Mazlina Abdul Majid | Computer Science | Research Excellence Award

Published on by Global Scholar Awards

Research Excellence Award

Mazlina Abdul Majid
Universiti Malaysia Pahang Al-Sultan Abdullah, Malaysia

Mazlina Abdul Majid
Affiliation Universiti Malaysia Pahang Al-Sultan Abdullah
Country Malaysia
Scopus ID 57222473453
Documents 120
Citations 1,112
h-index 21
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0001-9068-7368

Mazlina Abdul Majid is a computer science academic and researcher at Universiti Malaysia Pahang Al-Sultan Abdullah whose scholarly work encompasses data analytics, simulation modelling, artificial intelligence, green information technology, optimization, software usability, and sustainability-oriented computing. Her research profile connects computational methods with operational and environmental challenges, including applications involving simulation, intelligent algorithms, data-driven analysis, and sustainable information systems. Institutional and scholarly profiles identify her with research activities in data science, simulation and modelling, green technology, software engineering, and analytics. [1] [2]

Abstract

Mazlina Abdul Majid is a Malaysian computer science researcher whose work integrates data analytics, artificial intelligence, simulation modelling, optimization, green information technology, and sustainable computing. Her research addresses computational approaches for operational, environmental, and organizational challenges, with applications spanning intelligent algorithms, data-driven decision making, software systems, and sustainability assessment. Her scholarly record includes studies of green information technology adoption, sustainable enterprise strategies, simulation-based operational analysis, artificial intelligence, and optimization methods. Recent publications further demonstrate engagement with engineering optimization and computer vision applications. These interdisciplinary contributions connect computational techniques with practical sustainability objectives and support evidence-based innovation across contemporary digital research environments.[5]

Keywords

Computer science; artificial intelligence; data analytics; simulation modelling; optimization; green information technology; sustainability; green computing; software usability; enterprise systems; agent-based modelling; operational research; convolutional neural networks; genetic algorithms; engineering optimization; differential evolution; Lévy flight; harmony search; environmental sustainability; air quality estimation; data science.

Introduction

Mazlina Abdul Majid has developed a research profile within computer science that emphasizes the application of computational intelligence to operational and sustainability-related problems. Her institutional profile identifies expertise in modelling and simulation, green operations research, sustainability impact analysis, and software consultancy, while other scholarly sources associate her work with artificial intelligence, data analytics, optimization, and software usability. [1] [3]

Research Profile

Mazlina Abdul Majid’s research profile spans data science, simulation modelling, artificial intelligence, green information technology, and sustainability-oriented computing. Mazlina Abdul Majid has also been associated with the Data Science and Simulation Modeling research environment at Universiti Malaysia Pahang Al-Sultan Abdullah, where computational modelling is positioned as a means of supporting data-driven innovation and analytical solutions. [1] [4]

Research Contributions

Mazlina Abdul Majid has contributed to research examining computational approaches for sustainability, information technology adoption, operational modelling, and intelligent optimization. Mazlina Abdul Majid has participated in studies addressing green information technology adoption in government institutions, sustainable enterprise strategies, agent-based green information systems, and optimization algorithms. More recent work extends these interests toward computer vision and intelligent estimation of environmental conditions. [5] [6]

Publications

Mazlina Abdul Majid has published research across green information technology, sustainability, simulation, artificial intelligence, data analytics, and optimization. Mazlina Abdul Majid is listed as a contributor to the study “A novel method of S-box design based on discrete chaotic maps and cuckoo search algorithm,” and to recent work on image-based air quality estimation using convolutional neural networks optimized by genetic algorithms. [5] [6]

Research Impact

Mazlina Abdul Majid’s research impact can be considered through the breadth of computational topics represented in her scholarly record, including sustainability, green information systems, simulation modelling, artificial intelligence, optimization, and data analytics. Mazlina Abdul Majid’s work connects methodological development with applied problems, particularly where computational models can support operational decisions, environmental assessment, and sustainable technology practices. [2]

Award Suitability

Mazlina Abdul Majid’s documented research activity aligns with the scope of a Research Excellence Award because her scholarly profile combines sustained publication activity with interdisciplinary work in computer science, data analytics, artificial intelligence, optimization, simulation, and sustainable information technology. Mazlina Abdul Majid’s publication themes demonstrate the application of computational methods to practical research problems, providing a coherent basis for recognition within the Computer Science category of the Global Scholar Awards.[5]

Conclusion

Mazlina Abdul Majid represents a multidisciplinary computer science research profile centered on intelligent computation, simulation, analytics, optimization, and sustainability. Mazlina Abdul Majid’s publications demonstrate the application of computational techniques to green information technology, operational modelling, environmental estimation, and engineering optimization. The combination of these research themes provides a relevant scholarly foundation for consideration for the Research Excellence Award.[4]

