Qiang Gao

Qiang Gao 

Contact:

Room J310-1, Gezhi Building
Liutai Avenue, Wenjiang
Chengdu, Sichuan, CHINA, 611130

[中文页面]

Email: qianggao@swufe.edu.cn

Biography

Dr. Qiang Gao is currently working as the lecturer at the Department of Artificial Intelligence, School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics (西南财经大学, SWUFE) since March 2021. He (supervised by Prof. Fengli Zhang and Prof. Fan Zhou) received the Ph.D. degree in the Software Engineering from University of Electronic Science and Technology of China (电子科技大学, UESTC), Chengdu, Sichuan, China. He 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)), Recommendation System, Data Mining. Specifically, I am also interested in Fintech and Data Security.

Github: Goole Scholar:

I am looking for motivated students to join my research group, please feel free to contact me if you are interested in my research area.

Funds

Selected Publications (*Corresponding Author)

Preprints

  • Qiang Gao, Jinyu Hong, Xovee Xu, Ping Kuang, Fan Zhou, and Goce Trajcevski. "Predicting Human Mobility via Self-supervised Disentanglement Learning", arXiv preprint arXiv:2211.09625, 2022. [Paper]
  • Qiang Gao, Xinzhu Zhou, Kunpeng Zhang, Li Huang, Siyuan Liu, and Fan Zhou. "Incorporating Interactive Facts for Stock Selection via Neural Recursive ODEs", arXiv preprint arXiv:2210.15925, 2022. [Paper]
  • Yujie Li, Yuxuan Yang, Xin Yang, Qiang Gao*, Fan Zhou. "Forgetting Prevention for Cross-regional Fraud Detection with Heterogeneous Trade Graph", arXiv preprint arXiv:2204.10085, 2022. [Paper]

Journal Papers

  • Xin Yang, Metoh Adler LOUA, Meijun Wu, Li Huang, Qiang Gao. "Multi-granularity Stock Prediction with Sequential Three-way Decisions", Knowledge-Based Systems,2022. (Accepted )
  • 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,2022. (Accepted )
  • Qiang Gao, Fan Zhou, Xin Yang and Guisong Liu. "When Friendship Meets Sequential Human Check-ins: Inferring Social Circles with Variational Mobility", Neurocomputing, 2022. [Paper]
  • 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]
  • 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]
  • 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]
  • 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]
  • 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]
  • Qiang Gao, Fengli Zhang, Fuming Yao, Ailing Li, Lin Mei and Fan Zhou. "Adversarial Mobility Learning for Human Trajectory Classification", IEEE Access, 2020. [Paper]
  • 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. (中文CCF A类,软件学报高影响力文章)[Paper]

Conference Papers

  • 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). (Accepted )
  • 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). (Accepted )
  • 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). (Accepted )
  • 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]
  • 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]
  • 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]
  • 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). (CCF A) [Paper][Code ]
  • 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]
  • Fan Zhou*, Qiang Gao, Goce Trajcevski, Kunpeng Zhang, Ting Zhong, Fengli Zhang, "Trajectory-User Linking via Variational AutoEncoder", IJCAI 2018. (CCF A)[Paper]
  • Qiang Gao, Fan Zhou, Kunpeng Zhang, Goce Trajcevski, Xuecheng Luo, Fengli Zhang, "Identifying Human Mobility via Trajectory Embeddings", IJCAI 2017.(CCF A)[Paper][Code]

Activities & Services

Conference & Journal Organization:

  • Program Committee Member, MDM 2023
  • Program Committee Member, KSEM 2022
  • Program Committee Member, ACM SIGSPATIAL 2021/2022
  • Program Committee Member, EAI CollaborateCom 2020

Reviewing for:

  • IEEE Transactions on Knowledge and Data Engineering
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Systems Man Cybernetics-Systems
  • Human-Centric Intelligent Systems
  • KDD (2018-2021)
  • 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
  • IEEE Access

Honors:

  • 2021: Outstanding Doctoral Thesis Award of ACM Chengdu chapter
  • 2021: Outstanding Graduate Student of Sichuan Province
  • 2021: Outstanding Graduate Student of UESTC
  • 2019: Travel Scholarship of NSF
  • 2017: National Scholarship
  • 2017: National Cyber Security Scholarship
  • 2017: Outstanding Chairman of Student Branch of China Computer Society (CCF)

Teaching:

Current Courses:

  • Jingshi Building D402: Advanced Machine Learning for Undergraduates, Fall 2022
  • Jingshi Building C204: Data Mining for Undergraduates, Fall 2022
  • New Finance Complex Lab: Training Program of Artificial Intelligence for Undergraduates, Fall 2022
  • Previous Courses:

  • Jingshi Building E301: Machine Learning for Undergraduates, Spring 2022
  • Tongbo Building 201: Artificial Intelligence for PhD students, Fall 2021
  • Yide Building I101,I104: Data Mining for Undergraduates, Fall 2021
  • Jingshi Building B407: Data Mining for Undergraduates, Spring 2021

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