My CV

Education

• Doctor of Philosophy, Computing, Macquarie University, 2021.10 - Now.
• Master of Research, Computing, Macquarie University, 2020.01 - 2021.02.
• Master of Information Technology, Computing, University of Melbourne, 2014.02 - 2014.12.
• Bachelor of Software Engineering, Software Engineering, Tianjin University, 2006.09-2010.07.

Work experience

• Oracle, Australia
  • Senior Applied Scientist
  • LLM, Agents, NL2SQL, Agentic AI Assistants
  • Time: 2024.12 - Now.
• Amazon, International Machine Learning
  • Applied Scientist Intern
  • Recommender System, Sequential Recommendation
  • Time: 2024.04 - 2024.10
• Macquarie University, Data Horizons Research Centre
  • Research Assistant
  • Time: 2023.04 - 2023.12
• GenieUS Genomics
  • Research ARP.Intern
  • Genomic Pattern Recognition
  • Time: 2023.06 - 2023.10
• Data Centre of Ningxia
  • Senior Staff Member
  • Time: 2018.10 - 2019.12
• Information and Data Management Center of HRSS Ningxia
  • Senior Staff Member
  • Time: 2015.05 - 2018.10
• Ericsson (China) Communications Co.Ltd.
  • Integration Engineer
  • Time: 2010.07 - 2013.09

Awards

• Executive Dean’s Commendation for Academic Excellence in Year 2 Master of Research
  • 2021
• The Third Place (Silver Modal) in the Second Network Hacking Competition in Ningxia
  • 2018
• Award of Encouragement in the First Network Hacking Competition in Ningxia
  • 2017
• 2016’s Best Staff in Human Resources and Social Security Department of Ningxia Hui Autonomous Region
  • 2016
• Bronze Model in the Tianjin Metropolitan Collegiate Programming Contest
  • 2007

Hosted Projects

• Awesome Deep Graph Anomaly Detection REPO

Publications

Rethinking Unsupervised Graph Anomaly Detection with Deep Learning: Residuals and Objectives

On Fake News Detection with LLM Enhanced Semantics Mining

Divide and Denoise: Empowering Simple Models for Robust Semi-Supervised Node Classification against Label Noise

Graph Anomaly Detection with Few Labels: A Data-Centric Approach

Heterogeneous Subgraph Transformer for Fake News Detection

Towards Graph-level Anomaly Detection via Deep Evolutionary Mapping

Heterogeneous Graph Neural Network via Knowledge Relations for Fake News Detection

Heterogeneous Hypergraph Neural Network for Social Recommendation using Attention Network

Knowledge Graph Enhanced Heterogeneous Graph Neural Network for Fake News Detection

DAGAD: Data Augmentation for Graph Anomaly Detection

Deep Multi-Attributed-View Graph Representation Learning

A Comprehensive Survey on Graph Anomaly Detection with Deep Learning

Application of Mobile Games to Support Clinical Data Collection for Patients with Niemann-Pick Disease

Service and Research Activities

• Journal Reviewer
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Transactions on Knowledge and Data Engineering
  • ACM Transactions on Knowledge Discovery from Data
  • World Wide Web Journal
  • IEEE Transactions on Emerging Topics in Computing
  • IEEE Transactions on Neural Computing
  • Journal of Information Science
• Conference Reviewer
  • The ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD) 2025
  • The ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD) 2024
  • The IEEE International Conference on Data Mining (ICDM) 2021
  • The ACM Conference on Web Search and Data Mining (WSDM) 2021
  • The Conference on Information and Knowledge Management (CIKM) 2021
  • The IEEE International Conference on Big Knowledge (ICBK) 2021
  • International Joint Conference on Neural Networks (IJCNN) 2021, 2022
  • The ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD) 2021