Ling Xu | Engineering | Young Scientist Award | 4273

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Assoc. Prof. Dr. Ling Xu | Engineering | Young Scientist Award

Teacher | Fuzhou University | China

Assoc. Prof. Dr. Ling Xu is an Associate Professor at the College of Civil Engineering, Fuzhou University, specializing in transportation infrastructure construction, pavement materials, and maintenance engineering. He holds a doctorate in Transportation Engineering, a visiting scholarship in civil infrastructure research, and a bachelor’s degree in Civil Engineering, providing a solid academic foundation in pavement mechanics, material behavior, and life-cycle performance. His professional experience includes contributing to national and industry-funded projects on polyurethane concrete runway overlays, rubberized asphalt durability, high RAP mixture cracking mechanisms, high-speed railway waterproofing layers, and flexible interlayer systems for airfield pavements. His research focuses on low-carbon pavement materials, road maintenance technologies, numerical simulation, data mining, image processing, and life-cycle analysis, leading to impactful publications in high-ranking international journals on asphalt modification, pavement sustainability, thermal-mechanical behavior, and innovative maintenance materials. Recognized with a Young Scientist Award, he has also contributed to the academic community through editorial and review activities, professional memberships, and active participation in interdisciplinary research collaborations.

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Featured Publications

Seyed Ali Ekrami Kakhki | Civil Engineering | Research Excellence Award

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Dr. Seyed Ali Ekrami Kakhki | Civil Engineering | Research Excellence Award

Semnan University | Iran

Dr. Seyed Ali Ekrami Kakhki, a distinguished Civil Engineering scholar at Semnan University, specializes in structural engineering with a focus on reinforced concrete structures and progressive collapse analysis. He earned his Ph.D. in Civil Engineering – Structural Engineering from Azad University of Semnan, following an M.Sc. in Structural Engineering from Tafresh State University and a B.Sc. from Islamic Azad University, Taft. Dr. Ekrami Kakhki has led and supervised major civil engineering projects, including urban metro construction, rural road development, and structural strengthening of residential and institutional buildings, demonstrating a combination of technical expertise and leadership in project management. His research centers on the progressive collapse of reinforced concrete frames, incorporating soil-structure interaction and sensitivity analysis to enhance structural resilience. He has published multiple peer-reviewed articles in high-impact JCR Q2 journals such as the International Journal of Concrete Structures and Materials and contributed to the Journal of Structural and Construction Engineering, advancing the understanding of structural stability under critical load conditions. Recognized for his academic excellence and leadership, Dr. Ekrami Kakhki actively contributes to the civil engineering community through editorial roles, peer review, and collaborative research, reflecting a sustained commitment to innovation and scholarly impact in structural engineering.

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Top 5 Featured Publications

 


Numerical Investigation of the Progressive Collapse of RC Wall-Frame Structures

– International Journal of Concrete Structures and Materials, 2023


Evaluation of Progressive Collapse of RC Frames Based on Sensitivity Index

– International Journal of Concrete Structures and Materials, 2022


Analysis of Electrical Engineering Systems

– Journal of Electrical Engineering, 2016


Perovskite-Type LaFeO3 & LaFeO3-CNTs Nanocrystals for Methanol Oxidation

– Published under Springer (Chemistry/Nanocatalysts)

Md Ataur Rahman | Mechanical Enginnering | Excellence in Research Award

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Prof. Md Ataur Rahman | Mechanical Enginnering | Excellence in Research Award

Professor | Eastern Michigan University | United States

Professor Md Ataur Rahman is a faculty member in the GameAbove College of Engineering and Technology at Eastern Michigan University, where his research centers on automotive engineering, electric mobility, and intelligent mechanical systems. His academic foundation includes a PhD in Automotive Engineering from Universiti Putra Malaysia, an Executive MBA in Techno-Entrepreneurship jointly awarded by Cranfield University and Universiti Teknologi Malaysia, and a Bachelor of Science in Mechanical Engineering from Chittagong University of Engineering and Technology. His research portfolio integrates advanced electric vehicle technologies, intelligent control systems, adaptive machine-learning models, and sustainable transportation solutions. He has contributed to the development of novel electric propulsion systems, energy-efficient drivetrains, smart supercapacitors, and intelligent gearboxes, supported by multidisciplinary collaborations and strong publication output. His work in prototype development and technology commercialization bridges academia and industry, informed by his experience in electric vehicle design, electrification consultancy, and automated tractor system innovation. He also provides leadership in research mentoring, grant proposal development, and engineering program enhancement, fostering impactful research culture and interdisciplinary innovation. A Chartered Engineer and active member of ASME and SAE, he is recognized for his contributions to advancing electric mobility research, intelligent mechanical design, and future-focused engineering technologies.

