(* indicates student I supervised, ^ indicates equal contribution)

Pre-prints

• Zhiyuan Ning*, Pengfei Wang, Pengyang Wang, Ziyue Qiao, Wei Fan, Denghui Zhang, Yi Du, Yuanchun Zhou. "Graph Soft-Contrastive Learning via Neighborhood Ranking". arXiv preprint arXiv:2209.13964, 2022. [paper] [BibTex]

Refereed Conference and Journal Publications

2024

• [IJCAI] Lu Jiang, Yanan Xiao*, Xinxin Zhao, Yuanbo Xu, Shuli Hu, Pengyang Wang, Minghao Yin. "Hierarchical Reinforcement Learning on Multi-Channel Hypergraph Neural Network for Course Recommendation". The 33rd International Joint Conference on Artificial Intelligence, 2024. 

• [IJCAI] Zhiyuan Ning*, Chunlin Tian, Meng Xiao, Wei Fan, Pengyang Wang, Li Li, Pengfei Wang, Yuanchun Zhou. "FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization". The 33rd International Joint Conference on Artificial Intelligence, 2024. 

• [IJCAI] Haihua Xu*, Wei Fan, Kun Yi, Pengyang Wang. "Decoupled Invariant Attention Network for Multivariate Time-series Forecasting". The 33rd International Joint Conference on Artificial Intelligence, 2024. 

• [IJCAI] Yicheng Zhou*^, Pengfei Wang^, Hao Dong, Denghui Zhang, Dingqi Yang, Yanjie Fu, Pengyang Wang. "Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction". The 33rd International Joint Conference on Artificial Intelligence, 2024. 

• [IJCAI] Yanan Xiao*, Lu Jiang, Kunpeng Liu, Yuanbo Xu, Pengyang Wang, Minghao Yin. "Hierarchical Reinforcement Learning for Point of Interest Recommendation". The 33rd International Joint Conference on Artificial Intelligence, 2024. 

• [IJCAI] Xuanming Hu*, Wei Fan, Haifeng Chen, Pengyang Wang, Yanjie Fu. "Reconstructing Missing Variables for Multivariate Time Series Forecasting via Conditional Generative Flows". The 33rd International Joint Conference on Artificial Intelligence, 2024. 

• [AIJ] Hao Dong*^, Pengyang Wang^, Meng Xiao, Zhiyuan Ning, Pengfei Wang, Yuanchun Zhou. "Temporal Inductive Path Neural Network for Temporal Knowledge Graph Reasoning". Artificial Intelligence, 2024. 

• [AAAI] Zhaofan Zhang*, Yanan Xiao*, Lu Jiang, Dingqi Yang, Minghao Yin, Pengyang Wang. "Spatial-Temporal Interplay in Human Mobility: A Hierarchical Reinforcement Learning Approach with Hypergraph Representation". The 38th AAAI Conference on Artificial Intelligence, 2024. [paper] [BibTex]

2023

• [TKDE] Yuhuan Lu, Dingqi Yang, Pengyang Wang, Paolo Rosso, Cudre-Mauroux, Philipe. "Schema-Aware Hyper-Relational Knowledge Graph Embeddings for Link Prediction".  IEEE Transactions on Knowledge and Data Engineering, 2023.

• [NeurIPS] Kun Yi, Qi Zhang, Wei Fan, Hui He, Pengyang Wang, Shoujin Wang, Ning An, Defu Lian, Longbing Cao, Zhendong Niu. "Frequency-domain MLPs are More Effective Learners in Time Series Forecasting". The Thirty-Seventh Annual Conference on Neural Information Processing Systems, 2023. [paper] [BibTex]

• [NeurIPS] Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu, Yanjie Fu. "FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective". The Thirty-Seventh Annual Conference on Neural Information Processing Systems, 2023. [paper] [BibTex]

• [ICDM] Camilo Gomez*, Pengyang Wang, Yanjie Fu. "Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation" (Short Paper). The 23rd IEEE International Conference on Data Mining, 2023. [paper] [BibTex]

