Hatem Abuelizz | Quantitative Research | Best Researcher Award

Best Researcher Award

Hatem Abuelizz — King Saud University, Saudi Arabia

Hatem Abuelizz
Affiliation King Saud University
Country Saudi Arabia
Scopus ID 56667652300
Documents 149
Citations 2,037
h-index 24
Subject Area Quantitative Research
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0002-7092-7544

Hatem Abuelizz is a researcher affiliated with King Saud University whose indexed scholarly record comprises 149 documents, 2,037 citations, and an h-index of 24. These bibliometric indicators provide a quantitative basis for considering research productivity, scholarly visibility, and citation influence within the context of the International Research Data Analysis Excellence & Awards.[1]

Abstract

This academic recognition profile presents Hatem Abuelizz in relation to the Best Researcher Award within the International Research Data Analysis Excellence & Awards. The assessment emphasizes quantitative indicators, including publication volume, citation count, and h-index, while positioning these measures within a broader framework of research productivity, scholarly visibility, and data-oriented research evaluation.[1]

Keywords

  • Quantitative Research
  • Research Data Analysis
  • Bibliometric Evaluation
  • Research Productivity
  • Citation Impact
  • h-index
  • Scholarly Research
  • Research Excellence

Introduction

Quantitative research applies numerical measurement, statistical methods, and structured datasets to investigate research questions objectively. Within research data analysis, quantitative indicators can support systematic assessment of productivity and scholarly influence. Hatem Abuelizz’s indexed record provides measurable evidence that can be considered when evaluating research performance for an international recognition program.[1]

Research Profile

Hatem Abuelizz is affiliated with King Saud University in Saudi Arabia. The supplied Scopus information identifies 149 documents, 2,037 citations, and an h-index of 24. His ORCID record provides a persistent researcher identifier, while Scopus supplies an indexed bibliometric profile useful for structured quantitative research evaluation and scholarly record verification.[1][2]

Research Contributions

The documented research record indicates sustained scholarly activity measured through indexed publications and citation accumulation. A portfolio of 149 documents represents substantial publication activity, while 2,037 citations and an h-index of 24 provide complementary quantitative indicators. These measures can assist reviewers in examining research productivity, influence, continuity, and visibility across scholarly outputs.[1]

Publications

The supplied Scopus profile records 149 documents associated with Hatem Abuelizz. This publication count provides a quantitative measure of documented scholarly output, although publication totals alone do not establish research quality. Detailed assessment should additionally consider article relevance, methodological rigor, venue quality, collaboration, citation distribution, and individual contribution to published research.[1]

Research Impact

Research impact can be examined through multiple complementary indicators. The reported 2,037 citations reflect accumulated scholarly attention, while an h-index of 24 indicates repeated citation performance across a substantial portion of the publication record. Together, these measures provide quantitative evidence of visibility and influence that can inform comparative research assessment.[1]

Award Suitability

For the International Research Data Analysis Excellence & Awards, the documented publication and citation indicators provide relevant quantitative evidence for evaluating research achievement. The combination of 149 documents, 2,037 citations, and an h-index of 24 demonstrates a substantial indexed scholarly record. Final award suitability should also incorporate qualitative review and field-specific evidence.[1][3]

Conclusion

Hatem Abuelizz presents a measurable scholarly profile relevant to quantitative research evaluation. The reported publication count, citation total, and h-index establish a substantial bibliometric record for consideration in the Best Researcher Award. These indicators support structured assessment while recognizing that comprehensive evaluation should combine quantitative evidence with research quality, relevance, originality, and contribution.[1][2]

