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

Shahid Latif | Computer Science | Innovative Research Award

Published on by Global Scholar Awards

Innovative Research Award

Shahid Latif
University of the West of England, United Kingdom

Shahid Latif
Researcher Shahid Latif
Affiliation University of the West of England
Country United Kingdom
Scopus ID 57216963065
Documents 42
Citations 1,494
h-index 14
Subject Area Computer Science
Event Global Scholar Awards
ORCID 0000-0002-6368-2729

The Innovative Research Award recognizes the scholarly achievements and research contributions of Shahid Latif from the University of the West of England, United Kingdom. The recognition highlights academic engagement within the field of Computer Science and acknowledges contributions to interdisciplinary technological research, scientific dissemination, and internationally indexed scholarly communication.[1] The award reflects measurable academic visibility through citation performance, publication activity, and collaborative research participation within global scientific communities.[2]

Abstract

Shahid Latif maintains an internationally visible academic research profile associated with Computer Science and interdisciplinary technological innovation. The researcher’s scholarly activities include peer-reviewed publication, citation-based impact, and international research dissemination through recognized academic platforms.[1] Research visibility and scholarly engagement are further supported through academic identifiers and professional research networking systems.[2]

Keywords

  • Computer Science
  • Artificial Intelligence
  • Research Innovation
  • Scholarly Publications
  • Academic Impact
  • Scopus Indexed Research
  • Interdisciplinary Technology

Introduction

Academic recognition frameworks are designed to acknowledge scholarly excellence, publication visibility, research dissemination, and interdisciplinary scientific contribution. The Innovative Research Award associated with the Global Scholar Awards recognizes researchers demonstrating measurable academic impact and engagement within internationally indexed research environments.[1] Shahid Latif’s academic profile reflects sustained participation in Computer Science research and collaborative technological inquiry. Citation indicators, indexed publications, and scholarly networking profiles collectively demonstrate academic engagement and scientific communication within contemporary research systems.[3]

Research Profile

Shahid Latif is affiliated with the University of the West of England in the United Kingdom and maintains an internationally indexed Scopus author profile documenting research output, citations, and scholarly visibility.[1] The profile currently reflects forty-two indexed documents, 1,494 citations, and an h-index value of fourteen, indicating active scholarly participation and measurable academic impact. Research activities associated with the scholar are connected to Computer Science, intelligent systems, computational innovation, and interdisciplinary technological applications. Scholarly communication through international academic databases supports discoverability and global research accessibility.

Research Contributions

The scholarly contributions associated with Shahid Latif include participation in peer-reviewed research publication, citation-based dissemination, and interdisciplinary computational investigation. Indexed publications contribute to international scientific accessibility and broader academic communication within technological research communities.[1]

  • Contribution to peer-reviewed scientific publication and interdisciplinary research dissemination.
  • Participation in internationally indexed scholarly communication platforms.
  • Research engagement in intelligent computational systems and technological innovation.
  • Support for collaborative scientific inquiry and citation-based academic impact.

Publications

The Scopus author profile associated with Shahid Latif documents scholarly outputs indexed through internationally recognized academic databases.[1] Publication activity contributes to citation-based evaluation, academic visibility, and interdisciplinary scientific communication.[4]  Professional research identifiers including ORCID, Google Scholar, and ResearchGate profiles support discoverability, verification, and accessibility of scholarly contributions within international academic systems.[2][3]

  1. Research articles related to Computer Science and intelligent computational systems.
  2. Peer-reviewed journal and conference publications indexed within scholarly databases.
  3. Academic outputs contributing to citation-based dissemination and scientific accessibility.

Research Impact

Research impact is commonly evaluated through publication visibility, citation activity, scholarly accessibility, and interdisciplinary relevance. Citation metrics associated with Shahid Latif demonstrate measurable engagement within the international research community and broader scientific communication networks.[1] Academic recognition through international award frameworks may support collaboration, institutional engagement, and continued participation in global research initiatives associated with Computer Science and technological innovation.