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Top 5 Featured Publications

 

Chang Soo Kim | Engineering | Best Researcher Award

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Prof. Chang Soo Kim | Engineering | Best Researcher Award

Professor | Pukyong National University | South Korea

Professor. Chang Soo Kim is a distinguished Full Professor in the Division of Computer and AI Engineering at PuKyong National University, recognized for his expertise in intelligent manufacturing systems, artificial intelligence, and computational optimization. He holds advanced degrees in computer science with specialization in AI-driven optimization and machine learning, forming the foundation for his multidisciplinary research career. Throughout his long-standing academic tenure, he has served in key leadership roles including department chair, graduate program administrator, research center director, and executive leader for university–industry cooperation, successfully guiding large-scale projects, fostering collaborative innovation, and advancing strategic academic initiatives. His research focuses on flexible job shop scheduling, deep learning–based fault diagnosis, time-series forecasting, metaheuristic optimization, and smart industrial systems. He has produced an extensive portfolio of influential publications in high-impact SCI-indexed journals, contributing novel hybrid algorithms, trainable fusion strategies, adaptive scheduling frameworks, lightweight diagnostic models, and intelligent computational methods that support the evolution of smart manufacturing and data-driven engineering. His scholarly achievements have earned him multiple recognitions, including awards for research excellence, and he actively contributes to the global academic community through editorial service, participation in professional societies, and engagement in scientific committees. With a sustained record of innovative research, academic leadership, and impactful contributions to computer and AI engineering, Professor Chang Soo Kim exemplifies the qualities of a leading researcher whose work continues to influence both industry and academia.

Profiles:  Scopus

Featured Publications

1. Kim, C. S., et al. (2025). Flexible job shop scheduling optimization with multiple criteria using a hybrid metaheuristic framework. Processes.

2. Kim, C. S., et al. (2025). Multi-branch global Transformer-assisted network for fault diagnosis. Applied Soft Computing.

3. Kim, C. S., et al. (2025). DL-MSCNN: A general and lightweight framework for fault diagnosis with limited training samples. Journal of Intelligent Manufacturing.

4. Kim, C. S., et al. (2025). Enhanced quantum-based DNA sequence alignment with noise handling and error detection. IEEE Access.

5. Kim, C. S., et al. (2024). GAILS: An effective multi-object job shop scheduler based on genetic algorithm and iterative local search. Scientific Reports.

Professor Chang Soo Kim’s pioneering research in intelligent manufacturing, AI-driven optimization, and fault diagnosis advances the scientific foundations of smart industry while enabling more efficient, reliable, and data-driven production systems. His innovative computational frameworks and adaptive algorithms contribute directly to industrial digital transformation, fostering technological competitiveness and sustainable global innovation.

Weitao Yue | Engineering | Research Excellence Award

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Dr. Weitao Yue | Engineering | Research Excellence Award

China University of Mining and Technology | China

Dr. Weitao Yue is a Ph.D. candidate in Safety Science and Engineering at the China University of Mining and Technology, recognized for his specialization in coal and rock dynamic disaster prevention and control. With an academic foundation centered on advanced safety engineering and a research focus on hazardous dynamic phenomena in mining environments, he has developed strong expertise in the investigation of disaster mechanisms, monitoring technologies, early-warning strategies, and innovative control methods. His professional experience includes substantial involvement in major national scientific projects, where he has taken on core research roles involving theoretical modeling, experimental system development, large-scale data analysis, and interdisciplinary coordination. Through these efforts, he has demonstrated leadership, technical depth, and the ability to drive complex research tasks toward impactful outcomes. Dr. Yue has published multiple high-quality SCI papers as first or corresponding author in internationally renowned journals, with several works recognized among the most globally cited in the field, reflecting his rising academic influence and contribution to advancing coal mine safety science. His research achievements have earned significant academic recognition, further supported by his participation in professional research communities and contributions to collaborative scientific endeavors. Known for integrating theoretical insight with practical application, he consistently delivers research that supports safer mining operations and enhances scientific understanding of dynamic disasters. His growing portfolio of accomplishments, strong methodological capabilities, and commitment to scientific innovation position him as a promising researcher with substantial potential for future leadership and continued contribution to the safety engineering discipline.

Profiles:  Scopus

Featured Publications

1. [Authors not provided]. (2026). Failure mechanisms of fault fracture zone under dynamic loading. Engineering Failure Analysis.