References

  1. Universiti Malaysia Pahang Al-Sultan Abdullah. (n.d.). UMPSA Expert Directory: Professor Ts. Dr. Mazlina Binti Abdul Majid.
    https://apps.ump.edu.my/expertDirectory/profile.jsp?email=mazlina%40ump.edu.my
  2. ORCID. (n.d.). Mazlina Abdul Majid, ORCID iD 0000-0001-9068-7368.
    https://orcid.org/0000-0001-9068-7368
  3. International Journal of Science of Technology. (n.d.). Editorial Team: Prof. Dr. Ts. Mazlina Abdul Majid.
    https://ijsot.org/index.php/ijsot/about/editorialTeam
  4. Universiti Malaysia Pahang Al-Sultan Abdullah. (n.d.). Data Science & Simulation Modeling Research Group.
    https://fk.umpsa.edu.my/index.php/component/sppagebuilder?id=298&view=page
  5. Majid, M. A., et al. (2019). Green information technology adoption towards a sustainability policy agenda for government-based institutions: An administrative perspective. Journal of Science and Technology Policy Management, 10(2), 274–300.
    https://doi.org/10.1108/JSTPM-11-2017-0056
  6. Khan, A. A., Majid, M. A., & Dandoush, A. (2025). Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach. International Journal of Advanced Computer Science and Applications, 16(3).
    https://thesai.org/Downloads/Volume16No3/Paper_113-Image_Based_Air_Quality_Estimation_Using_Convolutional_Neural_Network.pdf
  7. Qin, F., Zain, A. M., Zhou, K.-Q., Yusup, N. B., Prasetya, D. D., Jalil, R. A., Abidin, Z. Z., Bahari, M., Kamin, Y., & Majid, M. A. (2025). Hybrid Harmony Search Algorithm Integrating Differential Evolution and Lévy Flight for Engineering Optimization. IEEE Access.
    https://doi.org/10.1109/ACCESS.2025.3529714

Dominic Ayamga | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Best Researcher Award

Dominic Ayamga — University of Technology Sydney

Dominic Ayamga
Affiliation University of Technology Sydney
Country Ghana
Scopus ID 59668577800
Documents 2
Citations 1
h-index 1
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0001-8264-3189

Dominic Ayamga is a computer science researcher whose documented work focuses on enterprise security architecture, inference attacks, cybersecurity governance, and information security. His research addresses how established security models can encounter inference-related weaknesses and how organizational practices influence security outcomes. His scholarly profile reflects an emerging contribution to cybersecurity research. [1]

Abstract

Dominic Ayamga is a computer science researcher affiliated with the University of Technology Sydney whose work examines enterprise security architecture, inference attacks, cybersecurity governance, and human factors in information security. His documented research includes studies of the Bell-LaPadula model and inference attacks, alongside emerging work connecting cybersecurity culture, governance, and organizational behavior. These contributions address security risks arising from information flow, access control, policy implementation, and user practices. With publications indexed in scholarly databases and an identified ORCID record, Ayamga’s research profile reflects an developing focus on socio-technical cybersecurity, resilient enterprise information protection, and secure digital governance practices. research practice.[5]

Keywords

Inference attacks, enterprise security architecture, Bell-LaPadula model, information flow, cybersecurity governance, cybersecurity culture, access control, human behaviour, information security, organizational security, NIST Cybersecurity Framework, ISO/IEC 27001, inference attack detection, digital security, socio-technical cybersecurity.[2]

Introduction

Dominic Ayamga’s research sits within computer science and cybersecurity, with particular attention to enterprise security architecture and inference-related risks. His published work considers how established security models perform when information can be inferred from authorized or indirect access. This focus connects technical controls with governance and organizational practice in contemporary environments. [1]

Research Profile

Dominic Ayamga is affiliated with the University of Technology Sydney associated with research in cybersecurity and enterprise security architecture. Records identify his ORCID as 0000-0001-8264-3189 and document work presented through the International Conference on Security of Information and Networks. His profile emphasizes focused information security, inference attacks, governance, and protection. [3]

Research Contributions

Dominic Ayamga contributes to cybersecurity research by examining weaknesses emerging when enterprise security models encounter inference attacks. His Bell-LaPadula study evaluates information-flow protection in relation to inference risks, while later work broadens the analysis toward cybersecurity culture, governance, access practices, and organizational behavior. Studies connect security architecture with socio-technical risk. [1] [2]

Publications

Dominic Ayamga’s publications include The Bell-LaPadula (BLP) Enterprise Security Architecture Model vs Inference Attacks, published in the 2024 International Conference on Security of Information and Networks, and Cybersecurity Culture, Governance, and Inference Attacks: A Developing-Country Case Study on Enterprise Security Architecture Adaptation, posted as a 2026 preprint. Works establish trajectory. [1] [2]

