Qiang Gao (高强)
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Contact:
NiceLab, Jingshi Building
Liutai Avenue, Wenjiang
Chengdu, Sichuan, CHINA, 611130
[中文页面]
Email: qianggao AT swufe DOT edu DOT cn
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Biography
I am currently an Associate Professor, PhD supervisor at the Complex Laboratory of New Finance and Economics (NiceLab) and School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics (SWUFE).
I (supervised by Prof. Fengli Zhang and Prof. Fan Zhou) received the Ph.D. degree in Software Engineering from University of Electronic Science and Technology of China (UESTC), Chengdu, China.
I was a visiting scholar, supervised by Prof. Diego Klabjan and Prof. Goce Trajchevski, at Northwestern University from 2019 to 2020.
My research focuses on Deep Learning+Mobility Mining (e.g., spatio-temporal data processing and location-based services (LBS)). Additionally, I am also partly interested in Regional/Urban Economics.
Github:
Goole Scholar:
I am looking for motivated MSc, PhD, and Postdoc to join my research group, please feel free to contact me if you are interested in my research area.
Funds
Selected Publications (*Corresponding Author)
Journal Papers
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Qiang Gao, Jinyu Hong, Xovee Xu, Ping Kuang, Fan Zhou, and Goce Trajcevski. "Predicting Human Mobility via Self-supervised Disentanglement Learning", IEEE Transactions on Knowledge and Data Engineering, 2023. [Paper].
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Xovee Xu, Zhiyuan Wang, Qiang Gao Ting Zhong, Bei Hui, Fan Zhou, and Goce Trajcevski. "Spatial-Temporal Contrasting for Fine-Grained Urban Flow Inference", IEEE Transactions on Big Data, 2023. [Paper]
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Qiang Gao, Hongzhu Fu, Kunpeng Zhang, Goce Trajcevski, Xu Teng, and Fan Zhou. "Inferring Real Mobility in Presence of Fake Check-ins Data", ACM Transactions on Intelligent Systems and Technology, 2023. [Paper].
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Xin Yang, Metoh Adler LOUA, Meijun Wu, Li Huang, Qiang Gao. "Multi-granularity Stock Prediction with Sequential Three-way Decisions", Information Sciences, 2023. [Paper]
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Qiang Gao, Wei Wang, Li Huang, Xin Yang, Tianrui Li and Hamido Fujita. "Dual-grained Human Mobility Learning for Location-aware Trip Recommendation with Spatial-temporal Graph Knowledge Fusion", Information Fusion, 2023. [Paper]
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Qiang Gao, Fan Zhou, Xin Yang and Guisong Liu. "When Friendship Meets Sequential Human Check-ins: Inferring Social Circles with Variational Mobility", Neurocomputing, 2023. [Paper]
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Qiang Gao, Fan Zhou, Ting Zhong, Goce Trajcevski, Xin Yang and Tianrui Li. "Contextual Spatio-Temporal Graph Representation Learning for Reinforced Human Mobility Mining", Information Sciences, 2022. [Paper]
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Qiang Gao, Wei Wang, Kunpeng Zhang, Xin Yang, Congcong Miao and Tianrui Li. "Self-supervised Representation Learning for Trip Recommendation", Knowledge-Based Systems, 2022. [Paper]
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Qiang Gao, Zhipeng Luo, Diego Klabjan and Fengli Zhang. "Efficient Architecture Search for Continual Learning", IEEE Transactions on Neural Networks and Learning Systems, 2022. [Paper]
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Fan Zhou, Yurou Dai, Qiang Gao, Pengyu Wang, and Ting Zhong. "Self-Supervised Human Mobility Learning for Next Location Prediction and Trajectory Classification", Knowledge-Based Systems, 2021. [Paper]
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Qiang Gao, Fan Zhou, Goce Trajcevski, Kunpeng Zhang, Ting Zhong and Fengli Zhang. "Adversarial Human Trajectory Learning for Trip Recommendation", IEEE Transactions on Neural Networks and Learning Systems, 2021. [Paper]
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Qiang Gao, Fengli Zhang, Fuming Yao, Ailing Li, Lin Mei and Fan Zhou. "Adversarial Mobility Learning for Human Trajectory Classification", IEEE Access, 2020. [Paper]
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高强, 张凤荔, 王瑞锦, & 周帆. (2017). 轨迹大数据: 数据处理关键技术研究综述. 软件学报, 28(4), 959-992. [Paper]
Conference Papers
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Kai Yang, Yi Yang, Qiang Gao, Ting Zhong, Yong Wang, and Fan Zhou. "Self-Explainable Next POI Recommendation", The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024). (Accepted)
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Jinyu Hong, Ping Kuang, Qiang Gao*, Fan Zhou. "Disentanglement-Guided Spatial-Temporal Graph Neural Network for Metro Flow Forecasting (Student Abstract)", The Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024). [Paper]
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Hongzhu Fu, Fan Zhou, Qing Guo, Qiang Gao*. "Spatial-Temporal Augmentation for Crime Prediction (Student Abstract)", The Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024). [Paper]
- Qiang Gao, Xiaojun Shan, Yuchen Zhang, and Fan Zhou. "Enhancing Knowledge Transfer for Task Incremental Learning with Data-free Subnetwork", Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023). [Paper]
