Julia Wood | Urban Planning | Best Researcher Award

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Ms. Julia Wood | Urban Planning | Best Researcher Award

University of Cape Town | South Africa

Ms. Julia Wood is an accomplished biodiversity and conservation specialist with extensive experience in managing sensitive ecosystems and promoting sustainable development. Her career spans leadership roles in municipal environmental management, applied ecological research, and conservation advocacy, reflecting a strong commitment to safeguarding South Africa’s unique natural heritage. With academic training including a BSc (Botany, Zoology), BSc Honours in terrestrial ecology, and an MSc in Botany focused on the natural vegetation of the Robertson Karoo, she is currently advancing her expertise through a PhD in Environmental and Geographical Studies. Her research examines critical factors that influence effective conservation action, addressing real-world implementation challenges in biodiversity planning and environmental governance. Throughout her tenure with the City of Cape Town—currently as Manager of Biodiversity Management—she has overseen 20 protected areas and coordinated the execution of strategic biodiversity initiatives, including the Local Biodiversity Strategy and Action Plan and fine-scale conservation plans. Her work integrates ecological protection with vital societal goals such as job creation, skills development, and environmental education, ensuring conservation efforts deliver measurable community benefit. Julia’s contributions include numerous publications, project leadership roles at WWF-SA’s Table Mountain Fund, and significant involvement in watershed and ecosystem-based management across diverse natural landscapes. Her collaborations extend across governmental agencies, non-profit organizations, and community stakeholders, strengthening regional responses to climate change, ecological restoration, and urban development pressures. An award-winning professional, she is respected for advancing evidence-based conservation strategies that enhance resilience and protect biodiversity in one of the world’s most ecologically significant regions. This continued dedication demonstrates her capacity to motivate progress, build partnerships, and contribute meaningfully to global environmental sustainability.

Profile: Scopus
Publications

Coordinating invasive alien species management in a biodiversity hotspot: The CAPE Invasive Alien Animals Working Group. Bothalia. 2020

Guangyang Liu | Environmental Risk Assessment | Research Excellence Award

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Prof. Guangyang Liu | Environmental Risk Assessment | Research Excellence Award

Deputy director | Chinese Academy of Agricultural Sciences | China

Prof. Guangyang Liu is a Research Fellow, Ph.D. supervisor, and CAAS Young Talent at the Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences (CAAS). His research focuses on nutritional quality and safety control of vegetable products, integrating multidisciplinary approaches across analytical chemistry, horticulture, nanoscience, and materials science. His work aims to address global challenges in food safety, sustainable agriculture, and public health through innovative nanotechnology-enabled solutions. Dr. Liu has made notable contributions to the development of advanced porous organic nanomaterials, the detection and control of agricultural chemical contaminants, and the enhancement of nutritional quality in vegetables. He has successfully established a comprehensive technology system that supports new nanomaterial creation, rapid pollutant detection, controlled removal, and the separation and purification of bioactive compounds. His research outcomes have significantly advanced risk assessment, quality evaluation, and safety assurance in vegetable production. He has published 129 academic papers, including 90 SCI papers, with 56 as first or corresponding author in leading journals such as Chemical Engineering Journal, Journal of Hazardous Materials, TrAC Trends in Analytical Chemistry, and Food Chemistry. His publications have achieved a cumulative impact factor exceeding 395, with 21 papers in journals of impact factor above 8, and 12 above 10. His work has earned two ESI Highly Cited Papers and an H-index of 32. Dr. Liu holds 22 authorized invention patents, has edited multiple monographs, and contributed to national agricultural standards. His achievements have been widely recognized, including the National Commercial Science and Technology Progress Award (First Prize), CAAS Young Talent honors, Sigma Xi Full Membership, and listing among the World’s Top 2% Scientists. He serves on expert panels, editorial boards, and international review committees, reinforcing his influence in advancing global food safety and agricultural sustainability.

Research Profiles: Scopus | ORCID
Publications

Analysis of microstructure properties of Ni–Fe MOFs and their influence on selective recognition of single and binary dye systems. npj Clean Water. (2 citations)

Enhanced insecticidal activity and bioavailability of thiacloprid from pH-responsive porous MPN(Fe)@ZIF-8 nanocarrier. Journal of Cleaner Production.