Research Impact

Dominic Ayamga’s research impact is presently reflected through a focused publication record addressing inference attacks and enterprise security architecture. The work contributes to discussions about information flow, access governance, security culture, and organizational behavior. Available bibliographic information reports one citation and an h-index of one, indicating an early-stage scholarly profile. [2]

Award Suitability

Dominic Ayamga appears suitable for consideration for Best Researcher Award within a computer science or cybersecurity category because his documented work addresses a specialized security problem across technical and organizational dimensions. His research connects formal security architecture with inference risks, governance, and human behavior, providing a scholarly basis for recognition.[4]

Conclusion

Dominic Ayamga’s research profile demonstrates a developing contribution to cybersecurity, particularly enterprise security architecture and inference attacks. His publications progress from model-level analysis toward broader governance and behavioral considerations. The combination of technical security concerns, organizational context, and identifiable scholarly outputs provides a foundation for continued research and academic recognition.[2]

References

  1. Ayamga, D., Nanda, P., & Mohanty, M. (2024). The Bell-LaPadula (BLP) Enterprise Security Architecture Model vs Inference Attacks. 2024 17th International Conference on Security of Information and Networks (SIN), 1–8. https://doi.org/10.1109/SIN63213.2024.10871247
  2. Ayamga, D., Nanda, P., & Mohanty, M. (2026). Cybersecurity Culture, Governance, and Inference Attacks: A Developing-Country Case Study on Enterprise Security Architecture Adaptation. SSRN. https://doi.org/10.2139/ssrn.6212346
  3. University of Technology Sydney. (2024). The Bell-LaPadula (BLP) Enterprise Security Architecture Model vs Inference Attacks. Open Publications of UTS Scholars. https://opus.lib.uts.edu.au/handle/10453/185595
  4. ORCID. (n.d.). ORCID record: Dominic Ayamga, 0000-0001-8264-3189.
    https://orcid.org/0000-0001-8264-3189
  5. Elsevier. (n.d.). Scopus author details: Dominic Ayamga, Author ID 59668577800. Scopus.
    https://www.scopus.com/pages/authors/59668577800

SeongJeong Yoon | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Best Researcher Award

SeongJeong Yoon
Swiss School of Management

SeongJeong Yoon
Affiliation Swiss School of Management
Country South Korea
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0001-5188-801X

SeongJeong Yoon is affiliated with the Swiss School of Management and is recognized for scholarly contributions in Computer Science through research that supports technological innovation, intelligent computing, digital transformation, and interdisciplinary collaboration. The academic profile reflects sustained engagement with internationally indexed publications and professional research activities that contribute to contemporary scientific knowledge and practical applications within computing disciplines.[1]

Abstract

SeongJeong Yoon has developed an academic profile centered on Computer Science, emphasizing intelligent information systems, digital innovation, software engineering, data analytics, artificial intelligence, cloud technologies, cybersecurity, and emerging computational methodologies. Research activities demonstrate consistent engagement with internationally indexed publications, interdisciplinary collaborations, and knowledge dissemination through scholarly communication. The work contributes to technological advancement by integrating theoretical understanding with practical implementation while addressing contemporary scientific and industrial challenges. Continued participation in academic research reflects commitment to innovation, evidence-based investigation, sustainable digital transformation, and the advancement of global computing knowledge through impactful scholarly contributions and collaborative scientific excellence.[1][2]

Keywords

Artificial Intelligence, Machine Learning, Data Analytics, Software Engineering, Intelligent Systems, Digital Transformation, Cloud Computing, Cybersecurity, Information Systems, Deep Learning, Big Data, Computer Vision.

Introduction

SeongJeong Yoon advances Computer Science through interdisciplinary investigations integrating intelligent computing, software development, and digital technologies. Academic activities emphasize rigorous methodology, collaborative research, and internationally visible publications that strengthen technological innovation while supporting practical applications, sustainable development, and continued scientific progress across evolving computational environments.[1]

Research Profile

SeongJeong Yoon maintains an internationally oriented research profile supported by scholarly publications, institutional collaboration, and participation within modern computing disciplines. Research interests encompass intelligent systems, digital innovation, information technologies, and computational problem solving while contributing to knowledge exchange across academic and professional scientific communities worldwide.[2]

Research Contributions

SeongJeong Yoon contributes through scholarly investigations exploring advanced computing technologies, analytical methodologies, and innovative digital solutions. Research integrates theoretical concepts with practical implementation, encouraging interdisciplinary collaboration while supporting technological advancement, academic excellence, and sustainable innovation across diverse Computer Science research applications.[3]

Publications

SeongJeong Yoon has authored and collaborated on scholarly publications addressing contemporary Computer Science themes including artificial intelligence, software engineering, information systems, cloud computing, and digital transformation. Published research demonstrates methodological consistency, academic relevance, and valuable contributions supporting evidence-based technological development within international scientific literature.[2]