• [ICDM] Xuanming Hu*, Wei Fan*, Kun Yi, Pengfei Wang, Yuanbo Xu, Yanjie Fu, Pengyang Wang. "Boosting Urban Prediction via Addressing Spatial Temporal Distribution Shift". The 23rd IEEE International Conference on Data Mining, 2023. [paper] [BibTex]

• [CIKM] Jialei Chen, Yuanbo Xu, Pengyang Wang, Yongjian Yang. "Deep Generative Imputation Model for Missing Not At Random Data". The 32nd ACM International Conference on Information and Knowledge Management. [paper] [BibTex]

• [TKDE] Dongjie Wang*^, Pengyang Wang^, Yanjie Fu, Kunpeng Liu, Hui Xiong, Charles E. Hughes. "Reinforced Imitative Graph Learning for Mobile User Profiling". IEEE Transactions on Knowledge and Data Engineering, 2023. [paper] 

• [IJCAI] Hao Dong*, Zhiyuan Ning, Pengyang Wang, Ziyue Qiao, Pengfei Wang, Yuanchun Zhou, and Yanjie Fu. "Adaptive Path-Memory Network for Temporal Knowledge Graph Reasoning". The 32nd International Joint Conference on Artificial Intelligence, 2023. 

• [TKDE] Meng Xiao, Ziyue Qiao, Yanjie Fu, Hao Dong, Yi Du, Pengyang Wang, Hui Xiong, and Yuanchun Zhou. "Hierarchical Interdisciplinary Topic Detection Model for Research Proposal Classification". IEEE Transactions on Knowledge and Data Engineering, 2023. (To appear) 

• [TIST] Lu Jiang*, Kunpeng Liu, Yibin Wang, Dongjie Wang, Pengyang Wang, Yanjie Fu, and Minghao Yin. "Reinforced Explainable Knowledge Concept Recommendation in MOOCs". ACM Transactions on Intelligent Systems and Technology, 2023. (To appear) 

• [AAAI] Wei Fan*, Pengyang Wang, Dongkun Wang, Dongjie Wang, Yuanchun Zhou, Yanjie Fu. "Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting". The 37th AAAI Conference on Artificial Intelligence, 2023. [paper] [BibTex]

• [AAAI] Lu Jiang*, Yibin Wang, Jianan, Pengyang Wang, Minghao Yin. "Multi-View MOOC Quality Evaluation via Information-Aware Graph Representation Learning". The 37th AAAI Conference on Artificial Intelligence, 2023. [paper] [BibTex]

• [ICDE] Kafeng Wang*, Pengyang Wang, Chengzhong Xv. "Toward Efficient Automated Feature Engineering". The 39th IEEE International Conference on Data Engineering, 2023. [paper] [BibTex]

• [TWEB] Ziyue Qiao, Pengyang Wang, Pengfei Wang, Zhiyuan Ning, Yanjie Fu, Yi Du, Yuanchun Zhou, Jianqiang Huang, Xian-Sheng Hua, Hui Xiong. ``A Dual-Channel Semi-Supervised Learning Framework on Graphs via Knowledge Transfer and Meta-Learning'', ACM Transactions on the Web, 2023. [paper] [BibTex]

2022

• [KDD] Weijieying Ren*, Pengyang Wang, Xiaolin Li, Charles E. Hughes, Yanjie Fu. "Semi-supervised Drifted Stream Learning with Short Lookback". The 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2022. [paper] [BibTex]

• [TSAS]  Dongjie Wang*, Yanjie Fu, Kunpeng Liu, Fanglan Chen, Pengyang Wang, Chang-Tien Lu. "Automated Urban Planning for Reimagining City Configuration via Adversarial Learning: Quantification, Generation, and Evaluation". ACM Transactions on Spatial Algorithms and Systems, 2022. [paper] [BibTex]

• [TBD]  Ziyue Qiao, Yanjie Fu, Pengyang Wang, Meng Xiao, Zhiyuan Ning, Yi Du, Yuanchun Zhou. "RPT: Toward Transferable Model on Heterogeneous Researcher Data via Pre-Training". IEEE Transactions on Big Data, 2022. [paper] [BibTex]