Award Suitability

The academic profile of Shahid Latif reflects characteristics commonly associated with scholarly recognition programs, including indexed publication activity, measurable citation performance, interdisciplinary engagement, and participation in internationally visible research dissemination systems.[1] Research visibility through professional academic identifiers and scholarly networking systems further supports recognition within contemporary scientific communication environments.[2][4]

Conclusion

Shahid Latif’s scholarly profile demonstrates sustained participation in academic publication, interdisciplinary technological inquiry, and international research dissemination associated with Computer Science and innovation-oriented scientific investigation. Indexed publications, citation indicators, and professional academic profiles collectively support visibility within global scholarly systems.[1] The Innovative Research Award represents recognition of ongoing scholarly engagement, academic communication, and participation in internationally recognized research environments supported through citation databases and professional research identification systems.[2]

References

  1. Elsevier. (n.d.). Scopus author details: Shahid Latif, Author ID 57216963065. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57216963065
  2. ORCID. (n.d.). ORCID researcher profile for Shahid Latif.
    https://orcid.org/0000-0002-6368-2729
  3. Google Scholar. (n.d.). Scholar profile of Shahid Latif.
    https://scholar.google.com/citations?user=CThRoJQAAAAJ&hl=en
  4. ResearchGate. (n.d.). ResearchGate profile of Shahid Latif.
    https://www.researchgate.net/profile/Shahid-Latif-11

Yonghuang Wu | Computer Science | Research Excellence Award

Published on by Global Scholar Awards

Research Excellence Award

Yonghuang Wu
Fudan University, China

Researcher Information
Affiliation Fudan University
Country China
Scopus ID 58151097300
Documents 5
Citations 80
h-index 2
Subject Area Computer Science
Event Global Scholar Award

The Research Excellence Award recognition profile for Mr. Yonghuang Wu presents an academic overview of his scholarly activities and research engagement in the field of Computer Science. Affiliated with Fudan University, China, Mr. Wu has contributed to research outputs indexed within internationally recognized academic databases. His publication metrics, citation record, and interdisciplinary involvement reflect continued participation in contemporary computational and scientific investigations.[1][3]

Abstract

This article documents the academic profile and scholarly indicators associated with Mr. Yonghuang Wu of Fudan University. The profile is based on publicly accessible bibliometric information, including indexed publications, citation performance, and subject specialization within Computer Science.[1][2]

Keywords

Computer Science; Scholarly Communication; Citation Analysis; Research Metrics; Academic Recognition; Bibliometrics.[1]

Introduction

Academic recognition systems frequently assess researchers through publication quality, citation performance, research consistency, and scholarly contribution.[2][4]

Fudan University provides a strong academic environment supporting interdisciplinary and computational research initiatives. Mr. Yonghuang Wu has participated in scholarly activities associated with internationally indexed research dissemination.[1][4]

Research Profile

Mr. Yonghuang Wu is affiliated with Fudan University in China and is associated with research activities in Computer Science. According to available bibliometric records, his scholarly profile includes five indexed documents with eighty citations and an h-index of two.[1]

Bibliometric indicators such as citations and h-index are widely used to evaluate research visibility and scholarly engagement within international academic systems.[2]

Research Contributions

The research contributions associated with Mr. Wu demonstrate participation in computational investigations and peer-reviewed academic dissemination relevant to Computer Science.[1]

Collaborative scientific publication contributes to methodological advancement, interdisciplinary communication, and scholarly knowledge exchange.

Publications

The publication portfolio associated with Mr. Yonghuang Wu includes research outputs indexed within internationally recognized academic databases. Such indexed publications contribute to scholarly visibility and scientific dissemination.[1]

Research Impact

Research impact is frequently evaluated through citation metrics, academic engagement, and contribution to scholarly communication networks. Citation activity associated with Mr. Wu reflects measurable research dissemination.[1][2]

Award Suitability

The documented publication record, citation metrics, and indexed scholarly contributions align with common evaluation criteria applied within international research recognition programs such as the Global Scholar Award.[2][4]

Conclusion

This article presents a structured academic overview of Mr. Yonghuang Wu and his measurable scholarly indicators associated with Fudan University and the field of Computer Science. The available bibliometric data reflect continued participation in scholarly communication and indexed academic dissemination.[1][3]

References

  1. Elsevier. (n.d.). Scopus author details: Mr. Yonghuang Wu, Author ID 58151097300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58151097300
  2. Li, Y., Wu, Y., Luo, Y., Sun, L., Qin, Z., Qiu, L., Cao, X., & Cai, X. (2025). Instance-level randomization: Toward more stable LLM evaluations. In Findings of the Association for Computational Linguistics: EMNLP 2025.
    https://doi.org/10.18653/v1/2025.findings-emnlp.182
  3. ORCID. (n.d.). ORCID profile record for Mr. Yonghuang Wu. ORCID Registry.
    https://orcid.org/0000-0002-5804-5573
  4. Global Scholar Awards. (n.d.). International academic recognition and scholarly evaluation framework.
    https://globalscholarawards.com/

