Bahaa Hussein Taher | Engineering | Research Excellence Award

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Mr. Bahaa Hussein Taher | Engineering | Research Excellence Award

University of Sumer | China

Mr. Bahaa Hussein Taher is a senior engineer and academic affiliated with the University of Sumer, specializing in computer science and electronic engineering with a strong focus on advanced networking and edge computing. His academic background includes doctoral and master’s level training in computer science, electronic engineering, and information engineering, building a solid foundation in computing systems and optimization. Professionally, he has held academic, engineering, and leadership roles, contributing to teaching, research supervision, quality assurance management, IT infrastructure development, and participation in strategic planning and technical committees. His research expertise centers on edge computing, dynamic task allocation, secure execution in next-generation networks, cryptographic protocols, scheduling, and optimization, with multiple publications in internationally indexed journals. He has actively contributed to the academic community through workshops, seminars, and conference participation, reflecting sustained scholarly engagement. His recognitions include language proficiency certifications and professional credentials that support international research collaboration, highlighting his capacity to advance impactful, secure, and efficient computing solutions with strong future research potential.

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Top 5 Featured Publications

 

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

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.

Sayyid Ali Banihashemi | Engineering | Editorial Board Member

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Assist. Prof. Dr. Sayyid Ali Banihashemi | Engineering | Editorial Board Member

Faculty Member | Payame Noor University | Iran

Assist. Prof. Dr. Sayyid Ali Banihashemi, Associate Professor in the Department of Industrial Engineering at Payame Noor University, is a recognized scholar specializing in project scheduling, data envelopment analysis, supply chain management, and organizational agility. He holds advanced degrees in industrial engineering with a concentration in operations research and performance evaluation, complemented by rigorous training in quantitative decision-making. His professional experience includes leading academic programs, supervising research initiatives, and contributing to major analytical and optimization projects that support organizational and operational improvement. Dr. Banihashemi’s research portfolio encompasses influential publications, high-impact citations, and methodological advancements that have shaped contemporary practices in project planning efficiency, productivity assessment, and supply chain performance. His scholarly contributions are further reflected in editorial responsibilities for reputable journals, memberships in distinguished professional societies, and certifications in advanced analytical methods. Widely cited and respected in his field, he has earned multiple recognitions for research excellence, academic service, and contributions to the industrial engineering community, establishing him as a dedicated leader committed to advancing theory and practice in operations and performance management.

Profiles: Google Scholar

Featured Publications

1. Dahmardeh, N., & Banihashemi, S. A. (2010). Organizational agility and agile manufacturing. European Journal of Economics, Finance and Administrative Sciences, 27, 178–184.

2. Banihashemi, S. A. (2011). The role of communication to improve organizational process. European Journal of Humanities and Social Sciences, 1(1), 13–24.

3. Banihashemi, S. A., Khalilzadeh, M., Shahraki, A., Malkhalifeh, M. R. M., & others. (2020). Optimization of environmental impacts of construction projects: A time–cost–quality trade-off approach. International Journal of Environmental Science and Technology, 1–16.

4. Banihashemi, S. A., & Khalilzadeh, M. (2021). Time-cost-quality–environmental impact trade-off resource-constrained project scheduling problem with DEA approach. Engineering, Construction and Architectural Management, 28(7), 1979–2004.

5. Banihashemi, S. A., Khalilzadeh, M., Antucheviciene, J., & Edalatpanah, S. A. (2023). Identifying and prioritizing the challenges and obstacles of green supply chain management in the construction industry using the fuzzy BWM method. Buildings, 13(1), 38.

Dr. Sayyid Ali Banihashemi’s work advances scientific and industrial practice by integrating optimization, sustainability, and performance evaluation to improve project delivery and supply chain systems. His research supports data-driven decision-making that enhances organizational efficiency, reduces environmental impacts, and strengthens the resilience and agility of modern industries.

