I’m an Associate Professor at Institute of Automation, Chinese Academy of Sciences (CASIA). Currently, I mainly focus on data mining, recommender systems, graph neural networks, fake news detection and AI for science. Before that, I received my PhD degree from CASIA, where I mainly focused on recommender systems and text mining.
PhD in Artificial Intelligence, 2013-2018
Institution of Automation, Chinese Academy of Sciences (CASIA)
BSc in Electronic Science, 2009-2013
Yanshan University
    Selected Publications:
Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation [paper] [arXiv] [code]
Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu and Liang Wang
IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), Accepted
Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations [paper] [arXiv]
Yingtao Luo, Qiang Liu (co-first and corresponding author), Yuntian Chen, Wenbo Hu, Tian Tian and Jun Zhu
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
Mining Stable Preferences: Adaptive Modality Decorrelation for Multimedia Recommendation [paper] [arXiv]
Jinghao Zhang, Qiang Liu, Shu Wu and Liang Wang
International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2023
Counterfactual Debiasing for Fact Verification [paper]
Weizhi Xu, Qiang Liu (co-first author), Shu Wu and Liang Wang
Annual Meeting of the Association for Computational Linguistics (ACL), 2023
Learning Latent Relations for Temporal Knowledge Graph Reasoning [paper]
Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu and Liang Wang
Annual Meeting of the Association for Computational Linguistics (ACL), 2023
RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring [paper] [arXiv]
Qiang Liu, Yingtao Luo, Shu Wu, Zhen Zhang, Xiangnan Yue, Hong Jin and Liang Wang
IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023
Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning [paper] [code]
Mengqi Zhang, Yuwei Xia, Qiang Liu (corresponding author), Shu Wu and Liang Wang
The Web Conference (WWW), 2023
Dynamic Graph Neural Networks for Sequential Recommendation [paper] [arXiv] [code]
Mengqi Zhang, Shu Wu, Xueli Yu, Qiang Liu and Liang Wang
IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023
MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning [paper] [arXiv]
Yuwei Xia, Mengqi Zhang, Qiang Liu (corresponding author), Shu Wu and Xiao-Yu Zhang
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Deep Stable Representation Learning on Electronic Health Records [paper] [arXiv] [code]
Yingtao Luo, Zhaocheng Liu and Qiang Liu (corresponding author)
IEEE International Conference on Data Mining (ICDM), 2022
Evidence-aware Fake News Detection with Graph Neural Networks [paper] [arXiv] [code]
Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu and Liang Wang
The Web Conference (WWW), 2022
An Empirical Study of Graph Contrastive Learning [paper] [arXiv] [code]
Yanqiao Zhu, Yichen Xu, Qiang Liu and Shu Wu
Advances in Neural Information Processing Systems (NeurIPS), 2021
Mining Cross Features for Financial Credit Risk Assessment [paper] [arXiv]
Qiang Liu, Zhaocheng Liu, Haoli Zhang, Yuntian Chen and Jun Zhu
ACM International Conference on Information and Knowledge Management (CIKM), 2021
Mining Latent Structures for Multimedia Recommendation [paper] [arXiv] [code]
Jinghao Zhang, Yanqiao Zhu, Qiang Liu (corresponding author), Shu Wu, Shuhui Wang and Liang Wang
ACM International Conference on Multimedia (ACMMM), 2021
STAN: Spatio-Temporal Attention Network for Next Point-of-Interest Recommendation [paper] [arXiv] [code]
Yingtao Luo, Qiang Liu (corresponding author) and Zhaocheng Liu
The Web Conference (WWW), 2021
Graph Contrastive Learning with Adaptive Augmentation [paper] [arXiv] [code]
Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu and Liang Wang
The Web Conference (WWW), 2021
Mining Significant Microblogs for Misinformation Identification: An Attention-based Approach [paper]
Qiang Liu, Feng Yu, Shu Wu and Liang Wang
ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2018
A Convolutional Approach for Misinformation Identification [paper]
Feng Yu, Qiang Liu, Shu Wu, Liang Wang and Tieniu Tan
International Joint Conference on Artificial Intelligence (IJCAI), 2017
DeepStyle: Learning User Preferences for Visual Recommendation [paper]
Qiang Liu, Shu Wu and Liang Wang
International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2017
Multi-behavioral Sequential Prediction with Recurrent Log-bilinear Model [paper]
Qiang Liu, Shu Wu and Liang Wang
IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2017
Context-aware Sequential Recommendation [paper]
Qiang Liu, Shu Wu, Diyi Wang, Zhaokang Li and Liang Wang
IEEE International Conference on Data Mining (ICDM), 2016
A Dynamic Recurrent Model for Next Basket Recommendation [paper]
Feng Yu, Qiang Liu (co-first author), Shu Wu, Liang Wang and Tieniu Tan
International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2016
Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts [paper]
Qiang Liu, Shu Wu, Liang Wang and Tieniu Tan
AAAI Conference on Artificial Intelligence (AAAI), 2016
COT: Contextual Operating Tensor for Context-aware Recommender Systems [paper]
Qiang Liu, Shu Wu and Liang Wang
AAAI Conference on Artificial Intelligence (AAAI), 2015