Research Impact

SeongJeong Yoon demonstrates measurable research impact through internationally indexed publications, scholarly visibility, citation activity, and interdisciplinary engagement. Academic contributions encourage knowledge transfer, technological innovation, and collaborative scientific advancement while supporting future investigations addressing emerging computational challenges across academic and industrial environments.[4]

Award Suitability

SeongJeong Yoon demonstrates qualities consistent with recognition through the Best Researcher Award by maintaining sustained scholarly productivity, international academic engagement, and impactful Computer Science research. Professional achievements illustrate commitment to innovation, scientific integrity, collaborative excellence, and meaningful contributions benefiting contemporary global research communities.[5]

Conclusion

SeongJeong Yoon represents an accomplished academic whose Computer Science research supports technological advancement through interdisciplinary scholarship, internationally indexed publications, and collaborative scientific engagement. Continued research activities reinforce professional excellence while contributing valuable knowledge that advances innovation, digital transformation, and sustainable computing research worldwide.[1]

References

  1. Moon, J.-H., Kim, N., Kim, W., & Yoon, S. (2024). A research on the technological elements of the digital twin operation platform in the industrial metaverse federation. https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11933357
  2. ORCID. (n.d.). ORCID record for SeongJeong Yoon.
    https://orcid.org/0000-0001-5188-801X
  3. Kim, N., Kim, W., & Yoon, S. (2024). Field empirical research on generative artificial intelligence job file generation and worker behavior issues.
    https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11742484
  4. Choi, J., Kim, N., Kim, W., & Yoon, S. (2023). Research on trends and key issues in industrial collaborative robots and worker interaction.
    https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11509571
  5. Global Scholar Awards. (n.d.). Best Researcher Award Recognition.
    https://globalscholarawards.com/

Mazen Ramadhan | Computer Science | Innovative Research Award

Published on by Global Scholar Awards

Innovative Research Award

Mazen Ramadhan
Multimedia University, Malaysia

Mazen Ramadhan
Affiliation Multimedia University
Country Malaysia
Scopus ID 57215557743
Documents 16
Citations 176
h-index 6
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0001-9555-7781

Mazen Ramadhan is a researcher at Multimedia University, Malaysia, whose scholarly work primarily focuses on computer science, intelligent systems, cybersecurity, machine learning, digital technologies, and applied computing. His research demonstrates interdisciplinary collaboration and addresses practical technological challenges through innovative computational methods. With publications indexed in major academic databases and measurable citation impact, his contributions have supported advancements in emerging digital technologies and continue to influence research within computer science and related engineering disciplines.[1]

Abstract

Mazen Ramadhan has established a research portfolio centered on computer science with emphasis on cybersecurity, intelligent systems, machine learning, software engineering, digital transformation, and data-driven technologies. His scholarly publications demonstrate practical applications of computational techniques for addressing contemporary technological problems while encouraging interdisciplinary collaboration. Through peer-reviewed research, measurable citation performance, and international academic visibility, his work contributes to knowledge development in emerging digital domains. The consistency of his publications, collaborative research activities, and recognized academic profile reflect sustained contributions to advancing innovation, computational methodologies, and applied scientific research within the global computer science community.[2]

Keywords

Cybersecurity, Machine Learning, Artificial Intelligence, Internet of Things, Software Engineering, Deep Learning, Computer Networks, Data Analytics, Intelligent Systems, Cloud Computing, Digital Transformation, Information Security.

Introduction

Mazen Ramadhan conducts research addressing modern computing challenges through interdisciplinary methods integrating artificial intelligence, cybersecurity, and software technologies. His publications reflect practical problem solving, collaborative investigation, and continuous engagement with emerging digital innovations supporting academic advancement and technological development across diverse computer science applications.[3]

Research Profile

Mazen Ramadhan maintains an internationally visible research profile supported by Scopus, Google Scholar, ORCID, ResearchGate, and institutional records. His publication metrics demonstrate consistent scholarly productivity, interdisciplinary collaboration, and citation impact within computer science, reflecting recognized academic participation in global research communities.[1]

Research Contributions

Mazen Ramadhan contributes to advancing intelligent computing by investigating secure digital systems, machine learning applications, software engineering practices, and innovative computational methodologies. His research supports practical implementations while encouraging multidisciplinary collaboration, enabling improvements in technology adoption, cybersecurity resilience, and intelligent information processing.[4]

Publications

Mazen Ramadhan has authored peer-reviewed publications indexed by Scopus and Google Scholar covering cybersecurity, artificial intelligence, machine learning, digital technologies, and software engineering. These publications demonstrate methodological diversity, collaborative research, and meaningful academic dissemination across recognized international journals and conference proceedings.[2]

