Model for Collaboration among Carriers to Reduce Empty Container Truck Trips. - Majbah Uddin; Nathan Huynh (Inf., 2020)

An Interpretable Machine Learning Framework to Understand Bikeshare Demand before and during the COVID-19 Pandemic in New York City. - Majbah Uddin; Ho-Ling Hwang; Md Sami Hasnine (CoRR, 2023)

Modeling Freight Mode Choice Using Machine Learning Classifiers: A Comparative Study Using the Commodity Flow Survey (CFS) Data. - Majbah Uddin; Sabreena Anowar; Naveen Eluru (CoRR, 2024)

Evaluation of Google's Voice Recognition and Sentence Classification for Health Care Applications. - Majbah Uddin; Nathan Huynh; José M. Vidal; Kevin M. Taaffe; Lawrence D. Fredendall; Joel S. Greenstein (CoRR, 2024)

Exploring the Effects of Population and Employment Characteristics on Truck Flows: An Analysis of NextGen NHTS Origin-Destination Data. - Majbah Uddin; Yuandong Liu; Hyeonsup Lim (CoRR, 2024)

Examining Rail Transportation Route of Crude Oil in the United States Using Crowdsourced Social Media Data. - Yuandong Liu; Majbah Uddin; Shih-Miao Chin; Ho-Ling Hwang; Jiaoli Chen (CoRR, 2024)

Agent-Based Modeling for Multimodal Transportation of CO2 for Carbon Capture, Utilization, and Storage: CCUS-Agent. - Majbah Uddin; Robin Clark; Michael Hilliard; Joshua Thompson; Matthew Langholtz; Erin Webb (CoRR, 2024)

Improving the accuracy of freight mode choice models: A case study using the 2017 CFS PUF data set and ensemble learning techniques. - Diyi Liu; Hyeonsup Lim; Majbah Uddin; Yuandong Liu; Lee D. Han; Ho-Ling Hwang; Shih-Miao Chin (Expert Syst. Appl., 2024)