Coral-like magnetic metal–organic framework for selective adsorption and detection of thiabendazole in tomato and Chinese cabbage samples. Foods.

Matrix interference of vegetable on enzyme-linked immunosorbent assay for parathion residue detection. Foods.

Cheng Yan | Sustainable Development | Best Researcher Award

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Prof. Dr. Cheng Yan | Sustainable Development | Best Researcher Award

Deputy Dean of the School of Artificial Intelligence | Jiangxi Normal University | China

Prof. Dr. Cheng Yan is a Professor and doctoral supervisor specializing in intelligent information processing, deep learning and affective computing, artificial intelligence and big data, and intelligent education. She earned her PhD from Tongji University and completed a postdoctoral fellowship at the university’s Computer Science and Technology Mobile Station. She has also undertaken academic visiting research at California State University, Fullerton (CSUF), in the United States. Since 2012, she has held the rank of professor. Dr. Cheng currently serves as Vice Dean of the School of Artificial Intelligence at Jiangxi Normal University, overseeing research and graduate education. She is also Director of the Jiangxi Provincial Key Laboratory of Intelligent Information Processing and Affective Computing, as well as a recognized provincial academic and technical leader. She has been selected for the national “Western Light” Talent Program. She holds multiple professional roles, including committee member and Deputy Secretary-General of the Intelligent Education Committee of the Chinese Association of Automation, and Chair of the Intelligent Education Committee of the Jiangxi Digital Economy Society. She is an expert reviewer for the National Natural Science Foundation of China, National Social Science Fund projects, degree thesis evaluations of the Ministry of Education, and several provincial scientific and technological programs. She serves as reviewer and editorial board member for multiple leading domestic and international journals. Dr. Cheng has led four national-level research projects and over twenty major or key provincial projects, and has participated in national key research initiatives such as the “Tenth Five-Year” major project on network education. She has published over 70 SSCI, SCI, EI, and CSSCI-indexed papers, authored two monographs, and supervised students who have received national and provincial scholarships and academic honors. Her work has earned numerous awards, including Best Research Award, Young Scientist Award, provincial first prizes in teaching and scientific research, and multiple patents and software copyrights. Her research continues to contribute significantly to the advancement of intelligent education and artificial intelligence applications.

Profile: Scopus
Publications

An expensive multi-objective evolutionary algorithm based on grid and relation learning. Applied Soft Computing.

Study on interpretable shallow class activation mapping algorithm based on spatial weights and inter-layer correlation. Computer Science China.

Semantic injection and multi-scale cross-axis attention-based portrait segmentation model. Signal, Image and Video Processing.

Mehran Akhavan | Tall building | Best Researcher Award

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Dr. Mehran Akhavan | Tall building | Best Researcher Award

Islamic Azad University | Iran

Dr. Mehran Akhavan Salmassi is a dedicated structural engineering researcher whose work focuses on advancing the safety, resilience, and performance of modern infrastructure systems. Holding a Ph.D. in Structural Engineering from the Islamic Azad University, Semnan Branch, he has developed a strong academic and research profile grounded in innovation, analytical rigor, and global engagement. His core areas of expertise include tall building engineering, structural control, and the development of high-performance structural systems capable of withstanding dynamic loads and extreme environmental conditions. Over the years, Dr. Salmassi has contributed significantly to the field through 18 peer-reviewed publications, reflecting both theoretical advancements and practical engineering solutions. His research also includes three recognized novelties, demonstrating his commitment to pioneering new methods and expanding current engineering knowledge. Dr. Salmassi actively contributes to the scientific community as a reviewer for three international journals, supporting the peer-review process and ensuring high-quality scholarly dissemination. His reputation as a knowledgeable and engaging scholar has earned him invitations as a speaker and distinguished speaker in more than 20 international conferences, where he has presented research findings, shared technical insights, and collaborated with experts across the globe. Through his growing academic footprint, he continues to foster meaningful collaborations that bridge research, industry practice, and societal needs. His work emphasizes the importance of innovation in structural engineering, particularly in the design of safe and sustainable tall buildings for rapidly developing urban environments. Driven by a passion for scientific excellence and public safety, Dr. Salmassi aims to contribute solutions that not only advance engineering practice but also inspire emerging researchers in the field.

