Hussein Ali Ahmed Ghanim | Artificial Intelligence | Innovative Research Award

Published on by New Scientists

Innovative Research Award

        Hussein Ali Ahmed                        Ghanim
Author Hussein Ali Ahmed Ghanim
Affiliation University of Kassala
Country Sudan
ORCID ID 0009-0008-0639-967X
Subject Area Artificial Intelligence
Event New Scientists Awards

Hussein Ali Ahmed Ghanim

University of Kassala, Sudan

Hussein Ali Ahmed Ghanim is an academic researcher affiliated with the University of Kassala in Sudan, with a stated research area in Artificial Intelligence. His academic profile is associated with contemporary developments in computational methods, intelligent systems, machine learning, and data-driven technologies. The researcher is also identified through an ORCID record, providing a persistent identifier for distinguishing scholarly work and research activities.[1]

Abstract

This academic recognition profile presents Hussein Ali Ahmed Ghanim, a researcher affiliated with the University of Kassala, Sudan, whose stated subject area is Artificial Intelligence. The profile summarizes the available academic information concerning his institutional affiliation, research specialization, researcher identification, and potential relevance to an Innovative Research Award. ORCID provides a persistent digital identifier intended to distinguish researchers and connect them with their scholarly contributions.[1]

Keywords

Artificial Intelligence, Machine Learning, Intelligent Systems, Computational Research, University of Kassala, Sudan, Research Innovation, Scholarly Communication, Innovative Research Award, New Scientists Awards.

Introduction

Artificial Intelligence is a multidisciplinary field concerned with computational systems capable of performing tasks that ordinarily require aspects of human intelligence, including learning, reasoning, perception, classification, and decision-making. Current research encompasses machine learning, deep learning, natural language processing, computer vision, intelligent agents, optimization, and data-driven modelling. Scholarly research in these areas contributes to the development and evaluation of computational techniques across scientific and applied domains.[2]

Within this broader research environment, Hussein Ali Ahmed Ghanim is associated with the University of Kassala and identifies Artificial Intelligence as his subject area. His ORCID identifier provides a persistent mechanism for linking his scholarly identity with research outputs and professional activities.[1]

Research Profile

The available profile information identifies Hussein Ali Ahmed Ghanim as a researcher at the University of Kassala in Sudan. His stated academic specialization is Artificial Intelligence, placing his research within a rapidly developing area of computer science and interdisciplinary computational research.

  • Researcher: Hussein Ali Ahmed Ghanim
  • Institution: University of Kassala
  • Country: Sudan
  • Subject Area: Artificial Intelligence
  • ORCID: 0009-0008-0639-967X

ORCID is widely used within scholarly communication to provide persistent identifiers for researchers and improve the attribution and discoverability of research contributions. The ORCID record associated with Hussein Ali Ahmed Ghanim can therefore serve as a reference point for distinguishing the researcher from individuals with similar names.[1]

Research Contributions

Research in Artificial Intelligence can involve the design, implementation, testing, and evaluation of computational systems that learn from data or perform tasks associated with intelligent behavior. Depending on the specific research problem, contributions may involve algorithms, predictive models, optimization procedures, knowledge representation, automated decision-making, or applications of intelligent technologies.

Because detailed publication-level information was not supplied for this profile, specific research findings or individual technical contributions are not attributed here without supporting bibliographic evidence. This approach distinguishes the documented subject specialization from claims about particular research outcomes.

Publications

Publication records are an important component of academic evaluation because they provide evidence of research dissemination through scholarly communication channels. For Hussein Ali Ahmed Ghanim, publication information should be verified through authoritative academic indexing services or the researcher’s maintained scholarly profiles before individual papers, citation counts, journal details, or DOI metadata are attributed to the researcher.

  • ORCID provides a persistent researcher identifier for scholarly attribution.[1]
  • Scopus can be used to verify indexed author and publication records where an author profile is available.[3]
  • Google Scholar can provide an additional discovery route for scholarly publications and citations when a verified author profile is available.[4]

Research Impact

Academic research impact may be considered through several complementary indicators, including the quality and relevance of publications, citation activity, research collaborations, adoption of findings, and contribution to the advancement of a field. Bibliometric databases can assist with measuring aspects of scholarly visibility, although citation indicators should be interpreted in relation to disciplinary context and the underlying publication record.[3]

For a researcher working in Artificial Intelligence, research impact may also arise through the development or evaluation of computational methods, datasets, software, models, or applications. A complete assessment should therefore consider qualitative research contributions alongside quantitative bibliometric indicators.

Award Suitability

The Innovative Research Award is presented within the context of the New Scientists Awards. Hussein Ali Ahmed Ghanim’s stated specialization in Artificial Intelligence provides a relevant disciplinary basis for consideration within an innovation-focused research recognition program. The assessment of award suitability should ultimately be based on the applicable nomination criteria, documented research outputs, originality, scholarly contribution, and evidence supplied during the formal evaluation process.[5]

Artificial Intelligence is an active research field in which methodological innovation and interdisciplinary applications are important areas of scholarly development. Recognition within such a field may appropriately consider the originality and significance of a candidate’s documented research rather than relying solely on bibliometric measures.

