Otilia Elena Dragomir | Artificial Intelligence | Innovative Research Award

Published on by Global Network Awards

Innovative Research Award

Otilia Elena Dragomir,
Valahia University of Targoviste, Romania.

Otilia Elena Dragomir
Affiliation Valahia University of Targoviste
Country Romania
Scopus ID 26537327000
Documents 53
Citations 372 (308 documents)
h-index 9
Subject Area Artificial Intelligence
Event Global Network Awards
ORCID 0000-0001-7583-725X

The Innovative Research Award recognizes distinguished contributions to scientific advancement, highlighting impactful research achievements across emerging and established disciplines. Otilia Elena Dragomir, affiliated with Valahia University of Targoviste, Romania, has been acknowledged for her contributions to the field of Artificial Intelligence, demonstrating consistent scholarly output and measurable research impact within indexed academic databases [1].

Abstract

This article outlines the academic profile and research contributions of Otilia Elena Dragomir in the domain of Artificial Intelligence. It contextualizes her scholarly work within contemporary computational research frameworks and highlights measurable academic outputs including publications, citation metrics, and indexing in Scopus. The evaluation is aligned with standard research assessment indicators used in global academic recognition systems [2].

Keywords

Artificial Intelligence, Machine Learning, Data Modeling, Computational Intelligence, Academic Research, Scientometrics

Introduction

Artificial Intelligence (AI) has emerged as a transformative discipline influencing diverse sectors including healthcare, engineering, and information systems. Researchers contributing to AI development are evaluated based on publication quality, citation metrics, and interdisciplinary relevance. Otilia Elena Dragomir’s academic work reflects engagement with evolving AI methodologies and applications [3].

Research Profile

Otilia Elena Dragomir is affiliated with Valahia University of Targoviste, Romania. Her Scopus-indexed research profile includes 53 documents with a cumulative citation count of 372 and an h-index of 9, indicating sustained scholarly engagement and moderate citation impact within the academic community [1].

Research Contributions

The research contributions of Dragomir primarily focus on Artificial Intelligence and computational modeling. Her work explores algorithmic efficiency, predictive analytics, and data-driven methodologies, contributing to advancements in intelligent systems design and evaluation. These contributions align with ongoing global research trends in AI innovation and applied computational science [4].

Publications

The author has contributed to multiple peer-reviewed journals indexed in Scopus, reflecting interdisciplinary engagement across Artificial Intelligence and related computational domains. These publications demonstrate methodological rigor and adherence to international research standards [5].

Research Impact

Research impact is assessed through bibliometric indicators such as citation counts, h-index, and publication volume. Dragomir’s citation profile indicates that her research has been referenced in over 300 documents, reflecting engagement and recognition within the academic community. Such metrics are widely used in evaluating research influence and academic visibility [2].

Award Suitability

The Innovative Research Award under the Global Network Awards framework recognizes measurable research excellence and global academic contribution. Based on publication metrics, subject relevance, and citation performance, Otilia Elena Dragomir meets the evaluation criteria for recognition within the Artificial Intelligence domain .

Conclusion

Otilia Elena Dragomir’s academic contributions reflect a consistent engagement with Artificial Intelligence research, supported by measurable bibliometric indicators and peer-reviewed publications. Her recognition through the Innovative Research Award underscores the importance of data-driven evaluation in modern academic ecosystems and highlights her role within the global research community.

References

  1. Elsevier. (n.d.). Scopus author details: Otilia Elena Dragomir, Author ID 26537327000. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=26537327000
  2. 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
  3. Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach. Pearson.
    https://aima.cs.berkeley.edu/
  4. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
    https://www.deeplearningbook.org/
  5. Elsevier. (n.d.). Guide for authors: Publishing ethics and standards.
    https://www.elsevier.com/authors/policies-and-guidelines

Xinran Li | Artificial Intelligence | Editorial Board Member

Published on by Global Network Awards

Dr. Xinran Li | Artificial Intelligence  | Editorial Board Member

Dr. Xinran Li | University of Shanghai for Science and Technology | China

Dr. Xinran Li is an active researcher specializing in multimedia information security, perceptual image hashing, information hiding, and artificial intelligence security. She has established a strong publication record with more than twenty peer-reviewed papers, including fifteen SCI-indexed works and multiple IEEE Transactions publications. Her contributions span robust perceptual hashing, encrypted-domain image hashing, steganography analysis, secure multimedia processing, and feature-fusion methods for image authentication. She has participated in several funded research projects and maintains interdisciplinary collaborations reflected through co-authored journal and conference papers. Her work has earned over forty citations, demonstrating growing global impact. She serves as a reviewer for high-quality venues and is a member of prominent professional societies, contributing to ongoing advancements in secure multimedia computing.

Profile: Orcid 

Featured Publications: 

Xinran Li, & Zichi Wang. (2024). Vaccine for digital images against steganography. Scientific Reports, 14(1), 21340.

Xinran Li, Zichi Wang, Guorui Feng, Xinpeng Zhang, & Chuan Qin. (2024). Perceptual image hashing using orthogonal moments feature fusion. IEEE Transactions on Multimedia, 26, 10041–10054.

Xinran Li, Chuan Qin, Zichi Wang, Zhenxing Qian, & Xinpeng Zhang. (2022). Unified performance evaluation method for perceptual image hashing. IEEE Transactions on Information Forensics and Security, 17, 1404–1419.

Xinran Li, Mengqi Guo, Zichi Wang, & Chuan Qin. (2024). Robust image hashing in encrypted domain. IEEE Transactions on Emerging Topics in Computational Intelligence, 8(1), 670–683.

Zichi Wang, Xinpeng Zhang, & Xinran Li. (2025). Untraceable steganography: Towards the anonymity of steganographer. IEEE Signal Processing Letters, 32, 956–960.