Profile: Google Scholar
Publications

Akhavan Salmassi, M., Kheyroddin, A., & Hemmati, A. (2020). Seismic behavior of end walls in RC tall buildings with torsional irregularity. Magazine of Civil Engineering, 97(07).

Salmassi, M. A., Kheyroddin, A., & Hemmati, A. (2024). Enhancement of the performance of two tall buildings with end shear walls using nonlinear time history analysis: A case study. Iranian Journal of Science and Technology, Transactions of Civil Engineering.

Akhavan Salmassi, M., Kheyroddin, A., & Hemmati, A. (2023). Evaluation of reinforced concrete tall buildings with end shear walls subjected to sequences far from the fault. Scientia Iranica.

Kheyroddin, A., & Akhavan Salmassi, M. (2018). Effect of end walls in tall buildings with square plan and flexural concrete frames under earthquake. In 7th National and 3rd International Conference on Modern Materials and Structural Systems.

Akhavan Salmassi, M., Kheyroddin, A., & Hemmati, A. (2021). Seismic behavior of tall buildings with end shear walls and opening. Journal of Seismology and Earthquake Engineering, 23(2), 55–70.

Akhavan Salmassi, M., Gerami, M., & Heidari Tafreshi, A. (2019). Evaluation of flexible steel frame structures with post-tensioned cables to sequences far from fault. Journal of Structural and Construction Engineering, 6(Special Issue 3), 221–234.

Alireza Javid | Concrete and FRP-strengthened structures | Research Excellence Award

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Mr. Alireza Javid | Concrete and FRP-strengthened structures | Research Excellence Award

Graduate Researcher in Structural Engineering | Sharif University of technology | Iran

Alireza Javid is a civil and structural engineering researcher whose work centers on sustainable construction materials, structural health monitoring, and the integration of advanced machine learning techniques into structural assessment and design. He holds an M.Sc. in Structural Engineering from Sharif University of Technology, where his research investigated the effects of high temperatures on cement bonding and pozzolanic concrete. His scholarly contributions reflect a strong interdisciplinary foundation, bridging experimental mechanics, data-driven modeling, and computational optimization. Javid has authored multiple peer-reviewed journal articles in high-impact international outlets, with published work addressing machine learning–based predictions of concrete compressive strength, bond behavior in FRP–timber systems under thermal cycling, high-temperature concrete overlay interactions, and the mechanical characterization of industrial by-product concrete. His publications collectively exceed 40 citations, demonstrating growing recognition within the structural materials and AI-in-construction communities. His research also extends to ultrasonic pulse velocity prediction, temperature-dependent performance of fiber-reinforced concrete, and microstructural deterioration of FRP composites in aggressive environments. Several manuscripts under review explore impact resistance of stabilized rammed earth, acid-rain durability of composite materials, and environmental effects on geopolymer concretes. In addition, he is preparing works on crack simulation, nano-engineered materials, and deep-learning-based crack classification, highlighting his expanding focus on intelligent infrastructure systems. As a research assistant at Sharif University of Technology, Javid has developed high-accuracy predictive models using CatBoost, gradient boosting, and novel optimization algorithms, achieving R² values up to 0.99 across various structural datasets. His work consistently emphasizes societal needs such as sustainability, material efficiency, and resilience under extreme conditions.

Profile: Google Scholar
Publications

Javid, A., & Toufigh, V. (2024). Utilizing ensemble machine learning and gray wolf optimization to predict the compressive strength of silica fume mixtures. Structural Concrete, 25(5), 4048–4074.

Javid, A., Javid, E., & Toufigh, V. (2025). High-temperature bond strength evaluation of concrete overlays with industrial by-products: Experimental and analytical approaches using machine learning. Engineering Applications of Artificial Intelligence, 153, 110954.

Lotfalipour, F., Javid, A., & Toufigh, V. (2025). Boosting algorithms for predicting the bond properties of timber and fiber reinforced polymer (FRP) under thermal cycling using single-lap shear tests. European Journal of Wood and Wood Products, 83(2), 83.

Mohsennia, E., Javid, A., & Toufigh, V. (2025). Advanced machine learning techniques for predicting compressive strength and ultrasonic pulse velocity of concrete incorporating industrial by-products. Case Studies in Construction Materials, e04801.

