Publications
KDD | 2026
RIPCN: A Road Impedance Principal Component Network for Probabilistic Traffic Flow Forecasting
NeurIPS | 2025
TrajMamba: An Efficient and Semantic-rich Vehicle Trajectory Pre-training Model
TransferTraj: A Vehicle Trajectory Learning Model for Region and Task Transferability
PLMTrajRec: A Scalable and Generalizable Trajectory Recovery Method with Pre-trained Language Models
UVTM: Universal Vehicle Trajectory Modeling with ST Feature Domain Generation
TrajCogn: Leveraging LLMs for Cognizing Movement Patterns and Travel Purposes from Trajectories
UniTE: A Survey and Unified Pipeline for Pre-training Spatiotemporal Trajectory Embeddings
Path-LLM: A Multi-Modal Path Representation Learning by Aligning and Fusing with Large Language Models
DutyTTE: Deciphering Uncertainty in Origin-Destination Travel Time Estimation
Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models
Pre-training General Trajectory Embeddings with Maximum Multi-view Entropy Coding
Pre-training Time-Aware Location Embeddings from Spatial-Temporal Trajectories
KDD | 2026
Traj-MLLM: Can Multimodal Large Language Models Reform Trajectory Data Mining?
AAAI | 2026
SculptDrug: A Spatial Condition-Aware Bayesian Flow Model for Structure-based Drug Design
AAAI | 2026
Spatial-Temporal Feedback Diffusion Guidance for Controlled Traffic Imputation
Diff-RNTraj: A Structure-aware Diffusion Model for Road Network-constrained Trajectory Generation
IEEE TKDE | 2024
STCDM: Spatio-Temporal Contrastive Diffusion Model for Check-In Sequence Generation
Micro-Macro Spatial-Temporal Graph-based Encoder-Decoder for Map-Constrained Trajectory Recovery
Inductive and Adaptive Graph Convolution Networks Equipped with Constraint Task for Spatial-Temporal Traffic Data Kriging
Spatial-Temporal Cross-View Contrastive Pre-Training for Check-in Sequence Representation Learning
Contrastive Pre-training with Adversarial Perturbations for Check-In Sequence Representation Learning
ESWA | 2023
Adversarial Self-Attentive Time-Variant Neural Networks for Multi-Step Time Series Forecasting
APIN | 2023
Multi-scale Adaptive Attention-based Time-Variant Neural Networks for Multi-step Time Series Forecasting
* Equal Contribution