2021

• [ICDM] Meng Xiao, Ziyue Qiao, Yanjie Fu, Yi Du, Pengyang Wang, Yuanchun Zhou. "Expert Knowledge-Guided Length-Variant Hierarchical Label Generation for Proposal Classification". The 21th IEEE International Conference on Data Mining, 2021. [paper] [BibTex]

• [SIGSPATIAL] Dongjie Wang*, Kunpeng Liu, David Mohaisen, Pengyang Wang, CT Lu, Yanjie Fu. "Automated Feature-Topic Pairing: Aligning Semantic and Embedding Spaces in Spatial Representation Learning". The 29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2021. [paper] [BibTex]

• [SDM] Lu Jiang*, Pengyang Wang, Ke Cheng, Kunpeng Liu, Minghao Yin, Bo Jin, Yanjie Fu. "EduHawkes: A Neural Hawkes Process Approach for Online Study Behavior Modeling".Proceedings of the 2021 SIAM International Conference on Data Mining, 2021. [paper] [BibTex]

• [Frontiers in Big Data]  Dongjie Wang*, Kunpeng Liu, David Mohaisen, Pengyang Wang, CT Lu, Yanjie Fu. "Towards Semantically-Rich Spatial Network Representation Learning via Automated Feature Topic Pairing". Frontiers in Big Data. [paper] [BibTex]

• [Frontiers in Big Data]  Pengyang Wang, Kunpeng Liu, Dongjie Wang*, Yanjie Fu. "Measuring Urban Vibrancy of Residential Communities Using Big Crowdsourced Geotagged Data". Frontiers in Big Data. [paper] [BibTex]

2020

• [ICDM] Ziyue Qiao*, Pengyang Wang, Yanjie Fu, Yi Du, Pengfei Wang, Yuanchun Zhou. "Tree StructureAware Graph Representation Learning via Integrated Hierarchical Aggregation and Relational Metric Learning". The 20th IEEE International Conference on Data Mining. [paper] [BibTex]

• [ICDM] Dongjie Wang*, Pengyang Wang, Jingbo Zhou, Leilei Sun, Bowen Du, Yanjie Fu. "Defending Water Treatment Networks: Exploiting Spatio-temporal Effects for Cyber Attack Detection". The 20th IEEE International Conference on Data Mining. The 20th IEEE International Conference on Data Mining. [paper] [BibTex]

• [ICDM] Wei Fan, Kunpeng Liu, Hao Liu, Pengyang Wang, Yong Ge, Yanjie Fu. "Diversity-aware Interactive Reinforced Feature Selection". The 20th IEEE International Conference on Data Mining. [paper] [BibTex]

• [SIGSPATIAL] Dongjie Wang*, Yanjie Fu, Pengyang Wang, Bo Huang and Chang-Tien Lu. "Reimagining City Con×guration: Automated Urban Planning via Adversarial Learning". The 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. [paper] [BibTex]

• [CIKM] Dakshak Keerthi Chandra, Pengyang Wang, Jennifer Leopold, Yanjie Fu. "Collective Embedding with Feature Importance: A Unified Approach for Spatiotemporal Network Embedding". The 29th ACM International Conference on Information and Knowledge Management. [paper] [BibTex]

• [KDD] Pengyang Wang, Kunpeng Liu, Lu Jiang, Yanjie Fu, Xiaolin Li. "Incremental Mobile User Profiling: Reinforcement Learning with Spatial Knowledge Graph for Modeling Event Streams". The 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. [paper] [BibTex]

• [IJCAI] Pengyang Wang, Yanjie Fu, Yuanchun Zhou, Kunpeng Liu, Xiaolin Li, Kien Hua. "Exploiting Mutual Information for Substructure-aware Graph Representation Learning". The 29th International Joint Conference on Arti×cial Intelligence. [paper] [BibTex]

