral research laid the groundwork for his later contributions in machine learning, multi-agent reinforcement learning (MARL), and data-science. His academic excellence and early engagement with algorithmic design and optimization established his trajectory as a dedicated researcher and educator in computational intelligence.

Professional Endeavors

Following his doctoral studies, Dr. Raza ur Rehman pursued a postdoctoral research position in Korea, focusing on sensor calibration for autonomous vehicles (AVs). Over 5.5 months, he conducted high-level interdisciplinary work aimed at improving the precision and reliability of AV sensor systems. He also gained substantial teaching experience 9 months as an Assistant Professor where he taught undergraduate and graduate courses in machine learning, deep learning, reinforcement learning, and data-science. In addition, his collaboration with the Electronics and Telecommunications Research Institute (ETRI), Korea, on a US Air Force–funded project, exemplified his ability to contribute to large-scale international research efforts.

Contributions and Research Focus

Dr. Raza ur Rehman’s research portfolio reflects a deep commitment to innovation and interdisciplinary integration. His primary focus areas include multi-agent reinforcement learning (MARL), autonomous vehicle systems, natural language processing (NLP), and optimization algorithms. He has authored a patent centered on MARL techniques and published several impactful journal and conference papers. Key publications include “QsOD: MARL-based QMIX with Grey Wolf Optimization” and “Prediction-Based Model for Chemical Compounds.” Moreover, he has presented research such as “Camera Calibration with CNN” at IEEE conferences and six additional papers at Korean academic venues. His current research extends to seven articles under review in internationally reputed journals, reinforcing his commitment to advancing data-science and intelligent systems.

Impact and Influence

Dr. Raza ur Rehman’s interdisciplinary research bridges theory and application spanning from algorithmic optimization to real-world technological integration. His MARL-related patent and publications contribute significantly to the growing body of knowledge in intelligent agent systems. By integrating data-science with advanced computational models, his work influences emerging fields such as autonomous navigation, machine learning-based control systems, and intelligent automation. As a mentor, he continues to inspire students through hands-on projects, fostering innovation and critical thinking in the next generation of engineers and researchers.

Academic Cites

His scholarly output includes publications in peer-reviewed international journals, conference presentations, and ongoing submissions to high-impact outlets. The QsOD study and the chemical compound prediction model have attracted interest in computational optimization and artificial intelligence research circles. His IEEE presentation on CNN-based camera calibration further strengthened his academic visibility and recognition within the AI research community.

Legacy and Future Contributions

Looking ahead, Dr. Hafiz Muhammad Raza ur Rehman aims to expand his research on multi-agent reinforcement learning, autonomous systems, and optimization-driven AI architectures. His future work is poised to contribute substantially to global research in data-science, particularly in developing adaptive, intelligent algorithms for complex real-world problems. Through continued teaching, mentorship, and publication, he aspires to leave a lasting legacy in both academia and applied research bridging the gap between theoretical innovation and practical technological advancement.

Featured Publications

Raza, S. N., ur Rehman, H. M., Lee, S. G., & Choi, G. S. (2019). Artificial intelligence-based camera calibration. 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), 32. IEEE.

Nagulapati, V. M., ur Rehman, H. M. R., Haider, J., Qyyum, M. A., Choi, G. S., & Lim, H. (2022). Hybrid machine learning-based model for solubilities prediction of various gases in deep eutectic solvent for rigorous process design of hydrogen purification. Separation and Purification Technology, 298, 121651.

ur Rehman, H. M. R., On, B. W., Ningombam, D. D., Yi, S., & Choi, G. S. (2021). QSOD: Hybrid policy gradient for deep multi-agent reinforcement learning. IEEE Access, 9, 129728–129741.

ur Rehman, H. M. R., Saleem, M., Jhandir, M. Z., & Hafiz, H. G. I. A. (2025). Detecting hate in diversity: A survey of multilingual code-mixed image and video analysis. Journal of Big Data, 12(1), Article 5.

Younas, R., ur Rehman, H. M. R., Lee, I., On, B. W., Yi, S., & Choi, G. S. (2025). Sa-MARL: Novel self-attention-based multi-agent reinforcement learning with stochastic gradient descent. IEEE Access, 13, Article 5.

Khan, N. U., & ur Rehman, H. M. R. (2025). Real time signal decoding in closed loop brain computer interface for cognitive modulation. Ubiquitous Technology Journal, 1(1), 32–39.

ur Rehman, H. M. R., Haider, S. A., Faisal, H., Yoo, K. Y., Jhandir, M. Z., & Choi, G. S. (2025). A novel framework for Saraiki script recognition using advanced machine learning models (YOLOv8 and CNN). IEEE Access, 13, Article 2.

