• 161 Citations
  • 8 h-Index
20152020

Research output per year

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Personal profile

Biography

My research topic is artificial intelligence, specializing in recommender systems. I mainly focus on applying data mining and machine learning techniques (e.g., deep learning, reinforcement learning) to design effective algorithms to enhance the performance of recommender systems in various domains, such as e-commerce, social networks, location-based social networks (LBSNs), multi-media, smart learning and so forth. Specifically, I am interested in leveraging side information (e.g., item categories, knowledge graphs) to address data sparsity and cold start problems of recommender systems. 

Research interests

  • Recommender Systems
  • User Modeling
  • Social Network Analysis
  • Machine Learning (Deep Learning, Reinforcement Learning)
  • Data Mining

Education/Academic qualification

Computer Science and Engineering, Ph.D., Nanyang Technological University

4 Aug 20141 Jul 2018

Computer Science and Engineering, Master, Yanshan University

1 Sep 20131 Jul 2014

Computer Science and Engineering, Bachelor, Yanshan University

1 Sep 20091 Jul 2013

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Research Outputs

  • 161 Citations
  • 8 h-Index
  • 14 Conference proceeding contribution
  • 5 Article
  • 2 Conference abstract
  • 1 Conference paper

Minimalistic attacks: how little it takes to fool deep reinforcement learning policies

Qu, X., Sun, Z., Ong, Y. S., Gupta, A. & Wei, P., 19 Feb 2020, In : IEEE Transactions on Cognitive and Developmental Systems.

Research output: Contribution to journalArticle

  • Modeling hierarchical category transition for next POI recommendation with uncertain check-ins

    Zhang, L., Sun, Z., Zhang, J., Kloeden, H. & Klanner, F., Apr 2020, In : Information Sciences. 515, p. 169-190 22 p.

    Research output: Contribution to journalArticle

  • Exploiting side information for recommendation

    Guo, Q., Sun, Z. & Theng, Y. L., 1 Jan 2019, Web Engineering: 19th International Conference, ICWE 2019, Proceedings. Bakaev, M., Frasincar, F. & Ko, I-Y. (eds.). Switzerland: Springer-VDI-Verlag GmbH & Co. KG, p. 569-573 5 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11496 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

  • 1 Citation (Scopus)

    Modeling heterogeneous influences for point-of-interest recommendation in location-based social networks

    Guo, Q., Sun, Z., Zhang, J. & Theng, Y-L., 2019, Web Engineering: 19th International Conference, ICWE 2019, Proceedings. Bakaev, M., Frasincar, F. & Ko, I-Y. (eds.). Switzerland: Springer, p. 72-80 9 p. (Lecture Notes in Computer Science; vol. 11496).

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

  • Multi-facet user preference learning for fine-grained item recommendation

    Zhou, X., Guo, G., Sun, Z. & Liu, Y., 26 Dec 2019, In : Neurocomputing. 385, p. 258-268 11 p.

    Research output: Contribution to journalArticle

  • Activities

    • 15 Membership of committee
    • 5 Publication Peer-review
    • 1 Visiting an external academic institution

    29th International Joint Conference on Artificial Intelligence, IJCAI 2020 (Event)

    Zhu Sun (Member)
    2020

    Activity: MembershipMembership of committee

    Journal of Web Engineering (Journal)

    Zhu Sun (Reviewer)
    2020

    Activity: Publication peer-review and editorial workPublication Peer-review

    Neurocomputing (Journal)

    Zhu Sun (Reviewer)
    2020

    Activity: Publication peer-review and editorial workPublication Peer-review

    25th International Conference on Intelligent User Interfaces, IUI 2020 (Event)

    Zhu Sun (Member)
    2020

    Activity: MembershipMembership of committee