Mazen Ramadhan | Computer Science | Innovative Research Award

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

Yuriy Perevalov | Engineering | Best Faculty Award

Best Faculty Award

Yuriy Perevalov
Saint Petersburg Electrotechnical University, Russia

Yuriy Perevalov
Researcher Yuriy Perevalov
Affiliation Saint Petersburg Electrotechnical University
Country Russia
Scopus ID 57200258235
Documents 26
Citations 29
h-index 3
Subject Area Engineering
Event Global Scholar Awards
ORCID
0000-0001-8703-7815

The Best Faculty Award recognizes the scholarly and academic contributions of Yuriy Perevalov from Saint Petersburg Electrotechnical University, Russia. The recognition highlights academic engagement in Engineering research, scientific dissemination, and interdisciplinary scholarly activities through internationally indexed publications and collaborative academic participation.[1] The researcher’s academic profile reflects sustained participation in research communication, technical innovation, and measurable scholarly visibility within international academic communities.[2]

Abstract

Yuriy Perevalov is associated with internationally indexed academic activities in Engineering and related technological disciplines. The academic profile demonstrates engagement in peer-reviewed publication, citation-based research visibility, and interdisciplinary scientific collaboration through recognized scholarly databases.[1] Research dissemination through ORCID, Google Scholar, and ResearchGate contributes to the accessibility and discoverability of scholarly outputs within the international research environment.[2][3]

Keywords

  • Engineering Research
  • Academic Publications
  • Scientific Communication
  • Research Visibility
  • Interdisciplinary Engineering
  • Scholarly Impact
  • Global Scholar Awards

Introduction

Academic recognition programs acknowledge scholarly excellence, research dissemination, and institutional contribution within international scientific communities. The Best Faculty Award associated with the Global Scholar Awards framework recognizes researchers demonstrating measurable academic participation, publication activity, and interdisciplinary collaboration through globally indexed scholarly systems.[1] Yuriy Perevalov’s academic profile reflects scholarly engagement in Engineering and related technical domains. Citation metrics, indexed publications, and professional research identifiers collectively contribute to scholarly visibility and academic communication within contemporary research environments.[2]

Research Profile

Yuriy Perevalov is affiliated with Saint Petersburg Electrotechnical University in Russia and maintains an internationally indexed research presence through Scopus and associated scholarly platforms.[1] The academic profile includes twenty-six indexed documents, twenty-nine citations, and an h-index of three, indicating active participation in scientific publication and scholarly dissemination. Research activities associated with the scholar are connected to Engineering, applied technologies, and interdisciplinary scientific innovation. Academic dissemination through recognized researcher identity systems enhances research discoverability and institutional visibility.[2][3]

Research Contributions

The scholarly contributions associated with Yuriy Perevalov support academic communication and interdisciplinary engineering research through peer-reviewed publications and indexed scientific dissemination.[1] Research activities reflect engagement with technical innovation, collaborative inquiry, and scholarly knowledge exchange within engineering-focused academic communities.

  • Participation in peer-reviewed engineering publication activities.
  • Contribution to internationally indexed research dissemination.
  • Engagement in interdisciplinary technical and engineering research.
  • Support for collaborative academic communication and scientific exchange.

Publications

The Scopus profile associated with Yuriy Perevalov documents scholarly outputs and citation indicators connected to Engineering and technological research dissemination.[1] Publication indexing through international academic databases supports accessibility, citation tracking, and interdisciplinary scientific communication.[4] Digital research identifiers including ORCID, Google Scholar, and ResearchGate profiles support publication discoverability, citation accessibility, and professional academic visibility within international scholarly environments.[2][3]

  1. Peer-reviewed journal and conference publications related to engineering research.
  2. Indexed scientific outputs contributing to technical academic communication.
  3. Research dissemination through internationally recognized scholarly systems.

Research Impact

Research impact may be evaluated through citation activity, publication indexing, scholarly engagement, and interdisciplinary relevance. The academic metrics associated with Yuriy Perevalov indicate measurable participation in engineering research communication and scientific dissemination activities.[1] Recognition through international academic award frameworks may contribute to institutional visibility, collaborative networking, and broader participation in global scholarly initiatives and scientific dialogue.[4]

Award Suitability

The academic profile of Yuriy Perevalov reflects characteristics commonly associated with scholarly recognition programs, including publication activity, interdisciplinary engagement, citation visibility, and sustained participation in scientific communication through internationally indexed research systems.[1] The researcher’s scholarly activities within Engineering and related technological fields contribute to technical innovation, collaborative inquiry, and broader academic dissemination objectives within modern scientific research environments.

