My CV

Download My Latest CV (PDF)

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

NEWSemi-Supervised Fake News Detection with Mixture of Experts

NEWRevisiting Graph-Level Anomaly Detection: From Partially to Fully Unsupervised Learning

Contrastive multi-knowledge graph learning for fake news detection

Multiknowledge and LLM-inspired heterogeneous graph neural network for fake news detection

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 graph semi-supervised learning against label noise

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

Heterogeneous subgraph transformer for fake news detection

Knowledge graph enhanced heterogeneous graph neural network 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

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