Research Impact

Mazen Ramadhan has achieved measurable research influence through citations, indexed publications, and collaborative scientific activities. His scholarly output supports ongoing developments in computer science while contributing evidence-based knowledge that benefits researchers, practitioners, and future investigations across intelligent digital technologies and computational innovation.[1]

Award Suitability

Mazen Ramadhan demonstrates qualifications appropriate for the Innovative Research Award through sustained publication activity, interdisciplinary computer science research, international academic visibility, and measurable scholarly impact. His research achievements illustrate innovation, scientific consistency, and meaningful contributions supporting technological advancement and global academic collaboration.[5]

Conclusion

Mazen Ramadhan continues contributing to computer science through interdisciplinary research, impactful scholarly publications, and international collaboration. His academic profile reflects sustained scientific productivity, practical innovation, and commitment to advancing intelligent digital technologies, supporting recognition within prestigious international research and innovation award programs.[2]

External Links

References

  1. Elsevier. (n.d.). Scopus Author Details: Mazen Ramadhan, Author ID 57215557743. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57215557743
  2. Google Scholar. (n.d.). Mazen Ramadhan Citation Profile.
    https://scholar.google.com/citations?user=-vuQJ7IAAAAJ&hl=en&oi=ao
  3. Multimedia University. (n.d.). Academic Expert Profile: Mazen Ramadhan.
    https://mmuexpert.mmu.edu.my/ramadhanmazen
  4. ORCID. (n.d.). Mazen Ramadhan Research Record.
    https://orcid.org/0000-0001-9555-7781
  5. IEEE. (2019). Representative publication in intelligent computing.
    https://doi.org/10.1109/ACCESS.2020.2970475

Yulin Jing | Computer Science | Research Excellence Award

Published on by Global Scholar Awards

Dr. Yulin Jing | Computer Science | Research Excellence Award

University of Electronic Science and Technology of China | China

Dr. Yulin Jing is a researcher affiliated with the University of Electronic Science and Technology of China, specializing in computer science with a focus on artificial intelligence, adversarial machine learning, and video recognition systems. With 5 publications, 24 citations, and an h-index of 3, Jing has contributed to advancing robust and secure AI models, particularly in the area of black-box adversarial attack algorithms. Engaged in collaborative research with multiple co-authors, their work addresses critical challenges in AI reliability and cybersecurity. Jing’s research holds societal significance by enhancing the safety and trustworthiness of intelligent systems in real-world applications, including surveillance, automation, and digital technologies.

Citation Metrics (Scopus)

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Featured Publication

Bin Liu | Computer Science | Research Excellence Award

Published on by Global Scholar Awards

Prof. Bin Liu | Computer Science | Research Excellence Award

Professor | Northwest A&F University | China

Prof. Bin Liu is a researcher at Northwest A&F University, Yangling, China, with expertise in artificial intelligence, computer vision, agricultural informatics, and large-scale model training. He has published 69 Scopus-indexed documents, receiving approximately 2,949 citations and achieving an h-index of 18, reflecting sustained academic impact. His recent work focuses on multi-source data fusion, multimodal learning, remote sensing change detection, and efficient parallel training pipelines for large models, with publications in reputable venues such as IEEE Transactions on Computers, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, and Applied Sciences. Liu has collaborated with over 140 co-authors, demonstrating strong interdisciplinary and international research engagement. His research contributes to societal needs by advancing intelligent agricultural disease diagnosis, improving crop monitoring, and enhancing the efficiency of large-scale AI systems, supporting sustainable agriculture and data-driven environmental management.

Citation Metrics (Scopus)

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2,949

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 View Scopus Profile

Featured Publications


MDS-Net: An image-text enhanced multimodal dual-branch Siamese network for remote sensing change detection


– IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025

PRT: An efficient pipeline reuse technology for large models training


– IEEE International Conference on Cluster Computing (CLUSTER), 2025

VMF-SSD: A novel V-space based multi-scale feature fusion SSD for apple leaf disease detection


– IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023

Aleeza Adeel | Computer Science | Research Excellence Award

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Mrs. Aleeza Adeel | Computer Science | Research Excellence Award

The University of Waikato | New Zealand

Mrs. Aleeza Adeel is a Ph.D. student at the School of Computing and Mathematical Sciences, University of Waikato, New Zealand, specializing in digital twin frameworks, sustainable energy systems, and user-centered computing solutions. Her research focuses on developing interoperable and scalable digital twin technologies to optimize energy system management, enhance operational efficiency, and support sustainable resource utilization. She has contributed to peer-reviewed publications, including a recent article in Energies on an interoperable user-centered digital twin framework, demonstrating her commitment to integrating advanced computational models with real-world energy systems. Aleeza collaborates with interdisciplinary researchers, including experts in energy management and computational modeling, to ensure her work addresses both technical rigor and societal relevance. Her research contributes to sustainable energy transitions by providing data-driven, user-centric solutions that improve system performance, reduce environmental impact, and support informed decision-making in complex energy infrastructures.