Tun Naw Sut | Chemical Engineering | Best Researcher Award

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Dr. Tun Naw Sut | Chemical Engineering | Best Researcher Award

Sungkyunkwan University | South Korea

Dr. Tun Naw Sut is a postdoctoral fellow specializing in nanomedicine, biomimetic membranes, and bio-sensing technologies, recognized for his interdisciplinary expertise and impactful research contributions. He holds dual doctoral training in nanomedicine and chemical engineering, supported by prior qualifications in materials science and biomedical engineering, forming a strong foundation for his work at the interface of engineering, biotechnology, and nanomaterials. His professional experience spans academic research, diagnostic platform development, electrochemical biomarker detection, phospholipid self-assembly studies, and compliance testing of medical electrical equipment, reflecting both scientific depth and industry-relevant technical capability. Dr. Sut’s research focuses on lipid-based nanomaterials, membrane biophysics, antimicrobial lipids, diagnostic sensors, and therapeutic nanoplatforms, and he has authored numerous publications in high-impact journals that advance the understanding and application of functional biomimetic systems. His leadership includes serving as guest editor and topic editor for international journals, contributing to the curation of scholarly work in biomimicry, functional materials, and membrane science. He has been recognized through competitive research grants, academic scholarships, and editorial appointments that highlight his innovation, scientific rigor, and growing influence in the field. Through his combined research excellence, interdisciplinary training, and dedication to advancing diagnostic and therapeutic technologies, Dr. Sut demonstrates exceptional potential for continued contributions to scientific innovation and research leadership.

Profiles: Scopus | ORCID

Featured Publications

1. Molla, A., Sut, T. N., Yoon, B. K., & Jackman, J. A. (2025). Headgroup-driven binding selectivity of alkylphospholipids to anionic lipid bilayers. Colloids and Surfaces B: Biointerfaces.

2. Lee, C. J., Jannah, F., Sut, T. N., Haris, M., & Jackman, J. A. (2025). Curvature-sensing peptides for virus and extracellular vesicle applications. ACS Nano.

3. Kim, D., Baek, H., Lim, S. Y., Lee, M. S., Lyu, S., Lee, J., Sut, T. N., Gonçalves, M., Kang, J. Y., Jackman, J. A., & Kim, J. W. (2025). Mechanobiologically engineered mimicry of extracellular vesicles for improved systemic biodistribution and anti-inflammatory treatment efficacy in rheumatoid arthritis. Advanced Healthcare Materials.

4. Ruano, M., Sut, T. N., Tan, S. W., Mullen, A. B., Kelemen, D., Ferro, V. A., & Jackman, J. A. (2025). Solvent-free microfluidic fabrication of antimicrobial lipid nanoparticles. ACS Applied Bio Materials.

5. Hwang, Y., Zhao, Z. J., Shin, S., Sut, T. N., Jackman, J. A., Kim, T., Moon, Y., Ju, B. K., Jeoni, J. H., Cho, N. J., & Kim, M. (2025). Nanopot plasmonic sensor platform for broad spectrum virus detection. Chemical Engineering Journal.

Dr. Tun Naw Sut’s work advances next-generation diagnostic and therapeutic technologies through innovative biomimetic membrane engineering and lipid-based nanomaterials. His research contributes to global health by enabling more effective pathogen detection, improved targeted delivery systems, and transformative strategies for sensing and treating complex diseases.

Kaíque Oliveira | Chemical Engineering | Editorial Board Member

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Dr. Kaíque Oliveira | Chemical Engineering | Editorial Board Member

Researcher | Federal University of São Carlos | Brazil

Dr. Kaíque Souza Gonçalves Cordeiro Oliveira, a Professor at IFSULDEMINAS, is an expert in electrochemical treatment of water and wastewater, with specialization in electrooxidation and capacitive and faradaic processes; he has completed advanced academic training with graduate degrees focused on electrochemical and environmental engineering disciplines, building a strong foundation in applied research and technological development. His professional experience includes leading instructional and research activities, mentoring students, and contributing to institutional projects that advance sustainable water-treatment technologies. Dr. Oliveira’s research centers on developing innovative electrochemical approaches for pollutant degradation, system optimization, and materials performance, resulting in impactful publications and growing recognition within the scientific community. His scholarly contributions, including peer-reviewed articles and participation in collaborative research initiatives, reflect his commitment to advancing environmentally responsible treatment methods. He has received professional acknowledgments for academic excellence, serves in editorial and review capacities for scientific journals, and contributes to professional societies and technical committees that promote innovation in electrochemical engineering.