Liana Mogilnikova | Materials Science | Best Researcher Award

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Mrs. Liana Mogilnikova | Materials Science | Best Researcher Award

Liana Mogilnikova  | MISIS | Russia

Mrs. Liana Mogilnikova is a dedicated and accomplished researcher specializing in the study of hexagonal ferrites and magnetically hard materials. Her research focuses on understanding phase transformations and crystal structures, contributing valuable insights into the synthesis and characterization of strontium hexaferrite. Through meticulous experimentation and analytical precision, she has developed a comprehensive methodology for investigating the structural and phase states of ferrite materials. Her scholarly contributions, reflected in publications in reputed journals, demonstrate her commitment to advancing material science and magnetic materials research. With strong skills in data analysis, academic writing, and conference presentation, she effectively communicates complex scientific findings to the research community. Her work not only deepens the understanding of ferrite synthesis mechanisms but also lays the foundation for future innovations in nanostructured and energy-efficient magnetic materials, establishing her as a promising and impactful researcher in her field.

Profiles: Scopus | ORCID

Featured Publications

1. Mogilnikova, L. D., Menushenkov, V. P., Mogilnikov, P. S., & Savchenko, A. G. (2025). Phase transformations in the synthesis process of strontium hexaferrite SrFe₁₂O₁₉ by the sol-gel method. Journal of Alloys and Compounds, 1042, 183995.

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

Abdullah Al Nahian | Data Analyst | Best Research Article Award

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Mr. Abdullah Al Nahian | Data Analyst | Best Research Article Award

Healthcare Data Analyst at Children’s Clinic of Michigan, United States

Mr. Abdullah Al Nahian is a dedicated professional and researcher with a strong background in data analytics, computer science, and information systems. His career spans diverse roles including data analyst, network engineer, software developer, and project coordinator, where he has consistently demonstrated expertise in data analysis, system optimization, and project management. Academically, he holds advanced education in information studies and computer science, complemented by certifications in project management, cybersecurity, and database systems. His research contributions focus on impactful areas such as predictive modeling for healthcare outcomes, machine learning applications in cancer stage classification, and neural network-based recognition systems, which have been published in reputable scientific platforms. Abdullah’s work bridges technical innovation with practical applications, particularly in healthcare and information technology, underscoring his ability to contribute solutions to real-world challenges. His combination of academic rigor, technical expertise, and professional experience highlights him as a promising researcher and thought leader in his field.

Professional Profile 

Google Scholar

Education

Mr. Abdullah Al Nahian has built a strong academic foundation that supports his career in technology and research. He earned his Bachelor of Science in Computer Science and Engineering from the University of Liberal Arts Bangladesh, where he developed core knowledge in programming, software development, and system design. To further strengthen his expertise, he pursued a Master of Science in Information Studies at Trine University, Detroit, with a focus on data analytics, information systems, and applied research. His academic journey has been complemented by professional certifications, including Project Management Professional (PMP), Advanced Database, and Cybersecurity, which add specialized knowledge to his technical profile. This combination of formal education and certifications demonstrates his commitment to continuous learning and skill development. By bridging theoretical understanding with practical applications, his educational background provides a strong base for his professional roles and impactful research contributions in data science, healthcare analytics, and machine learning.

Experience

Mr. Abdullah Al Nahian brings extensive professional experience across multiple domains of information technology, data analysis, and project management. Currently working as a Data Analyst at the Children’s Clinic of Michigan, he specializes in gathering, securing, and analyzing healthcare data to improve patient outcomes and operational efficiency. His previous roles include Assistant Coordinator at Polock Group BD, Network Engineer and Assistant Manager at Agni Systems Ltd., and Software Developer at NKSoft BD. Across these roles, he developed expertise in network engineering, customer support, ERP systems, project coordination, and administrative leadership. His career began with web development, gradually expanding to more advanced responsibilities involving data-driven decision-making, system monitoring, and organizational leadership. This progression highlights his adaptability and growth across technical and managerial domains. Additionally, his volunteer work as an IT Specialist further demonstrates his dedication to using technology for organizational improvement and staff empowerment. Collectively, his diverse experience reflects both technical mastery and leadership capability.

