Junior Momo Ziazet | AI Advancements | Best Researcher Award

Published on by Scientist Day

Global Scientist Day Awards

Junior Momo Ziazet
Concordia University, Canada
Junior Momo Ziazet
Affiliation Concordia University
Country Canada
Scopus ID 57219750482
Documents 5
Citations 34
h-index 3
Subject Area AI Advancements
Event Global Scientist Day Awards

Junior Momo Ziazet is a researcher affiliated with Concordia University, Canada, whose scholarly work contributes to the evolving field of artificial intelligence and computational research. Through peer-reviewed scientific publications indexed by Scopus, the researcher has demonstrated continued engagement with AI-related investigations and interdisciplinary technological innovation. The Global Scientist Day Awards recognizes researchers whose work supports scientific advancement through measurable academic output, research quality, and scholarly visibility.[1][2]

Abstract

This article presents an academic overview of Junior Momo Ziazet and summarizes publicly available scholarly indicators associated with the researcher’s contributions to artificial intelligence. The profile highlights institutional affiliation, publication activity, citation metrics, and research visibility while providing a neutral overview suitable for academic recognition.[1][3]

Keywords

Artificial Intelligence, Machine Learning, Intelligent Systems, Computational Intelligence, AI Research, Scientific Publications, Research Evaluation, Concordia University, Citation Analysis, Global Scientist Day Awards.

Introduction

Artificial intelligence has become one of the fastest-growing scientific disciplines, influencing numerous sectors including healthcare, engineering, education, automation, and data science. Researchers working within this domain contribute to algorithmic development, intelligent decision-making systems, and computational methodologies that improve efficiency and knowledge discovery.[2][4]

Research Profile

Junior Momo Ziazet is affiliated with Concordia University in Canada and has established a documented research presence within Scopus-indexed literature. The available bibliometric indicators include five indexed publications, thirty-four citations, and an h-index of three, reflecting measurable scholarly engagement within the research community.[1]

Research Contributions

The researcher’s work contributes to advancing artificial intelligence through scholarly investigations that support computational methodologies and intelligent system development. Published studies demonstrate participation in contemporary scientific discussions while contributing evidence-based findings to the academic community.[2]

Publications

The available Scopus author profile records five indexed publications associated with the researcher. These publications collectively demonstrate scholarly productivity and contribute to citation-based assessment within the field of artificial intelligence. Representative DOI resources illustrating scholarly publishing standards are included for reference.[1]

Research Impact

Citation-based indicators provide one perspective on scholarly influence by reflecting how frequently published work is referenced by other researchers. Although bibliometric measures do not fully represent scientific quality, they remain widely used in institutional evaluations and research benchmarking.[3]

Award Suitability

Based on publicly available scholarly information, Junior Momo Ziazet demonstrates characteristics commonly considered during academic recognition processes, including peer-reviewed publication activity, indexed research output, citation performance, and institutional affiliation.Final award decisions remain subject to independent peer evaluation and the official assessment procedures established by the Global Scientist Day Awards.[4]

Conclusion

Junior Momo Ziazet represents an emerging scholarly profile within artificial intelligence through documented research activity and measurable academic metrics. Continued publication, collaboration, and scientific engagement are expected to further strengthen research visibility and long-term scholarly impact. This profile provides a structured academic summary suitable for recognition within the Global Scientist Day Awards framework.[1]

References

  1. Elsevier (2026.). Scopus author details: Junior Momo Ziazet, Author ID 57219750482. Scopus.
    https://www.scopus.com/pages/authors/57219750482
  2. Google Scholar (2026.). Scholar profile for Junior Momo Ziazet.
    https://scholar.google.com/citations?hl=fr&user=0HSGA14AAAAJ
  3. Enhancing Energy Management and Efficiency of Asynchronous Federated Split Learning.
    https://ieeexplore.ieee.org/document/11162158
  4. Global Scientist Day Awards (2026.). Official Award Website.
    https://scientistday.org/

Saleem Ramadan | Data Science | Best Researcher Award

Published on by Scientist Day

Assoc. Prof. Dr. Saleem Ramadan | Data Science | Best Researcher Award

Assoc. Prof. Dr. Saleem Ramadan | Al Hussein Technical University | Jordan

Dr. Saleem Z. Ramadan is an accomplished Data Analyst and Business Analyst with a strong interdisciplinary background in industrial engineering, systems optimization, and data science. With academic and consulting experience across the U.S. and Jordan, he has applied data-driven decision-making, predictive analytics, and optimization modeling to complex problems in healthcare, manufacturing, and finance. Dr. Ramadan holds a Ph.D. in Systems Engineering from Ohio University and has served as Acting Chair and Associate Professor at Al Hussein Technical University, leading research and teaching initiatives integrating machine learning and operations analytics. He has developed impactful analytics solutions—ranging from hydroponic resource optimization and radiology workflow improvement to financial risk dashboards—using tools such as Python, SQL, Power BI, Tableau, and Minitab. His consulting work with Healthcare Operations & Performance Excellence (HOPE) led to measurable improvements in hospital performance through Six Sigma and process control techniques. A Certified Analytics Professional (CAP) and Microsoft Power BI Data Analyst Associate, Dr. Ramadan has authored 20 peer-reviewed publications, accumulating 236 citations from 230 documents with an h-index of 6. His recent works focus on machine learning–driven optimization, surgical scheduling prediction, and additive manufacturing parameter tuning. Dr. Ramadan’s combination of technical proficiency, academic leadership, and applied research impact uniquely positions him at the intersection of analytics innovation and business performance excellence.

Profiles:  Scopus | Google Scholar | LinkedIn

Featured Publications

Ramadan, S., Abushams, M., Al-Dahidi, S., & Odeh, I. (2025). A data-driven approach for predicting remaining intra-surgical time and enhancing operating room efficiency. Journal of Industrial Engineering and Management.

Ramadan, S., Abushams, M., Al-Dahidi, S., & Odeh, I. (2024). Optimizing tensile strength and energy consumption for FDM through mixed-integer nonlinear multi-objective optimization and design of experiments. Heliyon.