Best Researcher Award
Michael Adekunle Adelere
University of New Brunswick, Canada
The Best Researcher Award recognizes research contributions, scholarly productivity, and potential impact within a defined academic field. This profile presents Michael Adekunle Adelere in connection with computer science and research addressing cybersecurity knowledge representation, threat modeling, and risk reasoning. The information combines the supplied bibliometric indicators with two identified RiskOnto research outputs. Publication details and metrics should be interpreted according to their source and verification date. [1]
Abstract
This article outlines a research profile associated with Michael Adekunle Adelere and the Best Researcher Award. The supplied profile records seven documents, 61 citations, and an h-index of 3. The identified RiskOnto works concern ontology-driven cybersecurity frameworks for organizing threat models, reasoning about risk, and integrating security knowledge. These themes connect knowledge engineering with practical cybersecurity analysis. The profile is descriptive rather than an independent audit of research performance. [2]
Keywords
Computer science; cybersecurity; ontology engineering; threat modeling; risk reasoning; NIST Cybersecurity Framework; knowledge integration; research impact; scholarly evaluation.
Introduction
Cybersecurity research increasingly requires structured methods for connecting threats, vulnerabilities, risks, and defensive controls. Ontologies can represent relationships among these concepts and support consistent interpretation across security tools and workflows. RiskOnto is presented in the supplied publication information as a framework addressing these challenges. The award context provides an opportunity to consider the relevance, scholarly documentation, and potential practical value of this research direction. [3]
Research Profile
The supplied information associates Adelere with the University of New Brunswick in Canada and identifies computer science as the principal subject area. The reported bibliometric indicators offer a limited quantitative snapshot: seven documents, 61 citations, and an h-index of 3. These figures may vary across scholarly databases and over time. The supplied identifier and profile URL should be checked against authoritative researcher records before formal publication.
Research Contributions
The RiskOnto research direction focuses on representing cybersecurity concepts in a structured form that can support threat modeling and risk analysis. Its stated objectives include connecting security knowledge and aligning risk reasoning with recognized cybersecurity practices. Potential applications include documenting threats, examining relationships among risks and controls, and improving consistency in security assessments. These are research objectives, not evidence that every proposed capability has been independently validated in operational settings. [4]
Publications
- “RiskOnto: An ontology-driven framework for threat modeling, risk reasoning and cyber defense knowledge integration.” Computers & Security, listed publication date February 2027. [4]
- “RiskOnto 1.0: An Ontology-Driven Framework for Threat Modeling and Risk Reasoning Using the NIST Cybersecurity Framework.” Preprint, 2026. [5]
Research Impact
The reported 61 citations suggest that the indexed work has received scholarly attention, while an h-index of 3 describes a particular distribution of cited publications. Neither measure alone establishes research quality, originality, reproducibility, or real-world adoption. A fuller assessment would examine publication venues, independent validation, subsequent research uptake, and contributions to cybersecurity practice.
Award Suitability
The profile provides material relevant to consideration for the Best Researcher Award under the Global Innovation Technologist Awards. Relevant assessment areas include:
- Research relevance to current cybersecurity challenges.
- Documented scholarly output and citation indicators.
- Potential contribution of ontology-based risk reasoning.
- Verification of authorship, publication status, and research outcomes.
These considerations support an evidence-based review but do not independently establish an award decision.
Conclusion
Michael Adekunle Adelere’s supplied research profile highlights computer science scholarship and RiskOnto-related work in cybersecurity knowledge integration. The bibliometric figures and publication records provide starting points for evaluating scholarly activity. Verification of the underlying records and assessment of research quality remain important for a balanced award review.
External Links
References
- ORCID. Michael Adekunle Adelere researcher identifier.
https://orcid.org/0000-0001-6389-7909
- National Institute of Standards and Technology. Cybersecurity Framework.
- “RiskOnto: An ontology-driven framework for threat modeling, risk reasoning and cyber defense knowledge integration.” Computers & Security.
https://doi.org/10.1016/j.cose.2026.105223.
- “RiskOnto 1.0: An Ontology-Driven Framework for Threat Modeling and Risk Reasoning Using the NIST Cybersecurity Framework.” Preprint, 2026.
https://doi.org/10.2139/ssrn.6465624.
- Google Scholar. Research profile supplied for Michael Adekunle Adelere.
https://scholar.google.com/citations?user=QTQZo5wAAAAJ&hl=en&oi=ao
- Global Innovation Technologist Awards. Official website.
innovationtechnologist.com