Majbah Uddin R&D Staff Contact 865.341.1306 | UDDINM@ORNL.GOV All Publications Agent-based modeling for multimodal transportation of CO2 for carbon capture, utilization, and storage: CCUS-agent... Understanding electric vehicle ownership using data fusion and spatial modeling Travel Patterns and Characteristics of Millennial Population in New York State Data analytics for intermodal freight transportation applications Travel Patterns and Characteristics of Population in Rural Areas of New York State A Spatial-Temporal Analysis of Travel Time Gap and Inequality between Public Transportation and Personal Vehicles... Improving the accuracy of freight mode choice models: A case study using the 2017 CFS PUF data set and ensemble learning techniques Travel Patterns and Characteristics of Low-Income Population in New York State: 2017 Update Assignment of Freight Traffic in a Large-Scale Intermodal Network under Uncertainty Factors Influencing Mode Choice of Adults with Travel-Limiting Disability Optimizing Hydrogen Fueling Infrastructure Plans on Freight Corridors for Heavy-Duty Fuel Cell Electric Vehicles Exploring the Effects of Population and Employment Characteristics on Truck Flows: An Analysis of NextGen NHTS Origin-Destina... Mobility Gaps between Low-Income and Not Low-Income Households: A Case Study in New York State Examining Rail Transportation Route of Crude Oil in the United States Using Crowdsourced Social Media Data An interpretable machine learning framework to understand bikeshare demand before and during the COVID-19 pandemic in New York City A Comparative Study of Machine Learning Algorithms for Industry-Specific Freight Generation Model Travel Patterns and Characteristics of Elderly Population in New York State: 2017 Update... Providing Levelized Cost and Waiting Time Inputs for HDV Hydrogen Refueling Station Planning: A Case Study of U.S. I-75 Corridor Modeling Freight Traffic Demand and Highway Networks for Hydrogen Fueling Station Planning: A Case Study of U.S. Interstate 75 Corridor Freight Analysis Framework Version 5 (FAF5) Base Year 2017 Data Development Technical Report Modeling freight mode choice using machine learning classifiers: a comparative study using Commodity Flow Survey (CFS) data Model for Collaboration among Carriers to Reduce Empty Container Truck Trips Delivering Contextual Knowledge and Critical Skills of Disruptive Technologies through Problem-Based Learning in Research Experiences for Undergraduates Setting Injury severity analysis of truck-involved crashes under different weather conditions Key Links Curriculum Vitae Organizations Energy Science and Technology Directorate Buildings and Transportation Science Division Vehicle and Mobility Systems Research Section Transportation Analytics and Decision Sciences Group User Facilities National Transportation Research Center