References

  1. Synthesis and anticancer activity of new quinazoline derivatives.
    https://www.researchgate.net/publication/316360785_Synthesis_and_anticancer_activity_of_new_quinazoline_derivatives
  2. Experimental and theoretical evaluation of eco-friendly of pyrhazole-amide conjugates on the corrosion inhibition performance for mild steel in 1 M HCl solution.
    https://www.researchgate.net/publication/395361917_Experimental_and_theoretical_evaluation_of_eco-friendly_of_pyrhazole-amide_conjugates_on_the_corrosion_inhibition_performance_for_mild_steel_in_1_M_HCl_solution
  3. An in-depth study of indolone derivatives as potential lung cancer treatment
    https://www.researchgate.net/publication/388072633_An_in-depth_study_of_indolone_derivatives_as_potential_lung_cancer_treatment

Richard Ingwe Chuy | Predictive Analytics | Best Researcher Award

Dr. Richard Ingwe Chuy | Predictive Analytics | Best Researcher Award

Dr. Richard Ingwe Chuy at Programme National de Lutte contre le Sida, Congo, Democratic Republic of the

Professional Profile👨‍🎓

 👤 Summary

Richard Ingwe Chuy is a Congolese expert in methodology and statistics, specializing in biomedical research and data science. With over eight years of experience, he provides consultancy services and training in research design and statistical analysis, particularly in public health and epidemiology.

🎓 Education

  • Doctorant en Technologie de l’Information, Spécialité Science des Données
    Bircham International University, Espagne & Delaware (Mai 2022)
  • Master 2 en Méthodologie et Statistiques en Recherche Biomédicale
    Université Paris Saclay, France (2020/2021)
  • Master 1 en Méthodes en Santé Publique
    Université Paris Saclay, France (2019/2020)
  • Diplôme en Médecine Générale
    Université de Lubumbashi (UNILU), République Démocratique du Congo (2013)

💼 Professional Experience

Richard is currently a Consultant Indépendant, providing expertise in methodology and statistics to various organizations. He facilitates training on data analysis and research design. Previously, he worked at the Programme National de Lutte contre le VIH/SIDA et les IST in the Ministry of Health, DRC, and has experience in clinical medicine in Lubumbashi.

🔬 Research Interests

His research interests include methods in epidemiology and clinical studies, predictive analysis, and qualitative research. Richard is also focused on gender, human rights, and vulnerability reduction in public health contexts.

🤝 Professional Affiliations

Richard is a member of several professional organizations, including the International Aids Society (IAS), AFRAVIH, and the CQUIN network.

💻 Technical Skills

He possesses advanced skills in Microsoft Office, R, Python, SAS, and qualitative analysis software (Nvivo, QDA Miner Lite), as well as experience in electronic questionnaire design (CoboCollect, ODK).

 

Top Noted Publications 📖

  • Authors: Michel Luhembwe, Richard Ingwe, Aimée Lulebo, Dalau Nkamba, John Ditekemena
  • Journal: BioMed
  • Volume: 4
  • Issue: 3
  • Pages: 27
  • Year: 2024

Chenwi Neba Cyril | Predictive Analytics | Excellence in Research

Mr. Chenwi Neba Cyril ,Predictive Analytics, Excellence in Research

Austin Peay State University, United States

Author Profile

Orcid Profile
Google Scholar Profile
Research Gate Profile

🌟Summary

Chenwi Neba Cyril is a seasoned Predictive Data Analyst at Walmart Inc. and holds a Master’s Degree in Computer Science and Quantitative Methods. His expertise spans predictive analytics, with notable contributions in retail sales forecasting, credit card fraud detection, and environmental research. Cyril has published extensively in reputable journals and actively engages in consultancy projects. His current research focuses on integrating predictive analytics into geochemistry, advancing cancer detection through machine learning, and developing data-driven solutions for cybersecurity and public health challenges.

🎓Education

Chenwi Neba Cyril holds a Master’s Degree in Computer Science and Quantitative Methods with a concentration in Predictive Analytics from Austin Peay State University, USA, where he graduated with a perfect GPA of 4.00. He also earned Bachelor’s and Master’s degrees in Earth and Space Sciences from the University of Yaoundé I in Cameroon. His academic journey has equipped him with a robust foundation in both technical sciences and advanced quantitative methods, facilitating his expertise in predictive data analysis and research across diverse domains.

