Akhlaqur Rahman | Computer Science | Innovative Research Award

Published on | Editorial Board by World Top Scientists

Innovative Research Award

Akhlaqur Rahman
UniSC University of the Sunshine Coast, Australia

Akhlaqur Rahman
Affiliation UniSC University of the Sunshine Coast
Country Australia
Scopus ID 56921224000
Documents 37
Citations 917
h-index 18
Subject Area Computer Science
Event World Top Scientist Awards
ORCID 0000-0002-5491-4436

Akhlaqur Rahman is a researcher affiliated with UniSC University of the Sunshine Coast in Australia, with a stated research focus in Computer Science. The research profile supplied for this article records 37 documents, 917 citations, and an h-index of 18 in Scopus, providing a bibliometric basis for describing the researcher’s scholarly output and citation impact. The profile is considered in the context of the Innovative Research Award associated with the World Top Scientist Awards event.[1]

Abstract

This article presents an academic recognition profile for Akhlaqur Rahman, affiliated with UniSC University of the Sunshine Coast, Australia, in the field of Computer Science. The profile is framed around the Innovative Research Award and the World Top Scientist Awards event. According to the supplied Scopus profile information, the researcher has 37 documented publications, 917 citations, and an h-index of 18. [1] These indicators provide a quantitative description of publication activity and citation-based scholarly visibility, while the researcher’s ORCID identifier provides an additional persistent mechanism for author identification. [2]

Keywords

Akhlaqur Rahman; Computer Science; academic research; research impact; bibliometrics; Scopus; Innovative Research Award; World Top Scientist Awards.

Introduction

Academic recognition commonly draws on a combination of qualitative evidence and quantitative indicators. In research-intensive disciplines such as Computer Science, bibliographic databases are frequently used to document publication records, citation activity, and author-level metrics. Scopus is one such database and assigns author identifiers intended to distinguish researchers and consolidate indexed scholarly records. Such indicators provide a structured basis for examining a researcher’s publication history, scholarly visibility, and contribution to the broader academic literature. [1]

Research Profile

Akhlaqur Rahman’s supplied academic profile places the researcher at UniSC University of the Sunshine Coast in Australia and identifies Computer Science as the principal subject area. The profile is associated with the Innovative Research Award under the World Top Scientist Awards event. The available information establishes a research identity and bibliometric record but does not, by itself, establish the complete thematic scope of the researcher’s work. The profile therefore provides a concise basis for understanding the researcher’s institutional affiliation, disciplinary orientation, and documented scholarly presence. [1]

Research Contributions

The supplied profile supports an assessment of research contribution primarily through documented scholarly output and citation activity. A record of 37 indexed documents indicates sustained participation in the scholarly publication process, while 917 citations indicate that the associated publications have received substantial referencing within the indexed literature. [1] These bibliometric indicators provide quantitative evidence that can be considered alongside the relevance, originality, and academic significance of the researcher’s individual publications.

Publications

The supplied Scopus profile records 37 documents associated with Akhlaqur Rahman’s research record. This publication record provides evidence of sustained scholarly activity within the field of Computer Science. The documents indexed in an international bibliographic database may include different forms of scholarly output, and the precise composition of the record should be verified directly through the relevant author profile. Publication activity is an important component of academic assessment because it provides a documented record of research dissemination. However, publication counts alone do not establish the quality or significance of individual studies. A balanced assessment may also consider the scholarly venues, research methodology, originality, collaboration, citation context, and relevance of the findings to the discipline.[2]

Research Impact

The supplied bibliometric record reports 917 citations and an h-index of 18 for the researcher. These figures provide quantitative measures of the visibility and citation activity associated with the indexed research output. In particular, the h-index is intended to combine publication productivity with citation frequency into a single indicator. The combination of documented publications, citations, and an h-index of 18 indicates a measurable scholarly footprint in the supplied Computer Science research profile. Further assessment of research impact would benefit from examining the context and significance of citations, the influence of individual publications, and any documented contributions to academic, technological, or professional practice.[2]

