collaborators

20 papers

stat.ML2026

Alternative Graph Neural Networks: Synergizing GEV Models and Deep Learning for Travel Mode Choice Modeling

Yuqi Zhou, Zhanhong Cheng, Dingyi Zhuang +3

Generalized extreme value models capture dependence among choice alternatives in discrete choice modeling, but require this dependence to be predefined, symmetric, and shared unifo…

physics.soc-ph2026

Public transit gains and spatially uneven travel demand changes after NYC congestion pricing

Donghang Li, Dingyi Zhuang, Yunlin Li +5

New York City implemented the nation's first cordon-based congestion pricing program in January 2025, providing an opportunity to evaluate how system-wide urban mobility responds t…

cs.AI2026

AlphaOPT: Formulating Optimization Programs with Self-Improving LLM Experience Library

Minwei Kong, Ao Qu, Xiaotong Guo +12

Optimization modeling underlies critical decision-making across industries, yet remains difficult to automate: natural-language problem descriptions must be translated into precise…

cs.DB2026

Ozone: A Unified Platform for Transportation Research

Ou Zheng, Ruyi Feng, Yufeng Yang +11

Intelligent Transportation Systems increasingly depend on heterogeneous data from roadside cameras, UAV imagery, LiDAR, and in-vehicle sensors, yet the lack of unified data standar…

cs.LG2026

Bridge: Retrieval-Augmented Spatiotemporal Modeling for Urban Delivery Demand

Yihong Tang, Tong Nie, Junlin He +3

Forecasting urban delivery demand becomes substantially more challenging when newly added service regions lack historical records. Existing spatiotemporal forecasters effectively m…

cs.CV2026

Think Before You Drive: World Model-Inspired Multimodal Grounding for Autonomous Vehicles

Haicheng Liao, Huanming Shen, Bonan Wang +8

Interpreting natural-language commands to localize target objects is critical for autonomous driving (AD). Existing visual grounding (VG) methods for autonomous vehicles (AVs) typi…