Conclusion

Yuriy Perevalov’s academic profile demonstrates participation in engineering scholarship, interdisciplinary scientific communication, and internationally indexed research dissemination. Indexed publications, citation indicators, and professional academic visibility collectively support recognition within international scholarly and technological communities.[1] The Best Faculty Award under the Global Scholar Awards framework represents acknowledgment of scholarly engagement, institutional contribution, and continued participation in global academic and research systems.[4]

References

  1. Elsevier. (n.d.). Scopus author details: Yuriy Perevalov, Author ID 57200258235. Scopus.

    https://www.scopus.com/authid/detail.uri?authorId=57200258235
  2. ORCID. (n.d.). ORCID researcher profile for Yuriy Perevalov.

    https://orcid.org/0000-0001-8703-7815
  3. Google Scholar. (n.d.). Scholar profile of Yuriy Perevalov.

    https://scholar.google.com/citations?user=H-xf6RkAAAAJ&hl=en&oi=sra
  4. ResearchGate. (n.d.). ResearchGate profile of Yuriy Perevalov.

    https://www.researchgate.net/profile/Yuriy-Perevalov-2

Shahid Latif | Computer Science | Innovative Research Award

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

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/

Aleeza Adeel | Computer Science | Research Excellence Award

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

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

Zhaozhen Jiang | Computer Science | Best Research Article Award

Dr. Zhaozhen Jiang | Computer Science | Best Research Article Award

Assistant Researcher | Naval Submarine Academy | China

Dr. Zhaozhen Jiang is a distinguished researcher at the Navy Submarine Academy in Qingdao, China, specializing in intelligent systems, maritime navigation, and dynamic target search. His research focuses on the development of advanced path-planning algorithms and neural network–based optimization techniques for complex maritime environments. He has published extensively and collaborated widely with researchers across multiple disciplines, reflecting a strong commitment to interdisciplinary innovation. His recent work on GBNN-based maritime dynamic target search demonstrates a focus on enhancing operational decision-making and situational awareness in challenging naval contexts. Through his research, he aims to advance autonomous maritime systems and contribute to safer, more efficient naval operations, while fostering technological progress with meaningful societal impact.

Citation Metrics (Scopus)

40
30
20
10
0

Citations

37

Documents

15

h-index

4

Citations

Documents

h-index

View Scopus Profile

Featured Publications

Lili Zhan | Artificial Intelligence | Best Researcher Award

Assoc. Prof. Dr. Lili Zhan | Artificial Intelligence | Best Researcher Award

Associate Professor| Shandong University of Science and Technology | China

Assoc. Prof. Dr. Lili Zhan is a researcher whose work spans remote sensing, Arctic cryosphere monitoring, computer vision, and artificial intelligence–enhanced educational systems. Her scholarship incorporates both physical environmental analysis and advanced data-driven methodologies, with representative contributions including sensitivity analyses of microwave brightness temperature to variations in snow depth on Arctic sea ice, a deep-learning-based remote-sensing scene-classification framework employing EfficientNet-B7, and an improved YOLOv7 instance-segmentation method for ship detection in complex SAR imagery Lili-Zhan. She has also contributed to the design and implementation of intelligent teaching models grounded in contemporary AI and data-centric approaches, demonstrating interdisciplinarity across geospatial sciences and educational technology Lili-Zhan Across these domains, her work reflects a sustained commitment to methodological innovation, integrating state-of-the-art neural architectures with domain-specific challenges in environmental monitoring and maritime situational awareness. Her collaborations often bridge academic research groups focused on cryosphere change, Earth observation, and applied machine learning, enabling the development of tools that support improved climate understanding, maritime safety, and digital-education modernization. Although publication and citation metrics are not specified in the available document, the range of research topics and representative studies indicates a growing scholarly profile with contributions positioned at the intersection of remote-sensing physics and intelligent systems engineering. Collectively, her work holds global societal relevance: enhancing the accuracy of cryospheric measurements supports climate-model improvement and polar-region policy planning; advancing ship-detection techniques contributes to marine governance, environmental protection, and emergency response; and promoting AI-supported pedagogical frameworks aids the digital transformation of education.

Profile: Scopus 

Featured Publications

Zhan, L. (Year). SAR ship target instance segmentation based on SISS-YOLO. Journal Name, Volume(Issue), pages.