Research Focus

Mr. Abdullah Al Nahian’s research focuses on the intersection of data science, healthcare, and machine learning, reflecting both technical innovation and practical significance. His work includes developing predictive models to optimize healthcare outcomes, leveraging data-driven insights to improve patient care and resource management. He has also co-authored research on cancer stage classification using numerical biomarker data, showcasing the role of artificial intelligence in advancing medical diagnosis. Beyond healthcare, his contributions extend to neural network-powered recognition systems, such as automated license plate detection, and in-depth studies on project management and visualization techniques. His approach emphasizes applying computational methods to solve real-world problems, combining theoretical rigor with practical utility. Through his publications in recognized scientific platforms, he demonstrates a commitment to advancing knowledge in applied machine learning, data analytics, and information systems. His research is notable for addressing global challenges in healthcare and technology, bridging academic inquiry with societal impact.

Award and Honor

Mr. Abdullah Al Nahian has established himself as a promising researcher whose academic and professional achievements make him a strong candidate for recognition. His research contributions, published in respected scientific journals and platforms, reflect innovation and applicability in critical domains such as healthcare analytics, artificial intelligence, and project management. Co-authoring multiple peer-reviewed publications within a short period demonstrates his dedication to scholarly excellence and collaborative research. His academic journey, complemented by certifications in project management and cybersecurity, highlights his commitment to professional growth and expertise. In professional settings, he has consistently been recognized for leadership, technical problem-solving, and delivering solutions that improve organizational performance. While his portfolio primarily emphasizes research and professional contributions, his trajectory indicates strong potential for continued recognition through awards that honor innovation, interdisciplinary impact, and societal value. His blend of academic, research, and professional accomplishments positions him as a valuable contributor deserving of future honors.

Publications Top Notes

  • Title: Optimizing Healthcare Outcomes through Data-Driven Predictive Modeling
    Authors: MNM Sunny, MBH Saki, A Al Nahian, SW Ahmed, MN Shorif, J Atayeva, …
    Year: 2024
    Citations: 33

  • Title: Project Management and Visualization Techniques A Details Study
    Authors: MNM Sunny, MBH Sakil, A Al
    Year: 2024
    Citations: 24

  • Title: Neural Network-Powered License Plate Recognition System Design
    Authors: S Hasan, MNM Sunny, A Al Nahian, M Yasin
    Year: 2024
    Citations: 19

  • Title: Classification of Cancer Stages Using Machine Learning on Numerical Biomarker Data
    Authors: MNM Sunny, MM Amin, MH Akter, KMS Hossain, A Al Nahian, J Atayeva
    Year: 2024
    Citations: 3

  • Title: Optimizing Prescription Practices Using AI-Powered Drug Substitution Models to Reduce Unnecessary Healthcare Expenditures in Outpatient Settings
    Authors: A Al Nahian, S Samia, MTM Hussan, F Mahmud, MNM Sunny, SW Ahmed, …
    Year: 2025

  • Title: A Critical Review of Network Management Tools and Technologies in the Digital Age
    Authors: AAN Zakia Sultnana Munmun, Md Minhajul Amin, K M Shihab Hossain
    Year: 2024

Conclusion

Mr. Abdullah Al Nahian’s research portfolio demonstrates a consistent focus on applying data-driven approaches and machine learning techniques to solve critical challenges in healthcare, project management, and technology systems. His publications reflect both academic rigor and practical relevance, particularly in predictive healthcare modeling, cancer diagnosis, and AI-powered optimization solutions. The diversity of his work, ranging from network technologies to medical applications, highlights his ability to bridge interdisciplinary fields and contribute meaningful innovations. With multiple citations already attributed to his recent publications, his research is gaining recognition and impact in the academic community. His role as co-author in several high-quality studies also emphasizes strong collaboration skills and commitment to advancing collective knowledge. Overall, his contributions position him as a capable and promising researcher whose work holds significant value for both academic advancement and real-world problem-solving.