Best Researcher Award
Nazim Manić
State University of Novi Pazar, Serbia
Nazim Manić is identified in the supplied researcher profile as being affiliated with the State University of Novi Pazar in Serbia. This article presents the information in the context of the Best Researcher Award associated with New Scientists Awards; it does not independently establish an award selection or result. [1] [2] [3]
Abstract
This article provides an academic recognition profile for Nazim Manić, identified in the supplied information as affiliated with the State University of Novi Pazar, Serbia These values summarize selected dimensions of indexed scholarly output and citation activity but do not independently establish research quality, originality, or broader impact. Google Scholar, Scopus, and ORCID are provided as routes for checking researcher identity and available bibliographic records. Since individual publication titles, study findings, and DOI records were not included in the input data, this article avoids attributing specific technical contributions without verification. The profile is presented in connection with the Best Researcher Award category and New Scientists Awards. [1] [2] [3]
Keywords
Nazim Manić; State University of Novi Pazar; Serbia; Artificial Intelligence; Machine Learning; Google Scholar; Scopus; ORCID; bibliometrics; citation analysis; h-index; Best Researcher Award; New Scientists Awards.
Introduction
Researcher profiles and scholarly indexing services help readers identify authors, locate publications, and examine citation relationships. Google Scholar provides a searchable index of scholarly literature and author profiles, while Scopus supplies curated bibliographic and citation information for indexed publications. ORCID provides persistent digital identifiers that help distinguish researchers and connect them with their scholarly activities. Each system has its own coverage and record-management practices, so information may differ between databases. [1] [2] [3]
This article documents the researcher details and bibliometric values supplied for Nazim Manić. It uses a neutral, Wikipedia-inspired structure to distinguish reported profile information from research-specific claims that would require examination of verified publications. The stated association with Artificial Intelligence and Machine Learning provides the subject classification for this profile, rather than a verified inventory of individual research specializations.
Research Profile
Nazim Manić is associated in the supplied data with the State University of Novi Pazar in Serbia. The stated subject area is Artificial Intelligence and Machine Learning, fields encompassing computational methods that support prediction, classification, optimization, data analysis, and automated decision-making.
These identifiers can be used to locate relevant records, although the publication lists and author metadata should be checked to ensure that they correspond to the same individual. [1] [2] [3]
These values should be treated as a snapshot of the supplied profile information rather than guaranteed current metrics. Citation counts and h-index values can change as new publications are indexed, citation links are updated, and author profiles are corrected. The underlying database should be consulted for the latest figures.
Research Contributions
The supplied information associates the researcher with Artificial Intelligence and Machine Learning but does not identify individual papers, technical methods, software systems, datasets, patents, or specific scientific findings. Consequently, no particular algorithm, application, or research breakthrough is attributed to Nazim Manić in this article without supporting bibliographic evidence.
A publication-based account of research contributions could document the following elements after the relevant records have been verified:
- Research problems and objectives addressed in the researcher’s verified publications.
- Machine-learning algorithms, artificial-intelligence methods, computational frameworks, or analytical techniques explicitly described in published work.[4] [5]
Publications
The supplied Google Scholar profile information reports four documents. Individual publication titles, co-authors, journal names, publication years, and DOI identifiers were not supplied for this article. A specific bibliography is therefore not reproduced here, as doing so without verification could introduce incorrect titles or attribute publications to the wrong author.
The Google Scholar and Scopus author profiles are appropriate starting points for identifying potentially relevant records. Each publication should be checked against the publisher’s page or its DOI record before being included in a formal academic bibliography. Crossref provides a searchable metadata service that can help locate DOI-linked publication information. [1] [2] [5]
Research Impact
The reported citation count of 42 indicates that publications associated with the supplied profile have received citations within the relevant indexing context. An h-index of 3 conventionally indicates that at least three publications have each received at least three citations in the database or profile from which the value was calculated. The reported figures should be interpreted in relation to the source, coverage, and date of retrieval. [1] [4]
Citation measures are useful for describing aspects of scholarly visibility, but they do not directly measure methodological rigor, originality, reproducibility, or practical benefit. Citation patterns can vary substantially by discipline, publication type, research collaboration, and career stage.
Award Suitability
The Best Researcher Award is the recognition category specified for this academic profile in connection with New Scientists Awards. The supplied researcher identifiers and bibliometric values provide a starting point for documenting scholarly output and locating records for further review.
An appropriate award assessment would require review of verified research outputs, originality, technical rigor, documented contributions, research integrity, and alignment with the award’s published criteria. Citation counts and h-index values alone are not sufficient to establish award eligibility or merit.. [4]
Conclusion
Nazim Manić is identified in the supplied information as being affiliated with the State University of Novi Pazar in Serbia, with Artificial Intelligence and Machine Learning given as the subject area. Google Scholar, Scopus, and ORCID identifiers provide useful routes for examining author identity and scholarly records. A more comprehensive account of research contributions and impact would require verification of individual publications and their findings..
External Links
References
- Google. (n.d.). Google Scholar profile: Nazim Manić, user ID s-N_FiAAAAAJ.
https://scholar.google.com/citations?user=s-N_FiAAAAAJ&hl=en&oi=ao
- Elsevier. (n.d.). Scopus author details: Nazim Manić, Author ID 57192164885.
https://www.scopus.com/authid/detail.uri?authorId=57192164885
- ORCID. (n.d.). Nazim Manić researcher identifier: 0000-0001-8346-8255.
https://orcid.org/0000-0001-8346-8255
- Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences,
https://doi.org/10.1073/pnas.0507655102
- Crossref. (n.d.). Crossref metadata search. Crossref provides a searchable service for bibliographic metadata, including DOI-associated publication records. It is included as a verification resource;
https://search.crossref.org/