Melisa Gozet | Artificial Intelligence | Innovative Research Award

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Innovative Research Award

Melisa Gozet — Ostim Technical University, Turkey

Melisa Gozet
Affiliation Ostim Technical University
Country Turkey
Scopus ID 59723815900
Documents 3
Citations 5
h-index 1
Subject Area Artificial Intelligence
Event The Scientist Global Awards
ORCID 0000-0003-0706-5555
Google Scholar oDczXfUAAAAJ&hl

Melisa Gozet is a researcher affiliated with Ostim Technical University in Turkey whose stated subject area is artificial intelligence. Her research profile can be explored through her public scholarly identifiers and indexed publication records, including Scopus, ORCID, and Google Scholar. The Innovative Research Award article presents her research background and academic indicators in the context of The Scientist Global Awards. The available profile information provides a starting point for examining her scholarly output, citation activity, and potential relevance to innovation-oriented research recognition. [1] [2] [3]

Abstract

This article presents an academic profile of Melisa Gozet, affiliated with Ostim Technical University, Turkey, with artificial intelligence identified as her subject area. The supplied bibliometric information lists three documents, five citations, and an h-index of one. These indicators offer a limited quantitative snapshot of indexed research activity and should be interpreted in conjunction with publication content, research quality, methodological contribution, and relevance to the wider scientific community. The article also outlines considerations for evaluating research innovation in relation to The Scientist Global Awards. [1] [2]

Keywords

Melisa Gozet; artificial intelligence; innovative research; scholarly publications; research impact; bibliometrics; scientific innovation; Ostim Technical University; The Scientist Global Awards; academic recognition.

Introduction

Melisa Gozet’s supplied academic profile identifies Ostim Technical University in Turkey as her institutional affiliation and artificial intelligence as her subject area. Her Scopus Author ID, ORCID identifier, and Google Scholar profile provide routes for reviewing the publications associated with her scholarly record. Such identifiers are useful for distinguishing authors and locating research outputs, although profile completeness and indexing coverage can vary across databases. [1] [2] [3]

Research Profile

The available profile information associates Melisa Gozet with Ostim Technical University and identifies artificial intelligence as her research subject area. A detailed account of her particular specializations, research methods, project affiliations, and individual findings requires verification against her indexed publications and institutional records. The public scholarly identifiers listed in this article can support that review.  [4]

Research Contributions

The supplied information establishes artificial intelligence as the subject area associated with Melisa Gozet’s profile but does not provide publication titles, abstracts, datasets, project descriptions, or specific technical findings. Consequently, individual contributions cannot be described accurately without examining the underlying publications. A publication-level assessment should identify the problem addressed, the methods developed or applied, the evidence supporting the findings, and the relationship between the results and prior research. [4]

Publications

The supplied Scopus profile reports three documents associated with Melisa Gözet. The individual publication titles, author lists, publication dates, journal or conference details, and DOI identifiers have not been provided in the input data. They should therefore be retrieved and checked against the original records before a publication bibliography is added. [1]

Research Impact

The supplied profile reports five citations and an h-index of one. These values offer a limited bibliometric snapshot but do not independently establish the influence or quality of individual publications. Citation counts may change over time and vary between databases because of differences in indexing, document coverage, author attribution, and update schedules. [1] [4]

Award Suitability

The Innovative Research Award, as presented in this profile, provides a context for considering research originality, methodological development, and the potential value of scientific work. The Scientist Global Awards is the event named in the supplied information. The award website provides the relevant organizational reference for readers seeking official information about award categories and participation. [6]

Conclusion

Melisa Gozet’s supplied academic profile identifies an affiliation with Ostim Technical University in Turkey and a subject area of artificial intelligence. The reported record includes three documents, five citations, and an h-index of one, alongside Scopus, ORCID, and Google Scholar identifiers. These details provide a starting point for reviewing her scholarly work and documenting research activity in the context of the Innovative Research Award and The Scientist Global Awards. [1]