Profiles: Google Scholar

Featured Publications

1. Juchen, P. T., Barcelos, K. M., Oliveira, K. S. G. C., & Ruotolo, L. A. M. (2022). Using crude residual glycerol as precursor of sustainable activated carbon electrodes for capacitive deionization desalination. Chemical Engineering Journal, 429, 132209.

2. Barcelos, K. M., Oliveira, K. S. G. C., & Ruotolo, L. A. M. (2020). Insights on the role of interparticle porosity and electrode thickness on capacitive deionization performance for desalination. Desalination, 492, 114594.

3. Oliveira, K. S. G. C., dos Santos, E. V., Loor-Urgilés, L. D., Shabanloo, A., & others. (2025). The world impact of boron doped diamond electrodes and low-cost strategies for novel production systems for sustainable wastewater treatment. Current Opinion in Electrochemistry, 101648.

4. Oliveira, K. S. G. C., Farinos, R. M., Veroli, A. B., & Ruotolo, L. A. M. (2021). Electrochemical incineration of glyphosate wastewater using three-dimensional electrode. Environmental Technology, 42(2), 170–181.

5. Oliveira, K. S. G. C., Barcelos, K. M., Lado, J. J., Palma, J., & Ruotolo, L. A. M. (2023). Improving the electrochemical desalination performance of chloride-doped polyaniline activated carbon electrode by tuning the synthesis method. Chemical Engineering Journal, 457, 141059.

Dr. Kaíque Souza Gonçalves Cordeiro Oliveira’s work advances sustainable electrochemical technologies that enable cleaner water, improved resource recovery, and more resilient environmental systems. His innovations in electrooxidation and capacitive deionization contribute to global efforts to ensure accessible, energy-efficient, and environmentally responsible water treatment solutions for industry and society.

Mehdi Masoodi | Electronic and Telecommunication Engineering | Best Researcher Award

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Dr. Mehdi Masoodi | Electronic and Telecommunication Engineering | Best Researcher Award

Senior Researcher | CNR-IREA | Italy

Dr. Mehdi Masoodi is a distinguished postdoctoral researcher at CNR-IREA, Naples, Italy, specializing in signal and image processing with a particular focus on radar imaging and the application of artificial intelligence to enhance imaging capabilities. He earned his Ph.D. in Industrial and Information Engineering from the University of Campania Luigi Vanvitelli, Italy, following a Master’s degree with honors in Telecommunication Engineering from Azad University, Iran, and a Bachelor’s in Telecommunications Engineering from Pasargad University, Iran. Dr. Masoodi’s professional experience spans roles as a postdoctoral researcher, volunteer researcher, and electronics engineer, contributing to projects including contactless surveys of reinforced concrete, antenna diagnostics, and telecommunication infrastructure development. He has co-authored numerous peer-reviewed journal articles, served as a referee for international journals and conferences, and is recognized for his contributions to model-based radar imaging strategies and AI-driven signal processing approaches. His work has earned significant citations, reflecting its impact and relevance in the scientific community. Dr. Masoodi has also been acknowledged for his academic excellence through national ranking distinctions and top performance in competitive examinations. Proficient in Matlab, Python, and GPR-MAX, he has demonstrated leadership in research projects and collaborative initiatives, combining technical expertise with innovation. His ongoing dedication to advancing radar imaging research, mentoring emerging scholars, and contributing to high-quality scientific publications establishes him as a leading figure in his field and a worthy candidate for recognition.

Profiles: Google Scholar | Scopus 

Featured Publications

1. Masoodi, M., & Taromideh, H. (2025). Optimal and uniform sensor arrangement in near-field imaging. Journal of Computational and Applied Mathematics, 454, 116188.

2. Masoodi, M., Gennarelli, G., Soldovieri, F., & Catapano, I. (2024). Multiview multistatic vs. multimonostatic three-dimensional ground-penetrating radar imaging: A comparison. Remote Sensing, 16(17), 3163.

3. Masoodi, M., Esposito, G., Gennarelli, G., Maisto, M. A., & Soldovieri, F. (2024). Transverse resolution in 2D linear inverse scattering by a multimonostatic/multifrequency configuration. IEEE Geoscience and Remote Sensing Letters.

4. Taromideh, F., Fazloula, R., Choubin, B., Masoodi, M., & Mosavi, A. (2024). Ensemble machine learning for urban flood hazard assessment. In 2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics.

5. Masoodi, M., & Leone, G. (2023). Diagnostics of conformal arrays by phaseless data and non-uniform sampling. In 2023 IEEE Conference on Antenna Measurements and Applications (CAMA) (pp. 212–216).