Conclusion

Hussein Ali Ahmed Ghanim is affiliated with the University of Kassala in Sudan and has identified Artificial Intelligence as his research subject area. His academic identity is supported by an ORCID identifier, which provides a persistent mechanism for scholarly identification and attribution.[1]

The profile provides an academic basis for consideration for the Innovative Research Award while avoiding unsupported claims concerning specific publications or research outcomes. Further evaluation can incorporate verified publication records, research findings, scholarly impact, and the formal criteria established by the New Scientists Awards program.

References

  1. ORCID. (n.d.). ORCID record: Hussein Ali Ahmed Ghanim. ORCID.
    https://orcid.org/0009-0008-0639-967X
  2. Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.
    https://aima.cs.berkeley.edu/
  3. Elsevier. (n.d.). Scopus Author Search and Abstract & Citation Database. Scopus.
    https://www.scopus.com/
  4. Google. (n.d.). Google Scholar. Google Scholar.
    https://scholar.google.com/
  5. New Scientists Awards. (n.d.). New Scientists Awards — Official Award Website.
    https://newscientists.net/

Ibrahim Aromoye | Artificial Intelligence and Machine Learning | Editorial Board Member

Published on by New Scientists

Mr. Ibrahim Aromoye | Artificial Intelligence and Machine Learning | Editorial Board Member

Graduate Research Assistant | Universiti Teknologi PETRONAS | Malaysia

Mr. Ibrahim Aromoy is a promising researcher in Electrical and Electronic Engineering with a growing scholarly footprint in hybrid UAV systems, artificial intelligence, and intelligent surveillance technologies. His research is centered on the development of a Pipeline Inspection Air Buoyancy Hybrid Drone, a novel UAV concept that combines lighter-than-air and heavier-than-air technologies to improve flight endurance, stability, and inspection efficiency. By integrating deep learning–based object detection architectures into UAV platforms, his work advances real-time pipeline monitoring, anomaly identification, and autonomous decision-making for industrial applications. His contributions span AI-driven automation, robotics, swarm intelligence, energy-efficient IoT systems, and 5G-enabled surveillance technologies. He has authored several research papers in reputable international journals and conferences, including publications in IEEE Access, Neurocomputing, and Elsevier venues. These works address UAV reconnaissance, transformer-based detection models for pipeline integrity assessment, and optimization frameworks inspired by swarm behavior. His research output reflects measurable scholarly influence, with 15 Scopus citations, 7 indexed documents, and an h-index of 2. Mr. Ibrahim Aromoy has participated in multiple research and development projects, contributing to UAV design, embedded hardware integration, machine learning pipelines, and cyber-secure control systems. His work in hybrid drone architecture and automated surveillance has been supported by competitive institutional funding, reinforcing the technological relevance and innovation potential of his research. His scientific contributions extend beyond publications to academic service. He serves as a peer reviewer for high-impact journals such as IEEE Access and Results in Engineering, supporting the advancement of rigorous research dissemination in engineering and applied sciences. His expertise also includes AI vision systems, OpenCV-based automation, and embedded cybersecurity applications for unmanned systems, further strengthening his interdisciplinary research profile. Mr. Ibrahim Aromoy has been recognized with research-focused scholarships and academic distinctions that support his ongoing work in UAV innovation and intelligent automation. Through his integrated expertise in UAV engineering, deep learning, and intelligent inspection systems, he continues to contribute meaningfully to the evolution of smart surveillance, autonomous robotics, and AI-augmented engineering technologies.

Profiles: Scopus | ORCID | Google Scholar | ResearchGate | Web of Science

Featured Publications

1. Aromoye, I., Lo, H., Sebastian, P., Ghulam, E., & Ayinla, S. (2025). Significant advancements in UAV technology for reliable oil and gas pipeline monitoring. Computer Modeling in Engineering & Sciences, 142(2), 1155.

2. Aromoye, I. A., Hiung, L. H., & Sebastian, P. (2025). P-DETR: A transformer-based algorithm for pipeline structure detection. Results in Engineering, 26, 104652.

3. Zahid, F., Ali, S. S. A., & Aromoye, I. A. (2025). Exploring the potential benefits and overcoming the constraints of virtual and augmented reality in operator training. Transportation Research Procedia, 84, 625–632.

4. Mansoor, Y., Zahid, F., Azhar, S. S., Rajput, S., & Aromoye, I. A. (2025). Energy-efficient solar water pumping: The role of PLCs and DC-DC boost converters in addressing water scarcity. Transportation Research Procedia, 84, 681–688.

5. Zahid, F., Rajput, S., Ali, S. S. A., & Aromoye, I. A. (2025). Challenges and innovations in 3D object recognition: The integration of LiDAR and camera sensors for autonomous applications. Transportation Research Procedia, 84, 618–624.