Adedolapo Ogungbire Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
unknown
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Adedolapo Ogungbire’s research focuses on transportation patterns and their shifts, particularly in response to major societal events. Recent work investigates how ridesourcing services like Uber and Lyft adapted during the COVID-19 pandemic, using Chicago as a case study. Ogungbire has also applied machine learning to forecast workforce needs for state transportation agencies and employed explainable AI to understand telecommuting trends before, during, and after the pandemic. These studies contribute to understanding human mobility and the impact of public health crises on transportation systems and work behaviors. Ogungbire's scholarship metrics include an h-index of 2 and 4 total publications with 9 citations.
Metrics
- h-index: 2
- Publications: 4
- Citations: 142
Selected Publications
-
Unlocking telecommuting patterns before, during, and after the COVID-19 pandemic: An explainable AI-driven study (2024)
-
Hyperparameter Tuning in Machine Learning: A Comprehensive Review (2024)
-
Workforce forecasting for state transportation agencies: A machine learning approach (2024)
-
From stay-at-home to reopening: A look at how ridesourcing fared during the COVID-19 pandemic in Chicago, Illinois (2023)
-
Examining the Impact of the COVID-19 Pandemic on Ridesourcing Usage: A Case Study of Chicago (2022)
Collaborators
Researchers in the database who share publications
Similar Researchers
Based on overlapping research topics