Hey, wassup!

Kaize Ding(丁凯泽)

Ph.D. Student

Data Mining and Machine Learning Laboratory

School of Computing, Informatics, and Decision Systems Engineering

Arizona State University

Email: kaize.ding AT asu DOT edu


About Me

I am a PhD student of Computing Science and Engineering, Arizona State University. I work as a research assistant at Data Mining and Machine Learning Laboratory, advised by Professor Huan Liu.

Before that, I obtained my master and bachelor degrees from Beijing University of Posts and Telecommunications(BUPT).


Research Interests

My research interests generally lie in data mining and machine learning, recently I'm focusing on graph neural networks, and its applications such as anomaly detection, recommendation, etc.


News

[04/2020] One paper got accepted in SIGIR 2020.

[04/2020] One paper got accepted in IJCAI-PRICAI 2020.

[03/2020] Invited to be PC member of IJCAI 2020, ECML-PKDD 2020.

[10/2019] Our paper got accepted in WSDM 2020.


Publications

Preprint Papers:

  1. Feature Interaction-aware Graph Neural Networks [pdf] [bib]
    Kaize Ding, Yichuan Li, Jundong Li, Chenghao Liu and Huan Liu

Conference Papers:

2020:

  1. Next-item Recommendation with Sequential Hypergraphs [pdf] [bib]
    Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu and James Caverlee
    In Proceedings of the ACM International SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020

  2. Inductive Anomaly Detection on Attributed Networks [pdf] [bib]
    Kaize Ding, Jundong Li, Nitin Aagarwal and Huan Liu
    In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2020

  3. Key Opinion Leaders in Recommendation Systems: Opinion Elicitation and Diffusion [pdf] [bib]
    Kaize Ding*, Jianling Wang*, Ziwei Zhu, Yin Zhang and James Caverlee (*equal contribution)
    In Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2020

2019:

  1. InterSpot: Interactive Spammer Detection in Social Media (demo paper) [pdf] [bib]
    Kaize Ding, Jundong Li, Shivam Dhar, Shreyash Devan, and Huan Liu
    In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019

  2. Deep Anomaly Detection on Attributed Networks with Graph Convolutional Networks [pdf] [code]
    Kaize Ding, Jundong Li, Rohit Bhanushali, and Huan Liu
    In Proceedings of the SIAM International Conference on Data Mining (SDM), 2019

  3. Interactive Anomaly Detection on Attributed Networks [pdf] [code]
    Kaize Ding, Jundong Li, and Huan Liu
    In Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2019


Honors and Awards


Services

Program Committee:

IJCAI'20, ECML-PKDD'20

External Reviewer:

KDD'19, WWW'19, SIGIR'18, ASONAM'18


Experiences