Award Suitability

The Innovative Research Award profile is associated with the World Top Scientist Awards event. Based on the information supplied for this article, the researcher’s documented publication activity, citation record, and h-index provide quantitative evidence that may be relevant when considering scholarly recognition. Accordingly, the available information supports presenting Akhlaqur Rahman’s research profile as one with documented academic activity and measurable citation impact. A definitive determination of award eligibility or selection remains dependent on the formal criteria, verification procedures, and evaluation process established by the awarding organization.[2]

Conclusion

Akhlaqur Rahman’s supplied academic profile presents a researcher affiliated with UniSC University of the Sunshine Coast in Australia and working within the broad field of Computer Science. The profile records 37 documents, 917 citations, and an h-index of 18 in Scopus, providing quantitative evidence of an established indexed scholarly record. In the context of the Innovative Research Award and the World Top Scientist Awards event, the available bibliometric indicators may serve as supporting evidence of research productivity and scholarly visibility. A complete academic evaluation should nevertheless incorporate qualitative assessment of research originality, methodological contribution, publication quality, disciplinary relevance, and broader research influence. [2]

References

  1. Elsevier. (n.d.). Scopus author details: Akhlaqur Rahman, Author ID 56921224000. Scopus.
    https://www.scopus.com/pages/authors/56921224000
  2. Rahman, A., Jha, R. K., & Gupta, A. K. (2019). Gabor phase response based scheme for accurate pectoral muscle boundary detection. https://doi.org/10.1049/iet-ipr.2018.5290
  3. Rahman, M. A., Jha, R. K., & Gupta, A. K. (2022). Multidirectional Gabor filter-based approach for pectoral muscle boundary detection. IEEE Transactions on Radiation and Plasma Medical Sciences. https://doi.org/10.1109/TRPMS.2021.3058157
  4. Afrin, M., Jin, J., Rahman, A., Rahman, A., Wan, J., & Hossain, E. (2021). Resource allocation and service provisioning in multi-agent cloud robotics: A comprehensive survey. IEEE Communications Surveys & Tutorials.https://doi.org/10.1109/COMST.2021.3061435
  5. Ahsan, M. M., Ahad, M. T., Soma, F. A., Paul, S., Chowdhury, A., Luna, S. A., Yazdan, M. M. S., Rahman, A., Siddique, Z., & Huebner, P. (2021). Detecting SARS-CoV-2 from chest X-ray using artificial intelligence. https://doi.org/10.1109/ACCESS.2021.3061621

Hatem Magdy Keshk | Computer Science | Best Researcher Award

Published on | Editorial Board by World Top Scientists

Assist. Prof. Dr. Hatem Magdy Keshk | Computer Science | Best Researcher Award

Postdoc at King Fahd University of Petroleum and Minerals | Saudi Arabia

Dr. Hatem Magdy Keshk is an accomplished researcher and academic with extensive expertise in artificial intelligence, deep learning, remote sensing, satellite image processing, GIS, UAV applications, and smart cities. He has served in diverse academic and research roles, including teaching, curriculum development, and departmental leadership, while also conducting impactful research across multiple disciplines. His career spans leading institutions in Egypt, Saudi Arabia, and Hong Kong, where he has undertaken postdoctoral research in interdisciplinary and space-related fields. Beyond academia, he has contributed to national and international initiatives such as land cover classification for Arab countries and served as a member of research councils, reflecting his commitment to advancing both science and societal applications. With over a decade of experience in teaching and research, he continues to blend innovation with academic rigor, positioning himself as a valuable contributor to the global research community and a strong candidate for recognition

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Hatem Magdy Keshk has pursued an extensive academic journey in computer science and related fields, equipping himself with strong theoretical knowledge and practical expertise. His educational background is highlighted by a Postdoctoral Fellowship at The Hong Kong Polytechnic University, where he conducted interdisciplinary research at the Smart Cities Research Institute. He later advanced his postdoctoral work at King Fahd University of Petroleum and Minerals, focusing on artificial intelligence, deep learning, and UAV applications under the Interdisciplinary Research Center for Aviation and Space Exploration. Throughout his academic development, he has engaged in both teaching and research simultaneously, ensuring that his educational growth was complemented by practical exposure. This balanced foundation has enabled him to develop expertise in machine learning, programming, image processing, and networking, while also gaining international research exposure that broadened his perspective on addressing global scientific challenges through interdisciplinary approaches.