Lili Zhan’s work advances the precision of remote-sensing analytics and intelligent detection systems, strengthening global capabilities in environmental monitoring and maritime safety. Her innovations support science-driven decision-making with direct benefits for climate resilience and societal securit

Mona Almutairi | Artificial Intelligence | Best Researcher Award

Ms. Mona Almutairi | Artificial Intelligence | Best Researcher Award

Shaqra University | Saudi Arabia

Ms. Mona Almutairi is a highly motivated computer science graduate with a strong academic foundation and practical experience in system engineering and data management. She completed her Bachelor’s degree in Computer Science from Shaqra University in 2019 with an impressive GPA of 4.19 out of 5, demonstrating consistent academic excellence. Her professional experience includes serving as a System Engineer at the Ministry of Economy and Planning, where she contributed to optimizing systems operations and enhancing digital workflows, as well as volunteering as a Data Entry Assistant at the Ministry of Health, where she efficiently managed and organized large datasets with accuracy and confidentiality. She further enriched her technical expertise through professional courses in Software Engineering from the Saudi Digital Academy and Web Development from the Ministry of Communications and Information Technology, equipping her with up-to-date industry knowledge and coding proficiency. Her research interests lie in software development, data analysis, and emerging technologies that integrate innovation with societal advancement. Ms. Almutairi’s research skills include proficiency in data analysis tools, problem-solving, and the ability to apply algorithmic thinking to real-world challenges. She is also adept at using Microsoft Office and has strong communication, teamwork, and adaptability skills, making her a collaborative and reliable professional. Her dedication to learning and excellence has been recognized through various academic and professional achievements, reflecting her commitment to continuous improvement. Overall, Ms. Almutairi is a forward-thinking computer scientist who combines technical knowledge, analytical capabilities, and professional experience to drive innovation in the field of information technology.

Profiles: Google Scholar | ORCID

Featured Publications

Almutairi, M., & Dardouri, S. (2025). Intelligent hybrid modeling for heart disease prediction. Information, 16(10), 869. Citations: 1

Afeez Soladoye | Machine learning | Young Scientist Award

Mr. AfeezSoladoye | Machine learning | Young Scientist Award

Lecturer at Federal university Oye-Ekiti, Nigeria

Soladoye Afeez Adekunle is a promising young scholar in Computer Engineering, currently pursuing his Ph.D. at the Federal University Oye-Ekiti. With a Master’s degree earned with distinction, he has demonstrated strong academic and research capabilities. His work spans machine learning, artificial intelligence, and applied computing, including the development of medical prediction systems and fake news detection using deep learning. In addition to his teaching responsibilities at undergraduate and postgraduate levels, he actively contributes as a peer reviewer for reputable journals such as BMJ Open and serves as a technical editor. His involvement in academic committees and university-level projects reflects his leadership and dedication to institutional development. While his practical projects are impactful, the inclusion of more peer-reviewed publications and measurable research outcomes would further enhance his profile. Overall, his commitment to innovation, education, and research makes him a suitable and competitive candidate for the Young Scientist Award.

Professional Profile

Education🎓

Soladoye Afeez Adekunle has a solid educational background in Computer Engineering, reflecting his dedication to academic excellence and continuous professional development. He is currently pursuing a Ph.D. in Computer Engineering at the Federal University Oye-Ekiti, Nigeria, with a research focus on advanced computing and intelligent systems. He previously earned a Master of Engineering (M.Eng) in Computer Engineering from the same university, graduating with distinction in 2023. His undergraduate studies were completed at Ladoke Akintola University of Technology, Ogbomosho, where he obtained a Bachelor of Technology (B.Tech) degree in Computer Engineering in 2016. His foundational education includes a Senior School Leaving Certificate from Foundation Model College, Ikirun, in 2009, and a Primary School Leaving Certificate from Al-hilal Nursery and Primary School, Ikirun, in 2003. His academic journey reflects a consistent commitment to learning, skill acquisition, and growth in the field of computer science and engineering, preparing him for a successful career in research and education.

Professional Experience📝

Soladoye Afeez Adekunle has amassed valuable professional experience across academia, research, and industry. He currently serves as a Lecturer II in the Department of Computer Engineering at the Federal University Oye-Ekiti, where he teaches both undergraduate and postgraduate courses, supervises student projects, and mentors young researchers. In addition to his teaching role, he is the Assistant Examination Officer and Level Advisor, playing a vital role in exam coordination and academic advising. He also contributes as a Technical Editor for the FUOYE Journal of Engineering and Technology and reviews scholarly articles for esteemed journals like BMJ Open and the Nigerian Journal of Technological Development. As a freelance Machine Learning Engineer, he has developed predictive systems for medical diagnosis and fake news detection, showcasing his ability to apply research in practical contexts. His previous roles include network engineering trainee and peer tutor, reflecting a versatile and well-rounded professional path in computer science and engineering.