Qingyuan Li | Labor Economics | Best Researcher Award

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Dr. Qingyuan Li | Labor Economics | Best Researcher Award 

Dr. Qingyuan Li | Institute of Ethnology and Anthropology (IEA), Chinese Academy of Social Sciences (CASS) | China

Dr. Qingyuan Li is a Doctor of Economics from the University of the Chinese Academy of Social Sciences (UCASS) and a Postdoctoral Fellow at Peking University (PKU). His research interests lie at the intersection of labor economics and digital economics, with a strong interdisciplinary orientation spanning economics, sociology, and demography. Dr. Li has authored and co-authored 11 journal papers in prestigious SSCI and CSSCI indexed journals, addressing critical issues such as population aging, fertility, employment, income distribution, and health, while also leading six research projects and participating in national-level studies on population and aging strategies. His recent publications in Economic Modelling, Journal of Financial Research, Population Journal, and Management Review examine how digital infrastructure and Internet use influence household labor supply, financial behavior, and gender role attitudes, offering valuable empirical insights for China’s socio-economic transformation. He has also contributed to understanding the distributed effects of education on health and the moral hazard mechanisms in targeted poverty alleviation, advancing policy-oriented research in inclusive and sustainable development. His collaborative works have explored how digitalization empowers rural prosperity, family well-being, and youth employment, forming an evidence base for digital economy policymaking. With a growing body of influential publications, Dr. Li has earned over 300 citations and an h-index of 8, reflecting the impact and relevance of his research in both domestic and international academia. He has also authored two books, contributed to interdisciplinary studies on digital divides and digital dividends, and provided critical insights into the socio-economic dimensions of aging and digital transformation. In addition to his academic work, he has undertaken two consultancy projects and collaborated with leading research institutions, including the National School of Development at PKU and the Institute of Population and Labor Economics (IPLE) at CASS. As a member of the PKU Center for Healthy Aging and Development and the Health and Elderly Care Branch of the Chinese Society of Labor Economics, Dr. Li remains deeply engaged in advancing scholarly and policy dialogues on labor dynamics, digital inclusion, and social welfare in an era of rapid technological change and demographic transition.

Profile: Orcid 

Featured Publications

Dong, Y., & Li, Q. (2025). Fertility policy and household labor supply: Evidence from China’s universal two-child policy. Economic Modelling, 132, 107345.

Ivan Marovic | Project Management | Best Researcher Award 

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Prof. Dr. Ivan Marovic | Project Management | Best Researcher Award 

Prof. Dr. Ivan Marovic | University of Rijeka, Faculty of Civil Engineering | Croatia

Prof. Dr. Ivan Marovic is a distinguished academic with over two decades of experience in civil engineering, progressing from research assistant to full professorship at the University of Rijeka, Croatia. His expertise lies in Project Management with a particular focus on management information systems, multi-criteria decision analysis, and soft computing methods applied to civil engineering challenges. He has been recognized with numerous prestigious awards, including the Best Doctoral Thesis Award by the Croatian Association of Civil Engineers, the Vera Johanides Award by the Croatian Academy of Technical Sciences, and the Global Peer Review Award (Clarivate Analytics) for ranking among the top 1% of reviewers worldwide in Environment and Ecology as well as in Cross-Field research. Prof. Marović has demonstrated exceptional leadership in research, having led and participated in multiple national and international projects such as “Development of performance management model for construction projects based on soft computing methods (PerfMAN),” “CRESCO Adria,” “GAIA COFUND,” and several University of Rijeka-funded initiatives focusing on construction project optimization, climate adaptation, and infrastructure performance. His prolific academic output includes 40 Scopus-indexed and 38 Web of Science-indexed publications, achieving 457 citations (Scopus), 383 citations (WoS), and h-indices of 13 and 11, respectively, reflecting a consistent contribution to advancing sustainable construction and project management methodologies. His editorial involvement spans guest editorships in Sustainability and Applied Sciences, and membership on the editorial board of Advances in Civil and Architectural Engineering. As an active member of numerous scientific committees across Europe including OTMC, PrometheeDays, and DBMC conferences he has contributed to shaping the discourse in civil engineering research. Beyond academia, he has been actively engaged in consultancy and innovation-driven collaborations, notably co-investigating the award-winning “Innovative Connector for Joining Thin-Walled Steel C-Profile Structural Elements,” which received a silver medal at the ARCA International Exhibition for Innovation. His professional memberships include the Croatian Operational Research Society and the Croatian Association of Construction Management. A dedicated mentor, he has supervised over 45 bachelor’s and master’s theses and one doctoral dissertation. For his outstanding academic, research, and industry contributions, Prof. Marović continues to be recognized nationally and internationally as a leading figure in civil engineering project management and sustainable infrastructure development.