Experience

Dr. Hatem Magdy Keshk has accumulated extensive professional experience spanning over a decade across teaching, research, and academic leadership. He began his career as a teaching assistant and coordinator in computer science, where he managed courses, laboratories, and departmental coordination. His academic career includes teaching positions at leading Egyptian institutions such as Future University, Obour Institute, and others, where he taught a wide range of subjects from artificial intelligence to operating systems and GIS. Beyond teaching, he has played a significant role in research, serving as a researcher at the National Authority for Remote Sensing and Space Sciences, where he worked on satellite image analysis, GIS applications, and deep learning integration. His experience also extends internationally, with postdoctoral research at The Hong Kong Polytechnic University and King Fahd University of Petroleum and Minerals. These roles highlight his ability to blend teaching, research, and applied science, contributing to both academia and national projects.

Research Focus

The research of Dr. Hatem Magdy Keshk lies at the intersection of artificial intelligence, deep learning, and remote sensing, with strong applications in smart cities, UAV systems, and space exploration. His work has concentrated on developing algorithms and systems for processing and analyzing satellite images, contributing to fields such as land cover classification and environmental monitoring. By combining AI with geospatial technologies, his research aims to create efficient solutions for large-scale data analysis and decision support systems. He has also contributed to the advancement of UAV applications, integrating machine learning techniques for enhanced automation and real-world usability. His interdisciplinary approach extends to smart city development, where his work supports sustainable urban planning and technology-driven innovation. With contributions spanning data science, computer vision, and applied AI, his research not only strengthens academic knowledge but also provides solutions with societal and industrial impact, positioning him as a versatile and impactful researcher.

Award and Honor

Dr. Hatem Magdy Keshk has earned recognition for his sustained contributions to research, teaching, and academic service. His selection for prestigious postdoctoral fellowships at The Hong Kong Polytechnic University and King Fahd University of Petroleum and Minerals reflects international acknowledgment of his expertise and research potential. His involvement in high-level councils, including the Space Research Council under Egypt’s Ministry of Research and Higher Education, further highlights his standing as a respected contributor to national scientific initiatives. Additionally, his participation in globally significant programs, such as the FAO Land Cover Classification System for Arab countries, underscores the trust placed in his capabilities to contribute to large-scale, impactful projects. These honors, alongside his leadership roles in academic departments and curriculum development, showcase not only his research excellence but also his dedication to advancing education and interdisciplinary collaboration. Collectively, these achievements underline his status as a researcher of high merit.

Publication Top Notes

  • Title: Satellite super-resolution images depending on deep learning methods: a comparative study
    Year: 2017
    Citations: 24

  • Title: Change detection in SAR images based on deep learning
    Year: 2020
    Citations: 22

  • Title: Performance evaluation of quality measurement for super-resolution satellite images
    Year: 2014
    Citations: 16

  • Title: Obtaining super-resolution satellites images based on enhancement deep convolutional neural network
    Authors: HM Keshk, XC Yin
    Year: 2021
    Citations: 11

  • Title: Semantic segmentation of some rock-forming mineral thin sections using deep learning algorithms: a case study from the Nikeiba area, South Eastern Desert, Egypt
    Year: 2024
    Citations: 8

  • Title: Classification of EgyptSat-1 images using deep learning methods
    Year: 2020
    Citations: 8

  • Title: Three-pass (DInSAR) ground change detection in Sukari gold mine, Eastern Desert, Egypt
    Year: 2022
    Citations: 4

  • Title: Geometric Correction of Aerial Camera and LiDAR Hybrid System Data Using GNSS/IMU
    Year: 2022
    Citations: 2

  • Title: Retracted article: Sentinel-2 cloud mask classification using deep learning method
    Year: 2022
    Citations: 2

