Peter Obami | Artificial Intelligence | Best Researcher Award

Published on by Research Data Analysis

Best Researcher Award

Peter Obami
National Health Service, United Kingdom

Peter Obami
Affiliation National Health Service
Country United Kingdom
Documents 8
Citations 3
h-index 1
Subject Area Artificial Intelligence
Event International Research Data Analysis Excellence & Awards
ORCID 0009-0007-3738-0683

Peter Obami is affiliated with the National Health Service in the United Kingdom and is associated with research activity in Artificial Intelligence. The profile records eight documents, three citations, and an h-index of one. These bibliometric indicators provide a concise representation of the research information supplied for this recognition profile. [1]

Abstract

This academic recognition profile presents Peter Obami, affiliated with the National Health Service, United Kingdom, with Artificial Intelligence identified as the principal subject area. The supplied profile records eight documents, three citations, and an h-index of one. The article summarizes the documented research profile and its relevance to academic recognition. [2]

Keywords

Artificial Intelligence; Machine Learning; Data Analysis; Intelligent Systems; Research Profile; Artificial Intelligence Research; National Health Service; United Kingdom; Research Impact; Academic Recognition.

Introduction

Artificial Intelligence encompasses computational methods designed to perform tasks associated with perception, reasoning, learning, and decision-making. Contemporary AI research includes machine learning, neural networks, natural language processing, and intelligent systems. The field increasingly intersects with healthcare and data-intensive disciplines, creating opportunities for research-driven technological development and evidence-based applications. [3]

Research Profile

Peter Obami is identified in the supplied information as a researcher affiliated with the National Health Service in the United Kingdom, with Artificial Intelligence listed as the subject area. The profile contains eight documents, three citations, and an h-index of one. These indicators describe the documented publication and citation record provided for this article. [1]

Research Contributions

Research contributions in Artificial Intelligence may involve developing computational models, analyzing data, improving prediction, or applying intelligent methods to practical problems. For Peter Obami, the supplied subject classification places the profile within Artificial Intelligence. Specific contributions should be assessed through individual publications, methodologies, datasets, implementations, and documented research outputs rather than bibliometric indicators alone. [2]

Publications

The supplied profile records eight documents associated with the researcher. A complete publication assessment would consider article titles, journals or conferences, publication dates, research methods, co-authorship, and persistent identifiers such as DOIs. Because individual publication metadata were not supplied, this article does not attribute specific papers or findings beyond the documented publication count. [3]

Research Impact

Research impact can be considered through scholarly citations, adoption of methods, technological implementation, collaborations, and contributions to professional or public practice. The supplied record reports three citations and an h-index of one. These measures provide limited quantitative evidence and should be interpreted alongside publication quality, research context, and documented practical outcomes. [2]

Award Suitability

The profile is presented in connection with the International Research Data Analysis Excellence & Awards and identifies Artificial Intelligence as its subject area. Award suitability may be evaluated using documented research outputs, originality, methodological rigor, relevance, dissemination, and measurable impact. Final recognition should be determined according to the applicable award criteria and independently verifiable evidence. [1]

Conclusion

Peter Obami’s supplied academic profile identifies Artificial Intelligence as a research subject and records eight documents, three citations, and an h-index of one. The profile provides a concise basis for academic recognition while emphasizing the importance of evaluating detailed publications, research methods, and verifiable outcomes when assessing contributions to Artificial Intelligence. [2]

References

  1. Liquid Biopsy for Early Detection of Breast Cancer: Evidence and Public Health Implications from a Systematic Review.
    https://www.researchgate.net/publication/411920713
  2. Multiomic immune microenvironment signatures associated with response and resistance to immune checkpoint blockade across solid tumours
    https://link.springer.com/article/10.1007/s12672-026-05652-3
  3. Applications of Immunohistochemistry in Disease Diagnosis: Principles, Challenges, and Recent Advances
    https://www.researchgate.net/publication/407458875

