Publications

(* indicates the student/intern I supervised)

[InfFus] Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook

Information Fusion, 2024.

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[KDD'24] Spatio-Temporal Consistency Enhanced Differential Network for Interpretable Indoor Temperature Prediction

Proceedings of The 30th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2024.

Project

[KDD'24] Personalized Federated Continual Learning via Multi-Granularity Prompt

Proceedings of The 30th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2024.

Project

[IJCNN'24] GSDI: Spatio-Temporal Contrastive Learning for Geo-Sensory Data Inference

Proceedings of 2024 International Joint Conference on Neural Networks (IJCNN 2024).

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[IJCNN'24] VQGG: Generating Adaptive Graphs for Traffic Forecasting via a Vector-Quantized Graph Generator

Proceedings of 2024 International Joint Conference on Neural Networks (IJCNN 2024).

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[TIST] Exploring the distributed knowledge congruence in proxy-data-free federated distillation

ACM Transactions on Intelligent Systems and Technology, 2024.

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[TKDE] Federated Continual Learning via Knowledge Fusion: A Survey

IEEE Transactions on Knowledge and Data Engineering, 2024.

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[TNNLS] Daily Schedule Recommendation in Urban Life Based on Deep Reinforcement Learning

IEEE Transactions on Neural Networks and Learning Systems, 2024.

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[TKDE] Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey

IEEE Transactions on Knowledge and Data Engineering, 2023.

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[TRC] A Macro-Micro Spatio-Temporal Neural Network for Traffic Prediction

Transportation Research Part C, 2023.

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[CIKM'23] MLPST: MLP is All You Need for Spatio-Temporal Prediction

Proceedings of The 32nd ACM International Conference on Information and Knowledge Management, 2023.

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[CIKM'23] DiffUFlow: Robust Fine-grained Urban Flow Inference with Denoising Diffusion Model

Proceedings of The 32nd ACM International Conference on Information and Knowledge Management, 2023.

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[InfSci] HiSTGNN: Hierarchical Spatio-Temporal Graph Neural Network for Weather Forecasting

Information Sciences, 2023.

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[AI] AutoSTG+: An Automatic Framework to Discover the Optimal Network for Spatio-temporal Graph Prediction

Artificial Intelligence, 2023.

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[TKDE] Spatio-Temporal Dynamic Graph Relation Learning for Urban Metro Flow Prediction

IEEE Transactions on Knowledge and Data Engineering, 2023.

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[AAAI'23] Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction

Proceedings of The 37th AAAI Conference on Artificial Intelligence, 2023.

PDF DOI STDL UrbanFlow Code Dataset

[AAAI'23] Win-Win: A Privacy-Preserving Federated Framework for Dual-Target Cross-Domain Recommendation

Proceedings of The 37th AAAI Conference on Artificial Intelligence, 2023.

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[AAAI'23] AutoSTL: Automated Spatio-Temporal Multi-Task Learning

Proceedings of The 37th AAAI Conference on Artificial Intelligence, 2023.

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[AAAI'23] AirFormer: Predicting Nationwide Air Quality in China with Transformers

Proceedings of The 37th AAAI Conference on Artificial Intelligence, 2023.

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[KBS] Housing Rental Suggestion Based on E-commerce Data

Knowledge-Based Systems, 2023.

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[TKDE] Mixed-Order Relation-Aware Recurrent Neural Networks for Spatio-Temporal Forecasting

IEEE Transactions on Knowledge and Data Engineering, 2022.

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[CIKM'22] TrajFormer: Efficient Trajectory Classification with Transformers

Proceedings of The 31st ACM International Conference on Information and Knowledge Management, 2022.

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[CIKM'22] Generative-Free Urban Flow Imputation

Proceedings of The 31st ACM International Conference on Information and Knowledge Management, 2022.

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[KDD'22] Precision CityShield Against Hazardous Chemicals Threats via Location Mining and Self-Supervised Learning

Proceedings of The 28th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2022.

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[DeepSpatial'22] EAST: An Enhanced Automated Machine Learning Library for Spatio-Temporal Forecasting

In The 3rd ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems, 2022.

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[KDD'22] DeepSpatial'22: The 3rd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems

Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

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[TKDE] Forecasting Fine-grained Urban Flow via Spatio-temporal Contrastive Self-Supervision

IEEE Transactions on Knowledge and Data Engineering, 2022.

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[DASFAA'22] Multi-Memory enhanced Separation Network for Indoor Temperature Prediction

Proceedings of The 27th International Conference on Database Systems for Advanced Applications.

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[TKDE] Shortening passengers' travel time: A dynamic metro train scheduling approach using deep reinforcement learning

IEEE Transactions on Knowledge and Data Engineering, 2022.

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[TKDE] Fine-grained Urban Flow Inference with Incomplete Data

IEEE Transactions on Knowledge and Data Engineering, 2022.

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[TKDE] Cross-domain knowledge graph chiasmal embedding for multi-domain item-item recommendation

IEEE Transactions on Knowledge and Data Engineering, 2022.

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[InfSci] Fairness and accuracy in horizontal federated learning

Information Sciences, 2022.