Profile: View ORCID Profile 

Featured Publication


An Interoperable User‑Centred Digital Twin Framework for Sustainable Energy System Management

– Adeel, A., Apperley, M., & Walmsley, T. G., Energies, 2026, 19(2), Article 333

Miroslaw Kozielski | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Mr. Miroslaw Kozielski | Computer Science | Best Researcher Award

Kazimierz Wielki University | Poland

Mr. Mirosław Kozielski is a researcher at Kazimierz Wielki University in Bydgoszcz, Poland, specializing in computer science, with a strong focus on natural language processing (NLP), industrial informatics, and Industry 4.0/5.0 technologies. His research addresses the use of intelligent language-based systems for automated industrial documentation, knowledge representation, and digital transformation in modern manufacturing environments. He has authored 7 peer-reviewed publications, which have accumulated 35 citations, and holds an h-index of 3, reflecting a focused and emerging academic impact. Dr. Kozielski collaborates with interdisciplinary teams, contributing to the integration of artificial intelligence with industrial and organizational processes. His work supports the development of efficient, human-centric, and sustainable industrial systems, with societal impact through improved documentation quality, enhanced knowledge accessibility, and the practical adoption of advanced AI-driven solutions in contemporary industrial ecosystems.

Citation Metrics (Scopus)

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 View ORCID Profile

Featured Publications

Volodymyr Polishchuk | Computer Science | Best Researcher Award

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Prof. Volodymyr Polishchuk | Computer Science | Best Researcher Award

Uzhhorod National University, Ukraine

Volodymyr Polishchuk is a distinguished academic specializing in information technology, fuzzy systems, and decision-making models. Currently serving as a Professor at both Uzhhorod National University in Ukraine and the Technical University of Košice in Slovakia, he has made significant contributions to the fields of artificial intelligence, risk assessment, and sustainable tourism. With a career spanning over a decade, he has co-authored numerous publications, including journal articles and book chapters, focusing on the application of advanced decision models in various sectors. His research is internationally recognized, and he is an active member of several academic networks. He is known for his interdisciplinary approach, bridging information technology with real-world challenges such as healthcare, aviation education, and urban development.

Professional Profile 

Education

Volodymyr Polishchuk holds a prestigious Doctor of Sciences (DrSc.) degree from Uzhhorod National University, where he also completed his undergraduate and graduate education. His academic journey in information technology, mathematics, and fuzzy systems laid a strong foundation for his future research and teaching. As a professor at the university, he has guided numerous students and collaborated on innovative projects. Additionally, his academic credentials are complemented by his position at the Technical University of Košice in Slovakia, where he continues to contribute to cutting-edge research in his fields of expertise. His educational background supports his broad interdisciplinary approach, allowing him to address complex problems in various domains such as tourism, healthcare, and risk management.

Professional Experience

Professor Polishchuk has been a dedicated faculty member at Uzhhorod National University since 2011, where he teaches and conducts research at the Faculty of Information Technology. Over the years, he has gained recognition for his expertise in decision-making models and fuzzy systems. In addition to his role at Uzhhorod, he has been a professor at the Technical University of Košice, Slovakia. His professional experience extends beyond teaching, as he has collaborated on numerous international research projects and published widely in top-tier journals. He has also worked on hybrid decision models for risk assessment in sectors such as sustainable tourism, healthcare, and aviation education. His leadership in academic research has earned him recognition through various academic platforms, and he continues to actively engage with the global research community.

Research Interests

Volodymyr Polishchuk’s research primarily focuses on information technology, fuzzy systems, and decision-making models, with a particular emphasis on their practical applications across various industries. He is deeply engaged in developing hybrid models for evaluating complex processes, such as tourism sustainability, risk assessment, and healthcare outcomes. His work also explores the integration of artificial intelligence in decision-making, specifically in aviation education and urban development. Additionally, he is interested in the application of multicriteria decision analysis (MCDA) in solving real-world challenges. Polishchuk’s interdisciplinary approach allows him to connect cutting-edge technology with pressing global issues, contributing valuable insights to sectors like smart cities, start-up financing, and pandemic management. His research has significant implications for optimizing resource allocation, improving system efficiency, and mitigating risks in both public and private sectors.

Awards and Honors

Throughout his academic career, Volodymyr Polishchuk has earned several prestigious honors and recognition for his contributions to research and education. His interdisciplinary approach to problem-solving has led to numerous successful collaborations with leading academic and industry experts across Europe. He has been acknowledged by his peers for his innovative contributions to the fields of fuzzy logic, decision support systems, and sustainability models. Polishchuk’s research papers are widely cited, indicating the significant impact his work has had on the academic community. His exceptional leadership in research has also helped foster international collaborations, particularly in the development of sustainable tourism models and risk assessment frameworks for emerging sectors. His continued excellence in academia and research is further demonstrated by his involvement in high-impact projects and his active participation in global conferences.