Profiles: Scopus | Orcid | Google Scholar | Staff Page

Xianglin Dai | Agricultural and Biological Sciences | Best Researcher Award

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Prof. Xianglin Dai | Agricultural and Biological Sciences | Best Researcher Award

Prof. Xianglin Dai | Hebei Academy of Agriculture and Forestry Sciences | China

Prof. Xianglin Dai is an accomplished Associate Professor at the Institute of Coastal Agriculture, Hebei Academy of Agriculture and Forestry Sciences, where he has made notable contributions to agricultural and environmental research. He serves as a Committee Member of the Nutrient Cycling Committee of the Chinese Society of Plant Nutrition and Fertilizers and as a Guidance Expert for the Compilation of Achievements for the Third National Soil Census in Hebei Province, reflecting his influence in advancing soil and nutrient management practices in China. Prof. Dai has successfully led more than six major research projects, including the Hebei Natural Science Foundation General Project, the Hebei Academy of Agriculture and Forestry Sciences Innovation Talent Construction Project, the Tibet Autonomous Region Natural Science Foundation Youth Project, the Tangshan City Science and Technology Plan Project, and the Open Project of the State Key Laboratory of Barley and Yak Germplasm Resources and Genetic Improvement jointly supported by the Ministry and Province. His interdisciplinary research focuses on soil fertility, nutrient cycling, sustainable agriculture, and ecosystem productivity in coastal and high-altitude regions, providing critical insights into optimizing soil health and crop performance under changing climatic conditions. As first author or corresponding author, he has published more than 10 peer-reviewed papers in high-impact international and national journals such as Soil Biology and Biochemistry, Geoderma, Soil and Tillage Research, European Journal of Soil Biology, Applied Soil Ecology, Chinese Journal of Eco-Agriculture, and Journal of Applied and Environmental Biology, which are widely recognized for their scientific rigor and applied relevance. His research outputs have been cited extensively, accumulating over 350 citations with an h-index of 8 on Google Scholar, highlighting his growing academic impact in soil science and environmental sustainability. Beyond research, Prof. Dai has demonstrated innovation and knowledge transfer by securing 2 authorized patents as first inventor and 2 registered software copyrights, supporting technological applications in agricultural resource management. He has also authored 1 monograph as editor-in-chief and contributed to 2 additional scholarly books, further strengthening the dissemination of scientific knowledge. Through his dedication to soil ecology, nutrient dynamics, and sustainable agricultural systems, Prof. Dai continues to play a key role in advancing both theoretical research and its practical implementation, contributing to environmental conservation, agricultural modernization, and food security in China.

Profile: Orcid

Featured Publications

Dai, X., Song, D., Guo, T., Cui, J., Zhou, W., Huang, S., Shen, J., Liang, G., & He, P. (2022). Organic amendment regulates soil microbial biomass and activity in wheat–maize and wheat–soybean rotation systems. Agriculture, Ecosystems & Environment, 340, 107974.

Dai, X., Liu, Y., Sun, J., Zhao, Z., Wang, X., & Zhang, G. (2022). Response of soil bacterial community structure and function under two salt-tolerant plants in a coastal saline soil area of eastern Hebei province of China. International Journal of Phytoremediation, 24(9), 911–922.

Dai, X., Cui, J., Song, D., Xu, X., He, P., Wang, X., Liang, G., Zhou, W., & Zhu, P. (2021). Effects of long-term cropping regimes on SOC stability, soil microbial community and enzyme activities in the Mollisol region of Northeast China. Applied Soil Ecology, 166, 103941.

Dai, X., Song, D., Guo, Q., Zhou, W., Liu, G., Ma, R., Liang, G., He, P., & Sun, G. (2021). Predicting the influence of fertilization regimes on potential N fixation through their effect on free-living diazotrophic community structure in double rice cropping systems. Soil Biology and Biochemistry, 155, 108220.

Dai, X., Guo, Q., Song, D., Zhou, W., Liu, G., Liang, G., He, P., Sun, G., & Yuan, F. (2021). Long-term mineral fertilizer substitution by organic fertilizer and the effect on the abundance and community structure of ammonia-oxidizing archaea and bacteria in paddy soil of south China. European Journal of Soil Biology, 103, 103288.

Dai, X., Song, D., Zhou, W., Liu, G., Liang, G., He, P., Sun, G., Yuan, F., & Liu, Z. (2021). Partial substitution of chemical nitrogen with organic nitrogen improves rice yield, soil biochemical indicators and microbial composition in a double rice cropping system in south China. Soil and Tillage Research, 206, 104753.

Dai, X., Zhou, W., Liu, G., Liang, G., He, P., & Liu, Z. (2019). Soil C/N and pH together as a comprehensive indicator for evaluating the effects of organic substitution management in subtropical paddy fields after application of high-quality amendments. Geoderma, 337, 1111–1119.

