Innovative Research Award
Gelareh Vakili
University of Maryland, Baltimore County
Gelareh Vakili is a researcher affiliated with the University of Maryland, Baltimore County in the United States, with a stated subject area of Data Science and Analytics. The researcher is associated with Scopus Author ID 60765665400 and an ORCID identifier that provides a persistent digital identifier for scholarly activities. The supplied researcher record lists one document; citation and h-index values were not provided in the source information for this article.[2]
Abstract
Innovative Research Award profiles the academic and research record of Gelareh Vakili, affiliated with the University of Maryland, Baltimore County, United States. The supplied information associates the researcher with Data Science and Analytics and identifies a Scopus Author ID and ORCID record. Scopus is a major bibliographic and citation database used to index scholarly literature and provide author-level publication information. ORCID provides persistent identifiers intended to distinguish researchers and connect them with their scholarly contributions. On the basis of the supplied record, the profile documents one indexed publication and provides a foundation for describing the researcher’s academic activity without making unsupported claims about citation impact or research excellence.[1]
Keywords
Data Science and Analytics; Data Science; Analytics; Research Innovation; Academic Research; Scholarly Communication; Bibliometrics; Researcher Profile; University of Maryland, Baltimore County; International Innovator Awards; ORCID; Scopus.
Introduction
Data science and analytics encompass methodological approaches for collecting, processing, interpreting, and communicating information derived from data. Contemporary research in these areas commonly integrates statistical reasoning, computational methods, data management, and analytical techniques to address questions across scientific and applied domains. A researcher’s scholarly profile can therefore be considered through several complementary dimensions, including documented publications, subject-area classification, persistent identifiers, institutional affiliation, and measurable bibliographic indicators. [1]
Research Profile
The supplied academic profile places Gelareh Vakili at the University of Maryland, Baltimore County and identifies Data Science and Analytics as the principal subject area. The available bibliographic information lists one document in the supplied Scopus record. Because no citation count or h-index value was supplied, those indicators are intentionally reported as unavailable rather than estimated. This distinction is important because bibliometric measures can vary according to database coverage, publication type, indexing status, and the date on which the record is examined. [1]
Research Contributions
The available information supports describing Gelareh Vakili’s research profile in relation to Data Science and Analytics. However, a detailed assessment of specific methodological contributions requires access to the researcher’s publications, abstracts, datasets, software, or other scholarly outputs. Accordingly, the contribution profile below is limited to areas that can be reasonably connected with the supplied subject classification and bibliographic record. [2]
Publications
The supplied record specifies 1 document associated with the Scopus profile. No publication title, journal, year, authorship details, pages, or DOI were included in the input data. Consequently, no publication-specific bibliographic information or DOI has been inferred for this article. [3]
Research Impact
Research impact may be evaluated using multiple forms of evidence, including citations, scholarly dissemination, adoption of research outputs, collaboration, policy or industry use, and contributions to subsequent research. Bibliometric indicators such as citation counts and h-index values can provide useful quantitative signals, but they should be interpreted in relation to disciplinary norms and the coverage of the database being used. [1]
Award Suitability
The International Innovator Awards provides the stated recognition context for this profile. Based on the supplied information, Gelareh Vakili has a documented affiliation with the University of Maryland, Baltimore County, a research classification in Data Science and Analytics, an indexed Scopus record, and persistent scholarly identifiers. These elements provide verifiable components for an academic recognition profile. [1]
Conclusion
Gelareh Vakili is presented in the supplied academic record as a researcher affiliated with the University of Maryland, Baltimore County and associated with Data Science and Analytics. The available information includes a Scopus Author ID, an ORCID identifier, and one reported Scopus document. These identifiers and bibliographic details provide a basis for documenting the researcher’s scholarly profile.[2]
External Links
References
- Elsevier. (2026). Scopus author details: Gelareh Vakili, Author ID 60765665400. Scopus.https://www.scopus.com/authid/detail.uri?authorId=60765665400
- ORCID. (2026). ORCID record: Gelareh Vakili, ORCID iD 0000-0003-3384-3840. ORCID.https://orcid.org/0000-0003-3384-3840
- International Innovator Awards. (2026). Official website of the International Innovator Awards.https://innovatorawards.org/