Kay’s Homepage

Bio

I am a second year Computer Science Ph.D. student in Big Data and Social Computing (BDSC) Lab at University of Illinois Chicago. My advisor is Prof. Philip S. Yu. Before joining UIC, I received my bachelor degree from Beijing University of Posts and Telecommunications and Queen Mary University of London in 2021. I also interned in Walmart Global Tech in summer 2022, and AWS Shanghai AI Lab DGL team in summer 2021. My research interests are Graph Mining, Anomaly Detection, and Fraud Detection. I am actively looking for an Applied Scientist internship in graph mining, anomaly detection, and fraud detection for summer 2023. More information about me can be found in my Curriculum Vitae.

BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs.
Kay Liu, Yingtong Dou, Yue Zhao et al.
NeurIPS. 2022.
[Paper][Code][Data][Slides]
PyGOD: A Python Library for Graph Outlier Detection.
Kay Liu, Yingtong Dou, Yue Zhao et al.
arXiv preprint. 2022.
[Paper][Code]
Network Schema Preserving Heterogeneous Information Network Embedding.
Jianan Zhao, Xiao Wang, Chuan Shi, Zekuan Liu, Yanfang Ye.
IJCAI. 2020.
[Paper][Code]

Graph Neural Network based Fraud Detection: from Research to Application at Wells Fargo
Graph Neural Network based Anomaly Detection: from Research to Application at BUAA
Graph Neural Network based Anomaly Detection: from Research to Application at Novartis
Leveraging GNNs for Financial Fraud Detection: Practices and Challenges at KDD 2022