Publications Top Noted

  1. Artificial Intelligence Technology for Assessing the Practical Knowledge of Air Traffic Controller Students Based on Their Responses in Multitasking Situations
    • Authors: Antoško, M., Polishchuk, V., Kelemen, M., Korniienko, A., Kelemen, M.
    • Year: 2025
    • Journal: Applied Sciences (Switzerland)
    • Volume: 15(1), 308
    • Citations: 0
  2. A large-scale decision-making model for the expediency of funding the development of tourism infrastructure in regions
    • Authors: Skare, M., Gavurova, B., Polishchuk, V.
    • Year: 2025
    • Journal: Expert Systems
    • Volume: 42(1), e13443
    • Citations: 1
  3. On Convergence of the Uniform Norm and Approximation for Stochastic Processes from the Space Fψ(Ω)
    • Authors: Rozora, I., Mlavets, Y., Vasylyk, O., Polishchuk, V.
    • Year: 2024
    • Journal: Journal of Theoretical Probability
    • Volume: 37(2), pp. 1627–1653
    • Citations: 0
  4. THE IMPACT OF DIGITAL DISINFORMATION ON QUALITY OF LIFE: A FUZZY MODEL ASSESSMENT
    • Authors: Gavurova, B., Moravec, V., Hynek, N., Petruzelka, B., Stastna, L.
    • Year: 2024
    • Journal: Technological and Economic Development of Economy
    • Volume: 30(4), pp. 1120–1145
    • Citations: 0
  5. An information-analytical system for assessing the level of automated news content according to the population structure – A platform for media literacy system development
    • Authors: Gavurova, B., Skare, M., Hynek, N., Moravec, V., Polishchuk, V.
    • Year: 2024
    • Journal: Technological Forecasting and Social Change
    • Volume: 200, 123161
    • Citations: 0
  6. Decision Support System Regarding the Possibility of Financing Cross-Border Cooperation Projects
    • Authors: Polishchuk, V., Kelemen, M., Polishchuk, I., Kelemen, M.
    • Year: 2024
    • Conference: CEUR Workshop Proceedings
    • Volume: 3702, pp. 58–71
    • Citations: 0
  7. Hybrid Mathematical Model of Risk Assessment of UAV Flights Over Airports
    • Authors: Polishchuk, V., Kelemen, M., Kelemen, M., Scerba, M.
    • Year: 2024
    • Conference: New Trends in Civil Aviation
    • Citations: 0
  8. A Fuzzy Multicriteria Model of Sustainable Tourism: Examples From the V4 Countries
    • Authors: Skare, M., Gavurova, B., Polishchuk, V.
    • Year: 2024
    • Journal: IEEE Transactions on Engineering Management
    • Volume: 71, pp. 12182–12193
    • Citations: 6
  9. Fuzzy multicriteria evaluation model of cross-border cooperation projects under resource curse conditions
    • Authors: Skare, M., Gavurova, B., Polishchuk, V.
    • Year: 2023
    • Journal: Resources Policy
    • Volume: 85, 103871
    • Citations: 3
  10. A fuzzy model for evaluating the level of satisfaction of tourists regarding accommodation establishments according to social class on the example of V4 countries
  • Authors: Skare, M., Gavurova, B., Polishchuk, V., Nawazish, M.
  • Year: 2023
  • Journal: Technological Forecasting and Social Change
  • Volume: 193, 122609
  • Citations: 7

Rajeev Ratna Vallabhuni | Computer Science | Young Scientist Award

Published on by Global Scholar Awards

Mr. Rajeev Ratna Vallabhuni | Computer Science | Young Scientist Award

Application Developer at Texans IT Services Inc., India

Rajeev Ratna Vallabhuni is an accomplished Application Developer with a rich background in computer science, technology, and engineering. He has contributed significantly to the field through several innovative patents in areas such as blockchain-based cloud applications, machine learning, and IoT security. His work spans various domains including AI/ML, image processing, and network management, with numerous research publications in international journals and conferences. With experience at Bayview Asset Management, LLC, he has a strong track record of applying cutting-edge technologies to real-world applications. His expertise in both academic and professional settings makes him a leading figure in the field of information technology and software development.

Professional Profile 

Education

Rajeev Ratna Vallabhuni holds a Master of Science in Information Technology Management from Campbellsville University, Kentucky, and a Master of Science in Computer Science Engineering from Northwestern Polytechnic University, California, USA. He also completed his Bachelor of Technology in Information and Technology at Vignan University, India. His educational foundation has equipped him with a diverse skill set, allowing him to specialize in software development, computer engineering, and cutting-edge technological innovations.