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)

2949
2200
1500
700
0

Citations

2,949

Documents

69

h-index

18

Citations

Documents

h-index

View Scopus Profile
 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

Published on by Global Scholar Awards

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)

35
25
15
5
0

Citations

35

Documents

7

h-index

3

Citations

Documents

h-index

View Scopus Profile
 View ORCID Profile

Featured Publications

Christian Schachtner | Computer Science | Research Excellence Award

Published on by Global Scholar Awards

Prof. Dr. Christian Schachtner | Computer Science | Research Excellence Award

Professor of Business Informatics | RheinMain University of Applied Sciences | Germany

Dr. Christian Schachtner is a researcher at Fachhochschule Wiesbaden, Germany, specializing in safety culture, social impact assessment, and sustainable development in technical and organizational systems. His work bridges corporate social responsibility, environmental management, and smart district development, emphasizing practical solutions to complex societal challenges. According to Scopus, he has authored 23 scholarly publications, received 9 citations, and holds an h-index of 2. His recent research includes open-access work on the determinants of social impact through safety culture in technical organizations and scholarly contributions to book chapters on smart regional and district development initiatives. Dr. Schachtner actively collaborates with international researchers, supporting interdisciplinary perspectives and knowledge exchange. His research contributes to improving organizational governance, enhancing safety performance, and promoting socially responsible and sustainable practices across technical and socio-economic domains.

Citation Metrics (Scopus)

23
15
10
5
0

Citations

9

Documents

23

h-index

2

Citations

Documents

h-index

View Google Scholar Profile
 View Scopus Profile
 View ORCID Profile

Featured Publications

Sarbajit Paul Bappy | Computer Science | Research Excellence Award

Published on by Global Scholar Awards

Mr. Sarbajit Paul Bappy | Computer Science | Research Excellence Award

Teaching Assistant | Daffodil International University | Bangladesh

Sarbajit Paul Bappy is an emerging researcher in computer science with a growing focus on applied machine learning, medical image analysis, and agricultural informatics. He is currently serving as a Teaching Assistant in the Department of Computer Science and Engineering at Daffodil International University, Bangladesh, where he has been contributing to academic instruction and research support since 2025. Alongside his professional role, he is pursuing his undergraduate degree in Computer Science and Engineering at the same institution, demonstrating a strong integration of academic excellence and early-career research productivity. His scholarly work includes peer-reviewed publications and openly accessible datasets that address critical challenges in healthcare diagnostics and smart agriculture. Notably, he co-authored SkinVisualNet: A Hybrid Deep Learning Approach Leveraging Explainable Models for Identifying Lyme Disease from Skin Rash Images (MAKE, 2025), which combines deep learning with explainable AI techniques to enhance early disease detection. He also contributed significantly to the dataset Jackfruit AgroVision, a comprehensive benchmark for disease detection in jackfruit and its leaves, supporting advancements in precision agriculture and food-security research. His collaborations span multidisciplinary teams involving experts such as Amir Sohel, Rittik Chandra Das Turjy, Md Assaduzzaman, Ahmed Al Marouf, Jon George Rokne, and Reda Alhajj, illustrating his ability to contribute within diverse international research groups. Through his ongoing work in AI-driven health diagnostics, dataset development, and sustainable agricultural technology, Bappy aims to advance research that supports societal well-being, improves disease detection accuracy, and contributes to innovation within global machine learning communities.

Profiles: Google Scholar | ORCID | LinkedIn

Featured Publications

1. Sohel, A., Turjy, R. C. D., Bappy, S. P., Assaduzzaman, M., Marouf, A. A., Rokne, J. G., & Alhajj, R. (2025). SkinVisualNet: A Hybrid Deep Learning Approach Leveraging Explainable Models for Identifying Lyme Disease from Skin Rash Images. Machine Learning and Knowledge Extraction, 7(4), 157. https://doi.org/10.3390/make7040157  MDPI+1

2. Sohel, A., Bijoy, M. H. I., Turjy, R. C. D., & Bappy, S. P. (2025). Jackfruit AgroVision: A Extensive Dataset for Jackfruit Disease and Leaf Disease Detection using Machine Learning. Mendeley Data. https://doi.org/10.17632/pt647jfn52.1