Awele Okolie | Artificial Intelligence | Research Excellence Award

Ms. Awele Okolie | Artificial Intelligence | Research Excellence Award

Data Analyst Intern | Wentworth Institute of Technology | United States

Ms. Awele Okolie is an emerging researcher in Machine Learning and Artificial Intelligence, with a strong focus on socially impactful, data-driven research. Her work spans food insecurity prediction, financial fraud detection, healthcare analytics, traffic safety modeling, and explainable AI, demonstrating applied innovation across public policy and safety-critical domains. Her research interests include predictive modeling, explainable machine learning, spatiotemporal analysis, and AI-driven decision systems, supported by skills in data analytics, statistical modeling, and real-world dataset integration. Her scholarly contributions show growing recognition, with Google Scholar metrics of 41 citations, 14 documents, and an h-index of 5, while Scopus citations, documents, and h-index are not provided. Overall, her work reflects a strong commitment to transparent, ethical, and high-impact artificial intelligence research.

 

Citation Metrics (Google Scholar)

41
30
20
10
0

Citations

41

Documents

14

h-index

5

Citations

Documents

h-index

View Google Scholar Profile  View ResearchGate Profile

Featured Publications


Predicting food insecurity across US census tracts: A machine learning analysis using the USDA Food Access Research Atlas

– International Journal of Science and Research Archive, 17(2), 1156-1172, 2025 (Citations: 11)


An Explainable XGBoost Framework for Detecting Fraudulent Financial Transactions

– Journal of Scientific Research and Reports, 31(12), 244-255, 2025 (Citations: 6)


Spatiotemporal analysis and predictive modeling of traffic accidents in Boston: Insights for advancing Vision Zero initiatives

– International Journal of Science and Research Archive, 17(1), 528-543, 2025 (Citations: 6)


Machine learning approaches for predicting 30-day hospital readmissions: Evidence from Massachusetts healthcare data

– World Journal of Advanced Research and Reviews, 28(1), 1-12, 2025 (Citations: 6)