Javid, A., Kamali, H., & Toufigh, V. (2025). Compressive strength prediction of fiber-reinforced concrete under varied temperature conditions using machine learning. Construction and Building Materials, 504, 144648.

Majdi Benamara | Environmental Engineering | Breakthrough Research Award

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Dr. Majdi Benamara | Environmental Engineering | Breakthrough Research Award

Postdoc | University of Minho | Portugal

Dr. Majdi Benamara is a dedicated researcher in physics whose work spans advanced functional materials, nanostructured oxides, and energy‐related applications. With a publication record of 22 peer-reviewed articles, his contributions demonstrate strong expertise in semiconductor metal oxides, ferroelectric thin films, photocatalysts, and gas-sensing materials. His research consistently integrates experimental synthesis, structural and electrical characterization, and application-driven performance evaluation. Over the years, he has collaborated with multidisciplinary teams across Switzerland, Portugal, Belgium, Spain, and Tunisia, contributing to internationally relevant projects focused on sustainable materials and next-generation electronic devices. His recent appointment as a researcher at EMPA – Swiss Federal Laboratories for Materials Science and Technology reflects his growing impact in advanced materials engineering, particularly in building energy materials and hybrid oxide systems. Previous research experience at the University of Minho involved ferroelectricity in binary oxide thin films for high-performance capacitors, further solidifying his expertise in electronic materials and thin-film technologies. Earlier roles and internships at Materia Nova (Belgium), the University of Aveiro (Portugal), and the University of Sevilla (Spain) contributed to his strong technical foundation in sol–gel chemistry, supercritical drying, spark plasma sintering, pulsed laser deposition, and ion-beam sputtering. Dr. Benamara’s work has generated advances in gas sensors for environmental monitoring, visible-light photocatalysts for pollutant degradation, and doped oxide systems for electronic and dielectric applications. His collaborations with leading researchers and laboratories have strengthened his scientific visibility and enabled the development of innovative materials addressing global challenges in air quality, environmental remediation, and sustainable energy technologies. Through his consistent scholarly output and broad experimental capabilities, he continues to contribute significantly to the progress of materials science and applied physics on an international scale.

Profile: Google Scholar
Publications

1. Bembibre, A., Benamara, M., Hjiri, M., Gómez, E., Alamri, H. R., Dhahri, R., & others. (2022). Visible-light driven sonophotocatalytic removal of tetracycline using Ca-doped ZnO nanoparticles. Chemical Engineering Journal, 427, 132006.

2. Jaballah, S., Benamara, M., Dahman, H., Ly, A., Lahem, D., Debliquy, M., & El Mir, L. (2020). Effect of Mg-doping ZnO nanoparticles on detection of low ethanol concentrations. Materials Chemistry and Physics, 255, 123643.

3. Jaballah, S., Benamara, M., Dahman, H., Lahem, D., Debliquy, M., & El Mir, L. (2020). Formaldehyde sensing characteristics of calcium-doped zinc oxide nanoparticles-based gas sensor. Journal of Materials Science: Materials in Electronics, 31(11), 8230–8239.

4. Benamara, M., Gómez, E., Dhahri, R., & Serrà, A. (2021). Enhanced photocatalytic removal of cyanotoxins by Al-doped ZnO nanoparticles with visible-LED irradiation. Toxins, 13(1), 66.

5. Benamara, M., Massoudi, J., Dahman, H., Dhahri, E., El Mir, L., Ly, A., & others. (2020). High response to sub-ppm level of NO₂ with 50% RH of ZnO sensor obtained by an auto-combustion method. Journal of Materials Science: Materials in Electronics, 31(17), 14249–14260.