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Qiang Gao, Xiaohan Wang, Chaoran Liu, Goce Trajcevski, Li Huang, Fan Zhou. "Open Anomalous Trajectory Recognition via Probabilistic Metric Learning", The 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023). [Paper]
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Qiang Gao, Hongzhu Fu, Yutao Wei, Li Huang, Xingmin Liu, and Guisong Liu. "Spatial-Temporal Diffusion Probabilistic Learning for Crime Prediction", The 16th International Conference on Knowledge Science, Engineering and Management (KSEM 2023). [Paper]
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Li Huang, Kai Liu, Chaoran Liu, Qiang Gao*, Xiao Zhou, and Guisong Liu "HBay: Predicting Human Mobility via Hyperspherical Bayesian Learning", The 16th International Conference on Knowledge Science, Engineering and Management (KSEM 2023). [Paper] (Best Paper Award)
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Li Huang, Hongmei Wu, Qiang Gao*, Guisong Liu. "ATTENTION LOCALNESS IN SHARED ENCODER-DECODER MODEL FOR TEXT SUMMARIZATION", 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023). [Paper]
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Miaomiao Li, Jiaqi Zhu, Xin Yang, Yi Yang, Qiang Gao, Hongan Wang. "CL-WSTC: Continual Learning for Weakly Supervised Text Classification on the Internet", The 2023 ACM Web Conference, (WWW 2023). [Paper]
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Jinyu Hong, Fan Zhou, Qiang Gao*, Kuang Ping, Kunpeng Zhang. "Mobility Prediction via Sequential Trajectory Disentanglement (Student Abstract)", The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023). [Paper]
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Yujie Li, Yuxuan Yang, Qiang Gao*, Xin Yang. "Cross-regional Fraud Detection via Continual Learning (Student Abstract)", The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023). [Paper]
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Joojo Walker, Ting Zhong, Fengli Zhang, Qiang Gao and Fan Zhou. "Recommendation via Collaborative Diffusion Generative Model", The 15th International Conference on Knowledge Science, Engineering and Management (KSEM 2022). [Paper]
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Fan Zhou, Rongfan Li, Qiang Gao, Goce Trajcevski, Kunpeng Zhang, Ting Zhong. "Dynamic Manifold Learning for Land Deformation Forecasting", Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI),2022. [Paper]
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Qiang Gao, Fan Zhou, Goce Trajcevski, Fengli Zhang, Xucheng Luo. "Adversity-based Social Circles Inference via Context-Aware Mobility", 2020 IEEE Global Communications Conference. [Paper]
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Qiang Gao, Goce Trajcevski, Fan Zhou, Kunpeng Zhang, Ting Zhong, and Fengli Zhang. "DeepTrip: Adversarially Understanding Human Mobility for Trip Recommendation". Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2019). [Paper]
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Qiang Gao, Fan Zhou, Goce Trajcevski, Kunpeng Zhang, Ting Zhong and Fengli Zhang, "Predicting Human mobility via Variational Attention", The World Wide Web Conference (WWW 2019). [Paper][Code]
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Qiang Gao, Goce Trajcevski, Fan Zhou, Kunpeng Zhang, Ting Zhong and Fengli Zhang, "Trajectory-based Social Circle Inference", Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2018). [Paper][Code]
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Fan Zhou, Qiang Gao, Goce Trajcevski, Kunpeng Zhang, Ting Zhong, Fengli Zhang, "Trajectory-User Linking via Variational AutoEncoder", IJCAI 2018. [Paper]
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Qiang Gao, Fan Zhou, Kunpeng Zhang, Goce Trajcevski, Xuecheng Luo, Fengli Zhang, "Identifying Human Mobility via Trajectory Embeddings", IJCAI 2017. [Paper][Code]
Activities & Services
Conference & Journal Organization:
- Program Committee Member, MDM 2023/2024
- Program Committee Member, KSEM 2022/2023
- Program Committee Member, SISAP 2023/2024
- Program Committee Member, ACM SIGSPATIAL 2021-2023
- Program Committee Member, EAI CollaborateCom 2020
- etc.
Reviewing for:
- IEEE Transactions on Knowledge and Data Engineering
- IEEE Transactions on Neural Networks and Learning Systems
- IEEE Transactions on Systems Man Cybernetics-Systems
- IEEE Transactions on Intelligent Transportation Systems
- ACM Transactions on Knowledge Discovery from Data
- Human-Centric Intelligent Systems
- KDD (2018-2021/2024)
- ICME (2024)
- IEEE BigData (2019-2022)
- EAI CollaborateCom (2021)
- Scientific Reports
- GeoInformatica
- ACM Transactions on Asian and Low-Resource Language Information Processing
- ACM Transactions on Spatial Algorithms and Systems
- ISPRS International Journal of Geo-Information
- etc.
Teaching:
Current Courses:
Training Program of Artificial Intelligence for Undergraduates, Spring 2024
Previous Courses:
Advanced Machine Learning for Undergraduates, Fall 2022/2023
Training Program of Artificial Intelligence for Undergraduates, Fall 2022/2023
Machine Learning for Undergraduates, Spring 2022/2023
Artificial Intelligence for PhD students, Fall 2021
Data Mining for Undergraduates, Spring 2021, Fall 2021/2022
Update Time: Jan. 10, 2024
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