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 Economic Information Engineering, 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

Preprints

  • Qiang Gao, Wei Wang, Kunpeng Zhang, Xin yang and Congcong Miao. "Self-supervised Representation Learning for Trip Recommendation", (submitted for publication ), 2021. [Arxiv]
  • Qiang Gao, Zhipeng Luo, Diego Klabjan and Fengli Zhang. "Efficient architecture search for continual learning", (submitted for publication ), 2021. [Arxiv]

Journal Papers

  • 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(Early Access ). [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

  • 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:

  • TPC Member, KSEM 2022
  • Program Committee Member, ACM SIGSPATIAL 2021
  • Program Committee Member, EAI CollaborateCom 2020

Reviewing for:

  • IEEE Transactions on Knowledge and Data Engineering
  • IEEE Transactions on Systems Man Cybernetics-Systems
  • Human-Centric Intelligent Systems
  • KDD (2018-2021)
  • IEEE BigData (2019-2021)
  • EAI CollaborateCom (2021)
  • 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:

  • Tongbo Building 201: Artificial Intelligence for PhD students, Fall 2021
  • Yide Building I101,I104: Data Mining for Undergradutes, Fall 2021
  • Previous Courses:

  • Jingshi Building B407: Data Mining for Undergradutes, Spring 2021
  • Students:

    Master&PhD

  • Yujie Li, 1nd year PhD in Financial Intelligence and Financial Engineering (co-supervised with Prof. Xin Yang)
  • Wei Wang, 2nd year Master in Computer Science (co-supervised with Prof. Xin Yang)
  • Jiani Zheng, 2nd year Master in Business Intelligence (co-supervised with Prof. Xin Yang)
  • Pei Li, 1nd year Master in Computer Science
  • Zhenwu Li, 1nd year Master in Computer Science
  • Undergraduates

  • Hongzhu Fu, 3nd year Undergraduate in Computer Science
  • Yuxiang Li, 3nd year Undergraduate in Economics