Asadi Srinivasulu | Data Analysis | Innovative Research Award

Innovative Research Award

Asadi Srinivasulu — Optficial Labs
Asadi Srinivasulu
Affiliation Optficial Labs
Country India
Scopus ID 57191070975
Documents 71
Citations 464
h-index 11
Subject Area Data Analysis
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0002-5252-3669

The Innovative Research Award profile recognizes Asadi Srinivasulu of Optficial Labs, India, for documented scholarly activity associated with data analysis. The available bibliometric information reports 71 documents, 464 citations, and an h-index of 11 through the referenced Scopus author profile, providing a measurable basis for academic recognition and research assessment. [1]

Abstract

This article presents an academic recognition profile for Asadi Srinivasulu in connection with the Innovative Research Award. The profile summarizes available affiliation, bibliometric indicators, research subject classification, publication activity, and identifiers. The assessment is presented in a neutral scholarly format based on publicly referenced researcher-profile information. [2]

Keywords

Asadi Srinivasulu; Innovative Research Award; Data Analysis; Research Metrics; Bibliometrics; Scopus; ORCID; Research Publications; Citation Impact; International Research Data Analysis Excellence & Awards.

Introduction

Academic recognition commonly considers publication activity, citation performance, research visibility, and subject relevance. Asadi Srinivasulu’s available Scopus indicators provide a quantitative overview of documented scholarly output in data analysis. Such bibliometric measures support structured evaluation when interpreted alongside researcher identity and disciplinary context. [1]

Research Profile

Asadi Srinivasulu is affiliated with Optficial Labs in India and is associated with the subject area of Data Analysis. The available researcher profile identifies Scopus Author ID 57191070975 and an ORCID identifier, enabling persistent identification and access to scholarly records. [2]

Research Contributions

The documented research record indicates sustained scholarly engagement reflected through indexed publications and citation activity. Within the stated data analysis subject area, the available metrics provide evidence of research dissemination and subsequent scholarly referencing. Detailed contribution assessment should remain connected to the underlying indexed publication record. [3]

Publications

The available Scopus profile reports 71 documents associated with the researcher identifier. This publication count represents the indexed record available through the referenced author profile and offers a quantitative foundation for examining scholarly productivity, citation relationships, publication sources, and relevant article-level DOI records. [2]

Research Impact

The profile reports 464 citations and an h-index of 11, indicating that the indexed publication record has received measurable scholarly attention. These indicators provide a comparative perspective on citation performance, although bibliometric interpretation should consider publication year, discipline, database coverage, and methodological limitations. [3]

Award Suitability

Based on the supplied affiliation, research area, indexed publication count, citation record, and persistent researcher identifiers, the profile presents documented criteria relevant to academic recognition. The Innovative Research Award suitability may therefore be considered within a structured evaluation process emphasizing research activity, impact evidence, and disciplinary relevance. [1]

Conclusion

The available profile information presents a concise record of scholarly activity associated with Asadi Srinivasulu and Data Analysis. With 71 indexed documents, 464 citations, and an h-index of 11, the record provides measurable evidence for consideration within the International Research Data Analysis Excellence & Awards framework. [1]

References

  1. Diagnosis of Pneumonia from Chest X-Ray Images Using Federated Learning.
    https://link.springer.com/chapter/10.1007/978-981-96-1188-1_3
  2. Enhancing cybersecurity through script development using machine and deep learning for advanced threat mitigation.
    https://www.nature.com/articles/s41598-025-92676-4
  3. Obesity Risk Prediction Using Explainable Stacked Machine Learning with Lime Insights
    https://www.researchgate.net/publication/402127872_Obesity_Risk_Prediction_Using_Explainable_Stacked_Machine_Learning_with_Lime_Insights