Yingjie Yang | Data Science | Best Researcher Award

Best Researcher Award

Yingjie YangDe Montfort University

Yingjie Yang
Affiliation De Montfort University
Country United Kingdom
Scopus ID 7409384730
Documents 236
Citations 5720
h-index 38
Subject Area Data Science
Event International Research Data Analysis Excellence & Awards
ORCID 0000-0003-4525-5624

Yingjie Yang is a researcher affiliated with De Montfort University whose scholarly profile is associated with Data Science and interdisciplinary research involving data-driven methods. The available Scopus indicators record 236 documents, 5720 citations and an h-index of 38, providing a quantitative basis for assessing publication activity and scholarly influence in relation to the Best Researcher Award. [1]

Abstract

This article presents an academic recognition profile of Yingjie Yang, affiliated with De Montfort University, for consideration under the Best Researcher Award. Available bibliometric indicators, including 236 documents, 5720 citations and an h-index of 38, are considered alongside research activity in Data Science and related scholarly contributions. [1]

Keywords

Best Researcher Award; Yingjie Yang; De Montfort University; Data Science; Research Data Analysis; Bibliometric Assessment; Scholarly Publications; Citation Impact; Research Excellence; Academic Recognition. [2]

Introduction

Academic recognition commonly considers research productivity, citation performance, publication continuity and contribution to a specialist field. Yingjie Yang’s available scholarly indicators provide a measurable profile for examining research achievement within Data Science. Such evaluation supports transparent comparison of documented academic output and influence using established bibliometric information. [3]

Research Profile

Yingjie Yang is affiliated with De Montfort University in the United Kingdom and is associated with research in Data Science. The available Scopus profile records 236 documents, 5720 citations and an h-index of 38. These indicators collectively describe sustained scholarly activity and a documented record of academic visibility. [1]

Research Contributions

The research profile demonstrates contributions represented through a substantial body of indexed scholarly documents. Within the Data Science context, such work contributes to the continuing development, application and evaluation of data-driven knowledge. The accumulated publication record also indicates engagement with research communication and dissemination across relevant academic channels. [1]

Publications

The available Scopus record lists 236 documents associated with the researcher profile, indicating sustained publication activity. Indexed publications provide an important basis for evaluating scholarly productivity because they document research dissemination and enable subsequent citation analysis. Specific publication details should be interpreted through the linked author profile and corresponding publisher records.[2]

Research Impact

The profile records 5720 citations and an h-index of 38, indicating that the published work has received measurable scholarly attention. Citation indicators are not complete measures of research quality, but they provide useful evidence of academic visibility and uptake. Their interpretation is strengthened when considered with disciplinary context and documented research outputs. [3]

Award Suitability

Based on the available publication and citation indicators, Yingjie Yang presents a documented academic profile relevant to consideration for the Best Researcher Award. The combination of publication volume, citation performance and an h-index of 38 provides objective evidence for assessment. Final recognition should remain subject to the event’s eligibility criteria and review process. [1]

Conclusion

The available research profile of Yingjie Yang reflects sustained scholarly publication activity and measurable citation impact in association with Data Science. With 236 documents, 5720 citations and an h-index of 38, the profile provides evidence suitable for structured academic evaluation. These documented indicators support informed consideration for research recognition. [1]

 References

  1. Predicting the number of care beds for older people by a novel grey Verhulst cosine self-memory model: two case studies of Jiangsu and Shanghai, China.
    https://link.springer.com/article/10.1186/s12877-026-07337-6
  2. Interpretable Temporal Graph Attention Network and Cross-Modal Fusion for Early Rumor Detection.
    https://www.researchgate.net/publication/405011816_Interpretable_Temporal_Graph_Attention_Network_and_Cross-Modal_Fusion_for_Early_Rumor_Detection
  3. A novel time-varying Wiener process for adaptive RUL prediction under multiple uncertainties
    https://www.researchgate.net/publication/401712852_A_novel_time-varying_Wiener_process_for_adaptive_RUL_prediction_under_multiple_uncertainties

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