Meiqian Wang | Geotechnical Engineering | Best Innovation Award

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Prof. Meiqian Wang | Geotechnical Engineering | Best Innovation Award

Professor | Kunming University of Science and Technology | Best Innovation Award

Prof. Meiqian Wang is a researcher and faculty member at Kunming University of Science and Technology, specializing in geotechnical mechanics, geological engineering, and engineering project management. His work focuses on the mechanical behavior, sandification mechanisms, and disaster-control technologies of sandy dolomite, contributing to major infrastructure projects in Southwest China. He has led two research projects and participated in several significant initiatives, including a major science and technology project of the Yunnan Provincial Science and Technology Department, multiple National Natural Science Foundation projects, open fund studies, and enterprise-oriented engineering investigations. During his doctoral period, he achieved notable academic productivity, publishing seven first-author papers, including five SCI-indexed articles—with one in a top-tier journal—and one core Chinese publication. His work has also extended to engineering geology, machine-learning-based rock property evaluation, and structural stability analyses in complex geological conditions. In addition to scholarly publications, he has contributed substantially to scientific and technological innovation, holding one invention patent, five utility model patents, and four computer software copyrights related to rock mechanics testing, data acquisition, and analysis systems. He has collaborated extensively with interdisciplinary teams on tunnel engineering, rock mass behavior, and large water-diversion project studies, further enhancing the scientific understanding of rock sandification processes. His professional contributions include serving as a journal editorial board member and reviewer for several SCI journals in civil engineering and geosciences, reflecting his growing international academic presence. His research has delivered tangible societal benefits by supporting safer, more efficient design and construction practices in high-risk geological environments, thereby advancing regional infrastructure resilience and sustainability.

Profiles: ORCID
Publication:

Wang, M., Xu, W., Mu, H., Mi, J., Wu, Y., & Wang, Y. (2022). Study on construction and reinforcement technology of dolomite sanding tunnel. Sustainability, 14(15)

Lianyi Guo | Climate Change Mitigation and Adaptation | Research Excellence Award

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Dr. Lianyi Guo | Climate Change Mitigation and Adaptation | Research Excellence Award

Lecturer | Yangzhou University | China

Dr. Lianyi Guo is an emerging scholar in climate-system research whose work focuses on the attribution and projection of extreme climate change, with a strong emphasis on understanding nonlinear rainfall responses to large-scale atmospheric circulation patterns. With a growing research portfolio that includes leading or participating in eight national and provincial research projects, Guo has established a solid foundation in advancing methodologies for diagnosing climate extremes and improving future climate projections. His contributions include developing a novel analytical framework that bridges dynamic and thermodynamic processes to interpret changes in summer rainfall patterns, particularly across China, enabling more accurate attribution of observed hydrometeorological variations to anthropogenic influences. He has authored eight SCI-indexed journal articles, including publications in high-impact outlets, and his current citation record and h-index of 6 reflect a promising upward trajectory. Beyond publications, his engagement in two consultancy or industry-linked projects demonstrates an ability to translate scientific insight into practical climate-related applications. Guo’s collaborations across national research institutes further strengthen the interdisciplinary relevance of his work, supporting advances in climate diagnostics, model evaluation, and regional climate risk assessment. His ongoing studies aim to refine constraint-based projections of extreme rainfall, offering potential benefits for disaster preparedness, water-resource management, and climate-policy development. The scientific rigor, methodological innovation, and applicability of Guo’s research underline his significant contribution to the field and position him as a valuable contributor to global climate-science efforts, with strong potential for continued impact through high-quality publications, collaborative research, and the development of improved tools for understanding and predicting climate extremes.

Profiles: Scopus | ORCID | Research Gate 
Publications:

Guo, L., Shi, Y., & Zhao, Y. (2023). Future projections of extreme integrated water vapor transport and population exposure over the Asian monsoon region. Earth’s Future.

Guo, L., Jiang, Z., Li, L., & Wang, H. (2022). Increase of future summer rainfall in the middle and lower reach of the Yangtze River Basin projected with a nonhomogeneous hidden Markov model. Geophysical Research Letters.

Guo, L. (2022). Comparison of impact and water vapor characteristics between two types of floods in Eastern China. Environmental Research Letters.

Guo, L. (2020). Projected precipitation changes over China for global warming levels at 1.5 °C and 2 °C in an ensemble of regional climate simulations: Impact of bias-correction algorithms. Climatic Change.

Guo, L., Jiang, Z., Ding, M., Chen, W., & Li, L. (2019). Downscaling and projection of summer rainfall in Eastern China using a nonhomogeneous hidden Markov model. International Journal of Climatology.