Research Interest🔎

Soladoye Afeez Adekunle has earned recognition for his dedication to academic excellence, professional service, and contributions to the field of computer engineering. He graduated with distinction in his Master’s degree in Computer Engineering from the Federal University Oye-Ekiti, a testament to his academic strength and commitment to excellence. He has also been entrusted with key roles within the university, such as Assistant Examination Officer, Level Advisor, and member of several strategic committees, including the Artificial Intelligence Committee and departmental accreditation teams. These roles highlight the trust placed in him by his peers and institutional leadership. Additionally, his active involvement as a reviewer for respected international and national journals such as BMJ Open and the Nigerian Journal of Technological Development reflects recognition of his scholarly competence and critical thinking. Although formal awards are not explicitly listed, his growing responsibilities, editorial roles, and consistent academic performance collectively reflect a strong professional honor and recognition within his academic community.

Award and Honor🏆

Soladoye Afeez Adekunle has earned recognition for his dedication to academic excellence, professional service, and contributions to the field of computer engineering. He graduated with distinction in his Master’s degree in Computer Engineering from the Federal University Oye-Ekiti, a testament to his academic strength and commitment to excellence. He has also been entrusted with key roles within the university, such as Assistant Examination Officer, Level Advisor, and member of several strategic committees, including the Artificial Intelligence Committee and departmental accreditation teams. These roles highlight the trust placed in him by his peers and institutional leadership. Additionally, his active involvement as a reviewer for respected international and national journals such as BMJ Open and the Nigerian Journal of Technological Development reflects recognition of his scholarly competence and critical thinking. Although formal awards are not explicitly listed, his growing responsibilities, editorial roles, and consistent academic performance collectively reflect a strong professional honor and recognition within his academic community.

Research Skill🔬

Soladoye Afeez Adekunle possesses a diverse and practical set of research skills that align with cutting-edge developments in computer engineering and artificial intelligence. His expertise includes data analysis, machine learning model development, deep learning, and natural language processing. He has applied these skills in various impactful projects such as medical prediction systems for cancer and stroke, fake news detection, and object measurement using computer vision techniques. Adept at data preprocessing, model training, performance evaluation, and algorithm optimization, he ensures high-quality and accurate research outcomes. He is also skilled in using tools and frameworks such as Python, TensorFlow, Keras, and MATLAB for simulation and modeling. His experience in peer reviewing academic journals and formatting manuscripts further demonstrates his understanding of scientific writing and research ethics. Soladoye’s ability to merge academic research with practical application, along with his commitment to innovation, positions him as a capable and forward-thinking researcher in the technology domain.

Conclusion💡

Soladoye, Afeez Adekunle presents a strong case for the Young Scientist Award, especially in the areas of emerging technologies, machine learning, and applied computing. His academic excellence, teaching versatility, peer-review contributions, and practical ML project development demonstrate his passion and potential.

Publications Top Noted✍️

  • Title: IMPACT OF SOCIAL MEDIA ON POLICE BRUTALITY AWARENESS IN NIGERIA

    • Authors: OJOA, SOLADOYE Afeez A.

    • Year: 2020

    • Citations: 24

  • Title: Detection of Cervical Cancer Using Deep Transfer Learning

    • Authors: B.A. Omodunbi, A.A. Soladoye, A.O. Esan, N.S. Okomba, T.G.O.O.M. Ojelabi

    • Year: 2024

    • Citations: 4*

  • Title: Optimizing Stroke Prediction Using Gated Recurrent Unit and Feature Selection in Sub-Saharan Africa

    • Authors: A.A. Soladoye, D.B. Olawade, I.A. Adeyanju, O.M. Akpa, N. Aderinto, et al.

    • Year: 2025

    • Citations: 2

  • Title: E-learning: Significance on Federal Unity Schools Students’ in Nigeria Amidst COVID-19 Lockdown

    • Authors: A.A. Soladoye

    • Year: 2020

    • Citations: 2

  • Title: Development of a Medical Condition Prediction Model Using Natural Language Processing with K-Nearest Neighbour

    • Authors: B.A. Omodunbi, A.A. Soladoye, N.S. Okomba, M.O. Ayinla, C.S. Odeyemi

    • Year: [Year not specified]

    • Citations: 2*

  • Title: Smart Hospitality: Leveraging Technological Advances to Enhance Customer Satisfaction

    • Authors: O.O. Osadare, O.N. Akande, A.A. Soladoye, P.O. Sobowale

    • Year: 2024

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