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[TKDE] Urban flow pattern mining based on multi-source heterogeneous data fusion and knowledge graph embedding

IEEE Transactions on Knowledge and Data Engineering, 2021.

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[TKDE] TrajMesa: A Distributed NoSQL-Based Trajectory Data Management System

IEEE Transactions on Knowledge and Data Engineering, 2021.

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[TKDE] Gas-Theft Suspect Detection among Boiler Room Users: A Data-Driven Approach

IEEE Transactions on Knowledge and Data Engineering, 2021.

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[WWW'21] Fine-grained Urban Flow Prediction

Proceedings of The Web Conference 2021 (WWW'21).

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[WWW'21] AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph

Proceedings of The Web Conference 2021 (WWW'21).

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[AAAI'21] Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network

In Proceedings of the 35th AAAI Conference.

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[TBD] Predicting Fine-Grained Air Quality Based on Deep Neural Networks

IEEE Transactions on Big Data, 2020.

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[IEEE IntSys] Federated Digital Gateway: Methodologies, Tools and Applications

IEEE Intelligent Systems, 2020.

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[CIKM'20] You Are How You Use: Catching Gas Theft Suspects among Diverse Restaurant Users

In Proceedings of The 29th ACM International Conference on Information and Knowledge Management.

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[TKDE] Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks

IEEE Transactions on Knowledge and Data Engineering, 2020.

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[ECML-PKDD'20] Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics

In Proceedings of ECML-PKDD 2020.

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[KDD'20] AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction

In Proceedings of The 26th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2020.

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[TKDE] Spatio-Temporal Meta Learning for Urban Traffic Prediction

IEEE Transactions on Knowledge and Data Engineering, 2020.

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[TBD] Federated Forest

IEEE Transactions on Big Data, 2020.

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[InfFus] Predicting and ranking box office revenue of movies based on big data

Information Fusion, 2020.

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[TKDE] Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning

IEEE Transactions on Knowledge and Data Engineering, 2020.

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[InfFus] Urban flow prediction from spatiotemporal data using machine learning: A survey

Information Fusion, 2020.

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[UbiComp'19] CityGuard: Citywide Fire Risk Forecasting Using A Machine Learning Approach

In Proceedings of The 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing.

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[CIKM'19] Matrix Factorization for Spatio-Temporal Neural Networks with Applications to Urban Flow Prediction

In Proceedings of The 28th ACM International Conference on Information and Knowledge Management.

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[CIKM'19] CityTraffic: Modeling Citywide Traffic via Neural Memorization and Generalization Approach

In Proceedings of The 28th ACM International Conference on Information and Knowledge Management.

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[KDD'19] UrbanFM: Inferring Fine-Grained Urban Flows

In Proceedings of The 25th ACM SIGKDD international conference on Knowledge Discovery and Data Mining.

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[KDD'19] Urban Traffic Prediction from Spatio-Temporal Data using Deep Meta Learning

In Proceedings of The 25th ACM SIGKDD international conference on Knowledge Discovery and Data Mining.

PDF Cite Code Dataset Project Project Slides Video Ranked 12 in KDD 2019

[ACL'19] DOER: Dual Cross-Shared RNN for Aspect Term-Polarity Co-Extraction

In Proceedings of The 57th Annual Meeting of the Association for Computational Linguistics.

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[CIKM'18] DeepCrime: Attentive Hierarchical Recurrent Networks for Crime Prediction

In Proceedings of The 27th ACM International Conference on Information and Knowledge Management.

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[KDD'18] Deep Distributed Fusion Network for Air Quality Prediction

In Proceedings of The 24th ACM SIGKDD international conference on Knowledge Discovery and Data Mining.

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[IJCAI'18] GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction

In Proceedings of The 27th International Joint Conference on Artificial Intelligence.

PDF Cite Code Project Ranked 15th in IJCAI 2018

[AI] Predicting Citywide Crowd Flows Using Deep Spatio-Temporal Residual Networks

Artificial Intelligence, 2018.

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[AAAI'18] When Will You Arrive Estimating Travel Time Based on Deep Neural Networks

In Proceedings of Thirty-Second AAAI Conference on Artificial Intelligence.

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[AAAI'17] Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction

Proceedings of The 31st AAAI Conference on Artificial Intelligence.

PDF Cite Code Dataset Project Project DOI Ranked 4th in AAAI 2017 Cited over 2,000

[IJCAI'16] ST-MVL: Filling missing values in geo-sensory time series data

In Proceedings of The 25th International Joint Conference on Artificial Intelligence.

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[SIGSPATIAL'16] DNN-Based Prediction Model for Spatio-Temporal Data

In Proceedings of The 24th ACM International Conference on Advances in Geographical Information Systems.

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[InfSci] Efficient parallel boolean matrix based algorithms for computing composite rough set approximations

Information Sciences, 2016.

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[TKDE] A Parallel Matrix-based Method for Computing Approximations in Incomplete Information Systems

IEEE Transactions on Knowledge and Data Engineering, 2015.

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[KDD'14] Supervised Deep Learning with Auxiliary Networks

In Proceedings of The 20th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2014.

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[InfSci] Composite rough sets for dynamic data mining

Information Sciences, 2014.

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