💼 Professional Experience

Chenwi Neba Cyril currently serves as a Pricing Analyst and Manager at Walmart Inc., where he applies his extensive knowledge of data science and predictive analytics to drive strategic business decisions. His role involves leveraging advanced analytical techniques to optimize pricing strategies and enhance revenue growth. Cyril has also undertaken consultancy projects with multiple banks, specializing in improving fraud detection systems and customer relationship management through predictive analytics. Additionally, he has collaborated with microfinance institutions in Cameroon on projects aimed at implementing data-driven solutions for environmental challenges and sustainable development initiatives. His professional journey reflects a commitment to leveraging analytics to drive innovation and impact across various sectors.

🔬 Research Interests

Chenwi Neba Cyril’s research interests are interdisciplinary, spanning the integration of predictive analytics in geochemistry, machine learning applications for cancer detection, data-driven cybersecurity for military operations, and combating the opioid epidemic through advanced analytics. His current research aims to apply predictive analytics to identify geochemical pathways and predict mineral sources, revolutionize cancer detection methodologies through machine learning advancements, develop proactive cybersecurity solutions for military networks, and optimize interventions to mitigate the opioid crisis using big data analytics. Cyril’s work underscores a commitment to harnessing data-driven approaches to address complex societal challenges and drive transformative outcomes in public health and cybersecurity domains.

📖 Publication Top Noted

  • Authors: Cyril Neba, Gillian Nsuh, Adrian Neba, F Webnda, Victory Ikpe, Adeyinka Orelaja, Nabintou Anissia Sylla
  • Journal: Unfallchirurgie (Germany)
  • Volume: 20
  • Issue: 7
  • Pages: 9-30
  • Year: 2024

Article : Advancing Retail Predictions: Integrating Diverse Machine Learning Models for Accurate Walmart Sales Forecasting

  • Authors: Nabintou Anissia Sylla, Cyril Neba C., Gerard Shu F., Gillian Nsuh, Philip Amouda A., Adrian Neba F., F. Webnda, Victory Ikpe, Adeyinka Orelaja
  • Journal: Asian Journal of Probability and Statistics
  • Volume: 26
  • Issue: 7
  • Pages: 1-23
  • Year: 2024

Article : Comparative Analysis of Stock Price Prediction Models: Generalized Linear Model (GLM), Ridge Regression, Lasso Regression, Elasticnet Regression, and Random Forest – A Case …

  • Authors: Cyril Neba C., Gillian Nsuh, Gerard Shu F., Philip Amouda A., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 10
  • Pages: 12
  • Year: 2023

Article : Time Series Analysis and Forecasting of COVID-19 Trends in Coffee County, Tennessee, United States

  • Authors: Cyril Neba C., Gerard Shu F., Gillian Nsuh, Philip Amouda A., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 9
  • Pages: 14
  • Year: 2023

Article : Using Regression Models to Predict Death Caused by Ambient Ozone Pollution (AOP) in the United States

  • Authors: Cyril Neba C., Gerard Shu F., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda, Philip Amouda A.
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 9
  • Pages: 18
  • Year: 2023

Chenwi Neba Cyril | Predictive Analytics | Best Researcher Award

Mr. Chenwi Neba Cyril ,Predictive Analytics, Best Researcher Award

Austin Peay State University, United States

Author Profile

Orcid Profile
Google Scholar Profile
Research Gate Profile

🌟Summary

Chenwi Neba Cyril is a seasoned Predictive Data Analyst at Walmart Inc. and holds a Master’s Degree in Computer Science and Quantitative Methods. His expertise spans predictive analytics, with notable contributions in retail sales forecasting, credit card fraud detection, and environmental research. Cyril has published extensively in reputable journals and actively engages in consultancy projects. His current research focuses on integrating predictive analytics into geochemistry, advancing cancer detection through machine learning, and developing data-driven solutions for cybersecurity and public health challenges.