Veselina Chakarova | Electrochemistry and Corrosion | Best Researcher Award

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Dr. Veselina Chakarova | Electrochemistry and Corrosion | Best Researcher Award

Institute of Physical Chemistry – Bulgarian Academy of Sciences | Bulgaria

Ms. Veselina Petrova Chakarova is an accomplished researcher and chemist at the Institute of Physical Chemistry, Bulgarian Academy of Sciences (BAS), with over 14 years of scientific experience in the field of electrochemistry and corrosion. Her research primarily focuses on the development, optimization, and characterization of functional nickel-based coatings, particularly Ni–P and Ni–Co–P systems, applied to various substrates for enhanced corrosion resistance, catalytic efficiency, and surface functionality. A graduate of the University of Chemical Technology and Metallurgy in Sofia, Bulgaria, Ms. Chakarova specialized in Electrochemistry and Corrosion, laying the foundation for her strong experimental and theoretical background. Since joining the Institute of Physical Chemistry, she has significantly contributed to advancing materials science through the design of innovative chemical solutions for the electroless deposition of Ni–P coatings on both flexible and rigid polymer substrates and, more recently, on steel surfaces. These coatings have demonstrated superior properties suited for multiple industrial and technological applications. Her research achievements are evidenced by 14 publications in high-impact refereed journals, including a notable article in Catalysis Today, where she reported the synthesis and catalytic behavior of Ni–Co–P coatings. Additionally, her doctoral dissertation, titled “Obtaining and Characterizing Ni–P Coatings on Different Types of Substrates,” has become a reference point for future researchers in the field of functional coatings. Ms. Chakarova’s research portfolio includes 12 completed and ongoing scientific projects, several of which have been funded by the Bulgarian National Science Fund and the Ministry of Education and Science. Between 2017 and 2019, she led a project under the Young Scientists and Postdoctoral Researchers Program (“Young Scientists” module), and from 2020 to 2024, she has been a key beneficiary of the Young Scientists Program, promoting innovation in electrochemical surface modification. Her leadership in these projects has fostered the growth of early-career researchers and strengthened Bulgaria’s scientific capabilities in materials chemistry. Her scientific influence extends to her citation index of 71 in Scopus and other international databases, underscoring the recognition and relevance of her research within the global scientific community. Moreover, she has one published patent and another under process, reflecting her commitment to translating research outcomes into tangible innovations with practical impact. Ms. Chakarova’s current focus includes collaborative initiatives, particularly with TÜBİTAK (The Scientific and Technological Research Council of Turkey), aiming to develop advanced coatings with superior corrosion protection and catalytic performance. Her dedication to interdisciplinary collaboration, precision experimentation, and sustainable technological advancement highlights her as a promising leader in materials science and electrochemistry. Through her continuous research, mentorship, and innovation-driven mindset, Ms. Veselina Petrova Chakarova exemplifies the values of scientific excellence and impact. Her contributions to electrochemical coating technologies and corrosion science not only enhance Bulgaria’s research reputation but also align with the global goals of sustainable industrial advancement and technological innovation.

Profile: Orcid

Featured Publications

Chakarova, V. (2025). Evaluating the bifunctional properties towards HER and OER of NiCo electrodeposited coatings: Combined influence of support, Ni/Co ratio, and phosphorus doping. Catalysis Today, 438, Article 115495. https://doi.org/10.1016/j.cattod.2025.115495

Chakarova, V. (2023). Electrocatalytic properties of electroless Ni–P coatings towards hydrogen evolution reaction in alkaline solution: Ni–P coatings deposited on steel substrate at different concentrations of sodium hypophosphite. Electrocatalysis, 14(2), 276–287. https://doi.org/10.1007/s12678-022-00791-x

Chakarova, V. (2021). Corrosion behavior of the ζ-CrZn₁₃ phase obtained by annealing an electrodeposited Zn-Cr coating. Electrochemistry Communications, 123, 106904. https://doi.org/10.1016/j.elecom.2020.106904

Chakarova, V. (2020). Pre-treatment of dielectrics and technological process for deposition of chemical copper layers from copper solution with improved ecological impact. Transactions of the Institute of Metal Finishing, 98(2), 73–80. https://doi.org/10.1080/00202967.2020.1718941

Chakarova, V. (2019a). Hydrogen evolution reaction on electroless Ni–P coatings deposited at different pH values. Bulgarian Chemical Communications, 51(3), 312–318.

Chakarova, V. (2019b). Influence of annealing temperature on ζ-CrZn₁₃ formation in electrodeposited Zn–Cr coatings. Surface Engineering, 36(5), 419–427. https://doi.org/10.1080/02670844.2019.1598023

Chakarova, V. (2019c). Study on the degreasing and etching operations in the pre-treatment of ABS dielectric aimed at obtaining quality chemically deposited nickel-phosphorus coatings. Transactions of the Institute of Metal Finishing, 97(4), 171–179. https://doi.org/10.1080/00202967.2019.1630183