Yang Yunpeng | Geotechnical Engineering | Research Excellence Award

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Assoc. Prof. Dr. Yang Yunpeng | Geotechnical Engineering | Research Excellence Award

Yangtze University | China

Assoc. Prof. Dr. Yang Yunpeng is a dedicated early-career scholar and Specially Appointed Associate Professor at the College of Geosciences, Yangtze University, recognized for his emerging contributions to the field of geological hazards and mountain disaster dynamics. His research primarily focuses on the mechanisms, evolution, and monitoring of landslides, debris flows, rock avalanches, and snow avalanches, with an emphasis on disaster-chain processes in seismically active regions. He has developed expertise in seismic-signal-based monitoring and early warning frameworks, experimental flume testing, debris-flow dynamics, and disaster-risk mitigation technologies. Dr. Yang has published over ten research articles, including nine SCI-indexed papers, with four as first or corresponding author in reputable international journals such as Engineering Geology, JGR: Earth Surface, and Landslides. His work has clarified the chain-inducing mechanisms of seismic landslide–debris-flow sequences, advanced the understanding of debris-flow impact dynamics, and contributed novel insights into sediment transport transitions under seismic forcing. In addition to publications, he has participated in the development of multiple national invention patents related to disaster simulation, debris-flow hazard mitigation, and engineering modeling technologies, demonstrating both scientific innovation and practical applicability. Dr. Yang collaborates actively with interdisciplinary teams involving experts in seismology, geomorphology, engineering geology, and geotechnical engineering, enabling integrative approaches to mountain-hazard research. His contributions support national needs in major engineering construction and disaster-risk reduction, with societal impacts spanning improved hazard early-warning capabilities, enhanced understanding of disaster chains, and the development of protective strategies for vulnerable mountainous regions. Through rigorous research, international engagement, and commitment to scientific advancement, Yang Yunpeng continues to establish himself as a promising researcher contributing valuable knowledge to global geohazard prevention and sustainable development.

Profile: Scopus
Publication

Physical model experiment of rainfall-induced instability of a two-layer slope: Implications for early warning. Landslides. (2024)

Dongwook Kim | Construction Management | Best Researcher Award

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Dr. Dongwook Kim | Construction Management | Best Researcher Award

DL E&C | South Korea

Dr. Dongwook Kim is a distinguished civil engineer and senior manager at DL E&C’s Civil Smart Engineering Team, specializing in smart construction, Building Information Modeling (BIM), and modular infrastructure systems. He earned his Ph.D. in Civil Engineering from Chung-Ang University with exceptional academic performance, following master’s and bachelor’s degrees from the same institution. With over 18 years of professional and research experience, Dr. Kim has significantly contributed to the integration of digitalization, automation, and AI-based predictive maintenance in infrastructure engineering. His expertise spans modular composite structures, precast bridge systems, and machine learning applications for structural performance prediction. Dr. Kim has authored more than 25 SCI/SCIE-indexed papers and multiple domestic publications, and has contributed to three book chapters and several national patents on structural innovation and BIM applications. He has been a key technical advisor and committee member for leading Korean organizations such as the Ministry of Land, Infrastructure and Transport (MOLIT), Korea Institute of Civil Engineering and Building Technology (KICT), Korea Expressway Corporation (EX), and Korea National Railway (KR), helping develop BIM standards, digital construction guidelines, and smart infrastructure frameworks. His collaborative research includes international engagements with experts from Europe and Asia, fostering global knowledge exchange in smart civil engineering. Recognized for his contributions, Dr. Kim has received prestigious honors including the Ministerial Best Innovation Award (2021) and the International Young Scientist Best Researcher Award (2024), and has been listed in Marquis Who’s Who in the World for multiple consecutive years. His research continues to advance sustainable, data-driven infrastructure management and the implementation of AI-empowered digital twin technologies, contributing to the global transition toward resilient and intelligent civil engineering systems.

Profile: Scopus | ORCID
Publications:

Kim, D. (2025, September). Corrugated inner wall connections for composite Rahmen bridges: Advancing design and construction efficiency. KSCE Journal of Civil Engineering.

Kim, D., Matos, J., & Dang, S. N. (2025, February 23). Development of BIM platform for semantic data based on standard WBS codes. Buildings, 15(5), 711.