Yi-Chao Wu | Artificial Intelligence | Innovative Research Award

Published on by Research Data Analysis

Innovative Research Award

Yi-Chao Wu
National Taipei University of Technology

Yi-Chao Wu
Affiliation National Taipei University of Technology
Country Taiwan
Scopus ID 55574208118
Documents 40
Citations 144
h-index 7
Subject Area Artificial Intelligence
Event Research Data Analysis Awards
ORCID 0009-0002-2386-6117

Yi-Chao Wu is affiliated with National Taipei University of Technology and has contributed to the advancement of Artificial Intelligence through scholarly publications and collaborative research. His academic portfolio reflects sustained engagement in intelligent systems, computational methodologies, and applied AI studies while demonstrating measurable research visibility through indexed publications and citations.[1]

Abstract

This article presents a concise overview of Yi-Chao Wu’s academic achievements in Artificial Intelligence, highlighting publication performance, scholarly influence, and research engagement. The profile summarizes recognized indicators commonly used to evaluate research excellence within international academic communities.[2]

Keywords

Artificial Intelligence, Intelligent Systems, Machine Learning, Computational Intelligence, Data Analytics, Research Innovation, Scholarly Publications, Scopus, Academic Recognition, Research Excellence.

Introduction

Artificial Intelligence continues to influence scientific discovery and technological advancement across multiple disciplines. Researchers such as Yi-Chao Wu contribute to this evolving landscape through peer-reviewed studies that support innovation and evidence-based academic development.[3]

Research Profile

With forty indexed publications, one hundred forty-four citations, and an h-index of seven, the research profile demonstrates consistent scholarly activity. These indicators suggest sustained participation in Artificial Intelligence research and collaboration within the academic community.[1]

Research Contributions

The research contributions emphasize intelligent computational approaches, algorithmic development, and practical applications of AI technologies. Such work supports ongoing progress in data-driven decision making and advanced computational research across interdisciplinary domains.[4]

Publications

The publication record includes articles indexed in internationally recognized databases, reflecting peer-reviewed scientific dissemination. Continued publication activity contributes to academic visibility while encouraging knowledge exchange and future collaborative opportunities.[1]

Research Impact

Citation performance and publication metrics indicate a measurable level of scholarly influence within the Artificial Intelligence research community. These indicators provide objective evidence supporting research quality, visibility, and continuing academic engagement.[5]

Award Suitability

The documented research achievements, publication record, and recognized scholarly metrics align with common evaluation criteria for research excellence awards. The profile represents a balanced combination of productivity, scientific contribution, and professional academic development.

Conclusion

Yi-Chao Wu’s academic profile reflects continuous engagement in Artificial Intelligence research supported by internationally indexed publications and citation-based evidence. The documented achievements demonstrate meaningful scholarly participation while providing a strong foundation for continued research recognition.[2]

References

    1. Elsevier. (n.d.). Scopus author details: Yi-Chao Wu, Author ID 55574208118. Scopus.
      https://www.scopus.com/pages/authors/55574208118
    2. ORCID. (n.d.). Research profile of Yi-Chao Wu.
      https://orcid.org/0009-0002-2386-6117
    3. Wu, Y.-C., Xu, Z.-Q., & Lee, Y.-L. (2026). Dual-camera blind spot detection system by using pruned lightweight neural networks and data augmentation. Engineering Applications of Artificial Intelligence. Advance online publication
    4. Wu, Y.-C., Chen, Z.-S., & Lu, W.-J. (2026). Enhanced real-time traffic sign recognition via lightweight neural networks and wavelet transform. IET Intelligent Transport Systems. Advance online publication.
      https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/itr2.70286
    5. Wu, Y.-C., Lin, Z.-Y., Ciou, Y.-R., & Xu, J.-X. (2026, January 21). Traffic signal image recognition with lightweight machine learning model. In Proceedings of the ACM Conference (Conference paper).
      https://doi.org/10.1145/3796315.3796360