Zhen Li | Reliability and Systems Engineering | Best Researcher Award

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Prof. Dr. Zhen Li | Reliability and Systems Engineering | Best Researcher Award

Leader | Jiangsu University of Science and Technology | China

Prof. Dr. Zhen Li is an accomplished researcher and academic with extensive expertise in aerospace systems engineering, signal processing, and formal verification of software safety. He completed his higher education in business management, signal and information processing, and aerospace systems, culminating in a Ph.D. from a prestigious university. Over his career, he has held academic positions ranging from lecturer to professor, demonstrating consistent dedication to teaching and research. He has led research groups, authored a notable book, and published numerous papers in high-impact journals, with his work receiving significant citations. Prof. Li has also contributed to professional societies, including IEEE and the Chinese Artificial Intelligence Society, and has been recognized with national-level awards for his research excellence. His international collaborations and leadership roles highlight his influence in advancing research in engineering and artificial intelligence. With a strong record of innovation and mentorship, he continues to show great potential for future high-impact contributions.

Profiles: ORCID

Featured Publications

1. Li, Z., Tian, L., Sun, C., Wu, Y., Wang, D., & Miao, H. (2022). A systematic research on system recovery based on improved genetic algorithm and quotient resilience model under attack and damage. International Journal of Computational Intelligence Systems.

2. Liu, Y., Li, Z., Wang, D., Miao, H., & Wang, Z. (2021). Software defects prediction based on hybrid particle swarm optimization and sparrow search algorithm. IEEE Access.

3. Wu, Y., Li, Z., Sun, C., Wang, D., Zhao, B., & Yu, Z. (2021). Measurement and control of system resilience recovery by path planning based on improved genetic algorithm. Measurement and Control.

4. Li, Z. (2021). Safety ontology modeling and verification on MIS of ship-building and repairing enterprise. KSII Transactions on Internet and Information Systems.

5. Li, Z., Li, T., Wu, Y., Liu, Y., Miao, H., Wang, D., & Precup, R.-E. (2021). Software defect prediction based on hybrid swarm intelligence and deep learning. Computational Intelligence and Neuroscience.

Dongfeng Qi | Engineering | Best Researcher Award

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Prof. Dongfeng Qi | Engineering | Best Researcher Award

Professor | Shandong University of Technology | China

Prof. Dongfeng Qi is a leading researcher in laser manufacturing and material processing, specializing in femtosecond and nanosecond laser applications for advanced materials and flexible electronics. His work integrates theoretical modeling with experimental techniques to develop innovative micro- and nanostructures, including copper and silicon-based materials, phase-change films, and smart electronic devices. Prof. Qi has made substantial contributions to understanding laser-material interactions and patterning technologies, with high-impact publications in top-tier journals. He demonstrates strong interdisciplinary collaboration and mentorship, fostering international research partnerships and the growth of emerging scientists. His research is recognized for both fundamental insights and practical applications in photonics, energy storage, and flexible electronics. Prof. Qi’s consistent innovation, high-quality experimental work, and leadership in the field establish him as a leading figure in laser-based materials science. According to Scopus, he has 535 citations, 71 documents, and an h-index of 13.

Profiles: Scopus | Google Scholar

Featured Publications

1. Programming nanoparticles in multiscale: optically modulated assembly and phase switching of silicon nanoparticle array; L. Wang, Y. Rho, W. Shou, S. Hong, K. Kato, M. Eliceiri, M. Shi, …; ACS Nano, vol. 12, no. 3, pp. 2231–2241, 2018; 39 citations

2. Time-resolved analysis of thickness-dependent dewetting and ablation of silver films upon nanosecond laser irradiation; D. Qi, D. Paeng, J. Yeo, E. Kim, L. Wang, S. Chen, C. P. Grigoropoulos; Applied Physics Letters, vol. 108, no. 21, 2016; 37 citations

3. Femtosecond laser-induced large area of periodic structures on chalcogenide glass via twice laser direct-writing scanning process; X. Yu, Q. Zhang, D. Qi, S. Tang, S. Dai, P. Zhang, Y. Xu, X. Shen; Optics & Laser Technology, vol. 124, 105977, 2020; 34 citations

4. Progress in the design, nanofabrication, and performance of metalenses; Z. Wang, Y. Wu, D. Qi, W. Yu, H. Zheng; Journal of Optics, vol. 24, no. 3, 033001, 2022; 31 citations

5. Progress in preparation and applications of Te-As-Se chalcogenide glasses and fibers; Z. Wu, Y. Xu, D. Qi, Q. Nie, X. Zhang; Infrared Physics & Technology, vol. 102, 102981, 2019; 31 citations