References

  1. Elsevier. (2026). Scopus author details: Melisa Gozet, Author ID 59723815900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59723815900
  2. ORCID. (2026). ORCID record: 0000-0003-0706-5555.
    https://orcid.org/0000-0003-0706-5555
  3. Google Scholar. (2026). Melisa Gozet — Google Scholar profile.
    https://scholar.google.com/citations?user=oDczXfUAAAAJ&hl=tr&oi=ao
  4. An Analysis Approach for Crowds with Varying Density and Complexity Using Image Data
    https://doi.org/10.1109/it64745.2025.10930264
  5. YOLOv11-Based Explainable Framework for Anomaly Detection in Crowded Scenes Using Attention Fusion.
    https://doi.org/10.1109/acit65614.2025.11185718
  6. The Scientist Global Awards. (2026). Official award website.
    https://thescientists.net/

Nur Intan Raihana Ruhaiyem | Machine Learning | Best Researcher Award

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Dr. Nur Intan Raihana Ruhaiyem | Machine Learning | Best Researcher Award

Senior Lecturer | Universiti Sains Malaysia | Malaysia

Dr. Nur Intan Raihana Ruhaiyem is a highly accomplished researcher and Senior Lecturer at the School of Computer Sciences, Universiti Sains Malaysia, with notable expertise in computational biology, image processing, data visualization, and artificial intelligence applications. Her research spans deep learning, computer vision, and biomedical informatics, focusing on developing intelligent systems that enhance healthcare diagnostics, cultural heritage preservation, and data-driven decision-making. She has authored over 50 scholarly publications in reputable international journals and conferences, including IEEE Access, Biomedical Signal Processing and Control, Intelligence-Based Medicine, Diagnostics (Basel), Image and Vision Computing, and Scientific Reports. Her works have collectively garnered more than 230 citations and an h-index of 7, underscoring her growing impact in the computational and data science research community. Recent contributions such as the development of Mamba-based UNet architectures for medical image segmentation and hybrid restoration models for historical murals reflect her capacity to integrate advanced AI models into multidisciplinary domains. Dr. Ruhaiyem’s collaborative research extends internationally, with partnerships involving scholars from Australia, China, and the broader ASEAN region. Her role as a technical committee member for several prominent conferences—such as the International Visual Informatics Conference and Soft Computing in Data Science—demonstrates her leadership in promoting innovation and research excellence in data science and visual analytics. A Certified Professional Trainer recognized by Malaysia’s Human Resources Development Fund, she has also played a key role in professional education, serving as a lead instructor for national Data Science Certification programs. Through her research, mentorship, and active academic engagement, Dr. Ruhaiyem contributes significantly to advancing digital transformation, fostering analytical literacy, and bridging computational intelligence with societal needs.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

1. Younis, H. A., Ruhaiyem, N. I. R., Ghaban, W., Gazem, N. A., & Nasser, M. (2023). A systematic literature review on the applications of robots and natural language processing in education. Electronics, 12(13), 2864. Citations: 75

2. Salisu, S., Ruhaiyem, N. I. R., Eisa, T. A. E., Nasser, M., Saeed, F., & Younis, H. A. (2023). Motion capture technologies for ergonomics: A systematic literature review. Diagnostics, 13(15), 2593. Citations: 63

3. Goni, M. R., Ruhaiyem, N. I. R., Mustapha, M., Achuthan, A., & Nassir, C. M. N. C. M. (2022). Brain vessel segmentation using deep learning—A review. IEEE Access, 10, 111322–111336. Citations: 42

4. Yang, J., & Ruhaiyem, N. I. R. (2024). Review of deep learning-based image inpainting techniques. IEEE Access, 12, 138441–138482. Citations: 17

5. Younis, H. A., Ruhaiyem, N. I. R., Badr, A. A., Abdul-Hassan, A. K., Alfadli, I. M., & others. (2023). Multimodal age and gender estimation for adaptive human-robot interaction: A systematic literature review. Processes, 11(5), 1488. Citations: 16