Conclusion

Dr. Hatem Magdy Keshk has made significant contributions to the fields of artificial intelligence, deep learning, and remote sensing, with a strong focus on satellite image processing, change detection, and smart applications in geosciences and urban development. His publications demonstrate a blend of theoretical advancements and practical applications, contributing to international research visibility. With impactful works published in respected journals and conferences, his research has attracted citations that reflect the recognition of his contributions within the scientific community. Despite one retracted paper, the overall body of his work shows consistency, innovation, and interdisciplinary application. His role as both a researcher and collaborator highlights his ability to address complex scientific challenges and develop solutions of societal and technological value. These accomplishments position him as a strong candidate for honors such as the Best Researcher Award, with ongoing potential to expand his impact globally.

Yanming Zhao | Computer Science | Best Researcher Award

Published on | Editorial Board by World Top Scientists

Prof. Yanming Zhao | Computer Science | Best Researcher Award

Professor at Hebei MINZU Normal University, China

Yanming Zhao is a distinguished Professor at Hebei University of Nationalities, specializing in visual computing and deep neural networks. With a commitment to advancing technology and innovation, he has made significant contributions to the field of computer application technology, evidenced by his extensive research and numerous publications. 🌟

Profile 

Scopus Profile

Education🎓

Yanming graduated with a Master’s degree in Computer Application Technology from the School of Information at Shenyang University of Technology in 2010. His academic background laid a solid foundation for his future research endeavors and leadership in academia.

Experience🏛️💼

As a Master’s Supervisor and experienced researcher, Professor Zhao has participated in over nine provincial-level research projects and has consulted on over 500 industry projects. His work not only showcases his expertise but also his dedication to bridging the gap between academia and industry.

Research Interests🔬📈

Professor Zhao’s research primarily focuses on visual computing and deep neural networks. He has developed innovative algorithms, including the visual selectivity-based 3D graph convolutional algorithm (VS-3DGCN), aimed at enhancing point cloud segmentation performance and addressing key challenges in 3D graph convolutional algorithms.

Awards 🏆

Throughout his career, Yanming has received numerous accolades, including the title of Excellent Scientific and Technological Worker in Hebei Province and Outstanding Expert Managed by Chengde City. These awards reflect his significant contributions to the scientific community and his leadership in research.

Publications

Professor Zhao has published more than 30 academic papers in esteemed journals, such as:

  • Multi-channel depth segmentation network based on 3D graph convolution algorithm and its application in point cloud segmentation
    • Authors: Zhao, Y.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
    • Citations: 0
  • The Multi-View Deep Visual Adaptive Graph Convolution Network and Its Application in Point Cloud
    • Authors: Fan, H., Zhao, Y., Su, G., Zhao, T., Jin, S.
    • Journal: Traitement du Signal
    • Year: 2023
    • Citations: 4
  • Graph Convolution Algorithm Based on Visual Selectivity and Point Cloud Analysis Application
    • Authors: Zhao, Y., Su, G., Yang, H., Jin, S., Yang, J.
    • Journal: Traitement du Signal
    • Year: 2022
    • Citations: 2
  • Slow Feature Extraction Algorithm Based on Visual Selection Consistency Continuity and Its Application
    • Authors: Yang, H., Zhao, Y., Su, G., Fan, H., Shang, Y.
    • Journal: Traitement du Signal
    • Year: 2021
    • Citations: 0
  • Design and application of a slow feature algorithm coupling visual selectivity and multiple long short-term memory networks
    • Authors: Zhao, Y., Yang, H., Su, G.
    • Journal: Traitement du Signal
    • Year: 2021
    • Citations: 1

These contributions have garnered a total citation index of 102 times, illustrating the impact of his work on the research community. 📚🔗

Conclusion🌍✨

In summary, Professor Yanming Zhao stands out as a leading figure in the fields of visual computing and deep learning. His extensive research, numerous publications, and accolades make him a deserving candidate for the Best Researcher Award. His ongoing commitment to innovation and excellence continues to inspire colleagues and students alike.