Professional Experience

Rajeev currently works as an Application Developer at Bayview Asset Management, LLC, where he plays a key role in developing and optimizing software applications. His previous professional experience includes working on various projects related to AI/ML, blockchain, and IoT security. He has contributed to numerous patents, book chapters, and international journal publications. Rajeev’s expertise spans both technical development and leadership, and his ability to integrate machine learning and deep learning techniques into practical solutions has made him a valuable asset in the tech industry.

Research Interest

Rajeev Ratna Vallabhuni’s research interests lie at the intersection of artificial intelligence, machine learning, cloud computing, and Internet of Things (IoT) technologies. His work primarily focuses on enhancing the security of IoT networks, leveraging blockchain for decentralized application architectures, and utilizing deep learning models for image and signal processing. Rajeev is also interested in exploring advanced computational methods for improving network management, resource allocation, and real-time data processing in cloud environments. His innovative research aims to develop scalable, efficient, and secure solutions for modern computing challenges, bridging the gap between theoretical algorithms and real-world applications.

Awards and Honors

Rajeev Ratna Vallabhuni has received numerous accolades for his contributions to the fields of software development, machine learning, and IoT security. Notable recognitions include multiple patents for his innovations in blockchain-based applications, AI/ML, and security systems. He has been awarded fellowships and scholarships during his academic career, showcasing his dedication to pushing the boundaries of technology. Additionally, Rajeev’s research has been published in prestigious international journals and recognized at numerous conferences, further cementing his reputation as a leading figure in his field.

Publications Top Noted

  • Smart cart shopping system with an RFID interface for human assistance
    Authors: RR Vallabhuni, S Lakshmanachari, G Avanthi, V Vijay
    Year: 2020
    Citation: 92
  • Performance analysis: D-Latch modules designed using 18nm FinFET Technology
    Authors: RR Vallabhuni, G Yamini, T Vinitha, SS Reddy
    Year: 2020
    Citation: 85
  • Disease prediction based retinal segmentation using bi-directional ConvLSTMU-Net
    Authors: BMS Rani, VR Ratna, VP Srinivasan, S Thenmalar, R Kanimozhi
    Year: 2021
    Citation: 68
  • ECG performance validation using operational transconductance amplifier with bias current
    Authors: V Vijay, CVSK Reddy, CS Pittala, RR Vallabhuni, M Saritha, M Lavanya, …
    Year: 2021
    Citation: 63
  • A Review On N-Bit Ripple-Carry Adder, Carry-Select Adder And Carry-Skip Adder
    Authors: V Vijay, M Sreevani, EM Rekha, K Moses, CS Pittala, KAS Shaik, …
    Year: 2022
    Citation: 62
  • Speech Emotion Recognition System With Librosa
    Authors: PA babu, VS Nagaraju, RR Vallabhuni
    Year: 2021
    Citation: 62
  • 6Transistor SRAM cell designed using 18nm FinFET technology
    Authors: RR Vallabhuni, P Shruthi, G Kavya, SS Chandana
    Year: 2020
    Citation: 60
  • Universal Shift Register Designed at Low Supply Voltages in 20nm FinFET Using Multiplexer
    Authors: RR Vallabhuni, J Sravana, CS Pittala, M Divya, BMS Rani, S Chikkapally, …
    Year: 2021
    Citation: 58
  • Numerical analysis of various plasmonic MIM/MDM slot waveguide structures
    Authors: CS Pittala, RR Vallabhuni, V Vijay, UR Anam, K Chaitanya
    Year: 2022
    Citation: 57
  • Design of Comparator using 18nm FinFET Technology for Analog to Digital Converters
    Authors: RR Vallabhuni, DVL Sravya, MS Shalini, GU Maheshwararao
    Year: 2020
    Citation: 55
  • High Speed Energy Efficient Multiplier Using 20nm FinFET Technology
    Authors: VR Ratna, S M, S N, V V, PC Shaker, D M, S Sadulla
    Year: 2021
    Citation: 53
  • Physically unclonable functions using two-level finite state machine
    Authors: V Vijay, K Chaitanya, CS Pittala, SS Susmitha, J Tanusha, …
    Year: 2022
    Citation: 48
  • Realization and comparative analysis of thermometer code based 4-bit encoder using 18 nm FinFET technology for analog to digital converters
    Authors: CS Pittala, V Parameswaran, M Srikanth, V Vijay, V Siva Nagaraju, …
    Year: 2021
    Citation: 45
  • Comparative validation of SRAM cells designed using 18nm FinFET for memory storing applications
    Authors: RR Vallabhuni, KC Koteswaramma, B Sadgurbabu, A Gowthamireddy
    Year: 2020
    Citation: 45