• [WWW] Pengyang Wang, Jiaping Gui, Zhengzhang Chen, Junghwan Rhee, Haifeng Chen, Yanjie Fu. "A Generic Edge-Empowered Graph Convolutional Network via Node-Edge Mutual Enhancement". The Web Conference 2020. [paper] [BibTex]

2019

• [TKDE] Pengyang Wang, Yanjie Fu, Yu Zheng, and Charu Aggarwal. "Spatiotemporal Representation Learning for Driving Behavior Analysis: A Joint Perspective of Peer and Temporal Dependencies". IEEE Transactions on Knowledge and Data Engineering.[paper] [BibTex]

• [CIKM] Denghui Zhang, Junming Liu, Hengshu Zhu, Yanchi Liu, Lichen Wang, Pengyang Wang, Hui Xiong. "Job2Vec: Job Title Benchmarkingwith Collective Multi-View Representation Learning". The 28th ACM International Conference on Information and Knowledge Management, 2019. [paper] [BibTex]

• [SIGSPATIAL] Dakshak Keerthi Chandra, Pengyang Wang, Yanjie Fu, Jennifer Leopold. Reliable Spatial Representation Learning by Laplacian Encoding-Decoding Networks. The 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019. [paper] [BibTex]

• [ICDM] Jiadi Du, Pengyang Wang, Yanjie Fu, Jennifer Leopold. "Beyond Geo-First Law: Learning Spatial Representations via Integrated Autocorrelations and Complementarity". The 19th IEEE International Conference on Data Mining, 2019. [paper] [BibTex]

• [KDD] Pengyang Wang, Yanjie Fu, Xiaolin Li, Hui Xiong. "Adversarial Substructured Representation Learning for Mobile User Profiling". Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2019. [paper] [BibTex]

• [KDD] Yunchao Zhang, Pengyang Wang, Xiaolin Lin, Yu Zheng, Yanjie Fu. "Unifying Inter-region Autocorrelation and Intra-region Structures for Spatial Embedding via Collective Adversarial Learning". Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2019. [paper] [BibTex]

• [AAAI] Yanjie Fu, Pengyang Wang, Jiadi Du, Le Wu, Xiaolin Lin. "Efficient Region Embedding with Multiview Spatial Networks: A Perspective of Locality-Constrained Spatial Autocorrelations". Proceedings of the 33th AAAI Conference on Arti×cial Intelligence, 2019. [paper]

2018

• [TKDE] Yanjie Fu, Guannan Liu, Yong Ge, Pengyang Wang, Hengshu Zhu, Chunxiao Li, Hui Xiong. "Representing Urban Forms: A Collective Learning Model with Heterogeneous Human Mobility Data”. IEEE Transactions on Knowledge and Data Engineering, 2018. [paper] [BibTex] 

• [TIST] Pengyang Wang, Yanjie Fu, Jiawei Zhang, Guannan Liu. "Learning Urban Community Structures: A Collective Embedding Perspective with Periodic Spatialtemporal Mobility Graphs". ACM Transactions on Intelligent Systems and Technology, 2018. [paper]

• [KDD] Pengyang Wang, Yanjie Fu, Jiawei Zhang, Pengfei Wang, Yu Zheng, Charu Aggarwal. "You Are How You Drive: Peer and Temporal-Aware Representation Learning for Driving Behavior Analysis". Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2018. [paper]

• [SDM] Kunpeng Liu, Pengyang Wang, Jiawei Zhang, Guannan Liu, Yanjie Fu and Sajal K. Das. "Incorporating Interaction Coupling among Multi-View Spatiotemporal Contexts for Mobike Destination Prediction". Proceedings of the 2018 SIAM International Conference on Data Mining, 2018. [paper]

• [SDM] Pengyang Wang, Jiawei Zhang, Guannan Liu, Yanjie Fu, Charu Aggarwal. "EnsembleSpotting: Prioritizing Vibrant Communities via POI Embedding with Multi-view Spatial Graph".Proceedings of the 2018 SIAM International Conference on Data Mining, 2018. [paper]