Tiffany Lim
Deep hybrid model with satellite imagery: how to combine demand modeling and computer vision for travel behavior analysis? Transportation Research Part B. 2024;179.
MetRoBERTa: Leveraging Traditional Customer Relationship Management Data to Develop a Transit-Topic-Aware Language Model. Transportation Research Record. 2024.
Modeling virus transmission risks in commuting with emerging mobility services: A case study of COVID-19. Travel Behaviour and Society. 2024;34.
Can Mobility of Care be Identified from Transit Fare Card Data? A Case Study in Washington D.C. Findings. 2023.
Computer Vision for Transit Travel Time Prediction: An End-to-End Framework Using Roadside Urban Imagery. Public Transport. 2023.
Cooperative Bus Holding and Stop-skipping: A Deep Reinforcement Learning Framework. Transportation Research Part C: Emerging Technologies. 2023;155.
Examining the interactions between working from home, travel behavior and change in car ownership due to the impact of COVID-19. Travel Behaviour and Society. 2023;33.
Fairness-enhancing deep learning for ride-hailing demand prediction. IEEE Open Journal of Intelligent Transportation Systems . 2023;4.
Reconstructing Transit Vehicle Trajectory Using High-Resolution GPS Data. 2023 IEEE 26th International Conference on Intelligent Transportation Systems. 2023.
SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks. Temporal Graph Learning Workshop @ NeurIPS 2023. 2023.
ST-GIN: An Uncertainty Quantification Approach in Traffic Data Imputation with Spatio-temporal Graph Attention and Bidirectional Recurrent United Neural Networks. 2023 IEEE 26th International Conference on Intelligent Transportation Systems. 2023.
Train following model for urban rail transit performance analysis. Transportation Research Part C: Emerging Technologies. 2023;148.
Understanding multi-homing and switching by platform drivers. Transportation Research Part C: Emerging Technologies. 2023;154.