🎓Education

Chenwi Neba Cyril holds a Master’s Degree in Computer Science and Quantitative Methods with a concentration in Predictive Analytics from Austin Peay State University, USA, where he graduated with a perfect GPA of 4.00. He also earned Bachelor’s and Master’s degrees in Earth and Space Sciences from the University of Yaoundé I in Cameroon. His academic journey has equipped him with a robust foundation in both technical sciences and advanced quantitative methods, facilitating his expertise in predictive data analysis and research across diverse domains.

💼 Professional Experience

Chenwi Neba Cyril currently serves as a Pricing Analyst and Manager at Walmart Inc., where he applies his extensive knowledge of data science and predictive analytics to drive strategic business decisions. His role involves leveraging advanced analytical techniques to optimize pricing strategies and enhance revenue growth. Cyril has also undertaken consultancy projects with multiple banks, specializing in improving fraud detection systems and customer relationship management through predictive analytics. Additionally, he has collaborated with microfinance institutions in Cameroon on projects aimed at implementing data-driven solutions for environmental challenges and sustainable development initiatives. His professional journey reflects a commitment to leveraging analytics to drive innovation and impact across various sectors.

🔬 Research Interests

Chenwi Neba Cyril’s research interests are interdisciplinary, spanning the integration of predictive analytics in geochemistry, machine learning applications for cancer detection, data-driven cybersecurity for military operations, and combating the opioid epidemic through advanced analytics. His current research aims to apply predictive analytics to identify geochemical pathways and predict mineral sources, revolutionize cancer detection methodologies through machine learning advancements, develop proactive cybersecurity solutions for military networks, and optimize interventions to mitigate the opioid crisis using big data analytics. Cyril’s work underscores a commitment to harnessing data-driven approaches to address complex societal challenges and drive transformative outcomes in public health and cybersecurity domains.

📖 Publication Top Noted

  • Authors: Cyril Neba, Gillian Nsuh, Adrian Neba, F Webnda, Victory Ikpe, Adeyinka Orelaja, Nabintou Anissia Sylla
  • Journal: Unfallchirurgie (Germany)
  • Volume: 20
  • Issue: 7
  • Pages: 9-30
  • Year: 2024

Article : Advancing Retail Predictions: Integrating Diverse Machine Learning Models for Accurate Walmart Sales Forecasting

  • Authors: Nabintou Anissia Sylla, Cyril Neba C., Gerard Shu F., Gillian Nsuh, Philip Amouda A., Adrian Neba F., F. Webnda, Victory Ikpe, Adeyinka Orelaja
  • Journal: Asian Journal of Probability and Statistics
  • Volume: 26
  • Issue: 7
  • Pages: 1-23
  • Year: 2024

Article : Comparative Analysis of Stock Price Prediction Models: Generalized Linear Model (GLM), Ridge Regression, Lasso Regression, Elasticnet Regression, and Random Forest – A Case …

  • Authors: Cyril Neba C., Gillian Nsuh, Gerard Shu F., Philip Amouda A., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 10
  • Pages: 12
  • Year: 2023

Article : Time Series Analysis and Forecasting of COVID-19 Trends in Coffee County, Tennessee, United States

  • Authors: Cyril Neba C., Gerard Shu F., Gillian Nsuh, Philip Amouda A., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 9
  • Pages: 14
  • Year: 2023

Article : Using Regression Models to Predict Death Caused by Ambient Ozone Pollution (AOP) in the United States

  • Authors: Cyril Neba C., Gerard Shu F., Adrian Neba F., Aderonke Adebisi, P. Kibet., F. Webnda, Philip Amouda A.
  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 8
  • Issue: 9
  • Pages: 18
  • Year: 2023