Hanchen Wang

About Me

I am currently an ARC DECRA Fellow and lecturer at Australian Artificial Intelligence Institute (AAII), University of Technology Sydney. I am also an Adjunct Lecturer at The University of New South Wales and an Associate Investigator of ARC Centre of Excellence for the Mathematical Analysis of Cellular Systems (MACSYS). Before joining UTS, I was a postdoctoral research fellow at Data and Knowledge Research Group at The University of New South Wales, supervised by Prof. Wenjie Zhang. I obtained my Ph.D. degree in Computer Science from the University of Technology Sydney in November 2021, advised by Prof.Ying Zhang and Prof.Lu Qin. I received my bachelor’s degree in Mathematics and Applied Mathematics from Zhejiang University in July 2016. Find out more about me here.

HYDRA: Proactive Android Malware Drift Adaptation via Hierarchical Graph Contrastive Learning

May 20, 2026

🎉 One paper accepted by ACM CCS 2026

We have one paper, titled "HYDRA: Proactive Android Malware Drift Adaptation via Hierarchical Graph Contrastive Learning", accepted by ACM CCS 2026. Congrats to Han.

May 20, 2026

🎉 Agentic AI Survey & ICDE 2026 Tutorial

We released a comprehensive survey "Data in Agentic AI" and a corresponding ICDE 2026 tutorial "Data-Centric Foundations of Agentic AI". Congrats to Yuxin.

May 15, 2026

Towards Generative Graph Matching for Graph Edit Distance Computation

May 1, 2026

Data-Centric Foundations of Agentic AI

May 1, 2026

🎉 One paper accepted by ICML 2026

We have one paper, titled "Towards Generative Graph Matching for Graph Edit Distance Computation", accepted by ICML 2026. Congrats to Wei.

May 1, 2026

MGDN: A Graph of Graphs Neural Network for Malware Detection

Apr 30, 2026

Data in Agentic AI: A Comprehensive Survey

Apr 1, 2026

🎉 One paper accepted by TKDE 2026

We have one paper, titled "MGDN: A Graph of Graphs Neural Network for Malware Detection", accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE) 2026.

Apr 1, 2026

Accelerating K-Core Computation in Temporal Graphs

Mar 1, 2026

Small Shifts, Large Gains: Unlocking Traditional TSP Heuristic Guided-Sampling via Unsupervised Neural Instance Modification

Feb 1, 2026

RLMiner: Finding the Most Frequent k-sized Subgraph via Reinforcement Learning

Jan 1, 2026

Finding critical users in social networks with reinforcement learning

Jan 1, 2026

🎉 One paper accepted by EDBT 2026

We have one paper, titled "Accelerating K-Core Computation in Temporal Graphs", accepted by EDBT 2026. Congrats to Zhuo.

Dec 1, 2025

🎉 One paper accepted by Information Sciences

We have one paper, titled "Finding critical users in social networks with reinforcement learning", accepted by Information Sciences. Congrats to Xulu.

Nov 1, 2025

Give Me Some SALT: Structure-Aware Link Modeling for Temporal Weighted Link Prediction

Oct 1, 2025

🎉 One paper accepted by NeurIPS 2025

We have one paper, titled "Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN", accepted by NeurIPS 2025. Congrats to Wei.

Sep 20, 2025

Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN

Sep 19, 2025

Machine Learning for Graph Data Management and Query Processing

*International Conference on Very Large Data Bases (VLDB) 2025 (Tutorial)*

Sep 4, 2025

🎉 One paper accepted by CIKM 2025

We have one paper, titled "Give Me Some SALT Structure-Aware Link Modeling for Temporal Weighted Link Prediction", accepted by CIKM 2025. Congrats to Ting.

Aug 6, 2025

Efficient and Accurate Subgraph Counting: A Bottom-up Flow-learning based Approach

Aug 1, 2025

🎉 VLDB Tutorial

We have one tutorial, titled "Machine Learning for Graph Data Management and Query Processing", accepted by VLDB 2025. I will be the presenter. See you in London.

Jun 30, 2025

Structure and Position-Aware Graph Modeling for Trajectory Similarity Computation Over Road Networks

May 1, 2025

Predicting Membrane Fouling of Submerged Membrane Bioreactor Wastewater Treatment Plants Using Machine Learning

Mar 5, 2025

AIGC for Graphs: Current Techniques and Future Trends

*IEEE International Conference on Data Engineering (**ICDE**) 2025 (Tutorial)*

Mar 4, 2025

DiffGED: Computing Graph Edit Distance via Diffusion-based Graph Matching

Mar 1, 2025

Covering K-Cliques in Billion-Scale Graphs

Mar 1, 2025

🎉 One paper accepted by VLDB 2025

We have one paper, titled "Efficient and Accurate Subgraph Counting: A Bottom-up Flow-learning based Approach", accepted by VLDB 2025. Congrats to Qiuyu.

Mar 1, 2025

AI-Empowered Catalyst Discovery: A Survey from Classical Machine Learning Approaches to Large Language Models

Feb 1, 2025

🎉 New Position at UTS

I joined the Data Intelligence Lab at AAII, UTS as an ARC DECRA Fellow and lecturer (Continuing position).

Jan 15, 2025

RIDA: a robust attack framework on incomplete graphs

Jan 1, 2025

Inferring gene regulatory networks by hypergraph generative model

Jan 1, 2025

🎉 One paper accepted by ICDE 2025

We have one paper, titled "Structure and Position-Aware Graph Modeling for Trajectory Similarity Computation Over Road Networks", accepted by ICDE 2025. Congrats to Peilun.

Dec 15, 2024

Temporal Insights for Group-Based Fraud Detection on e-Commerce Platforms

Oct 1, 2024

Bridging Large Language Models and Graph Structure Learning Models for Robust Representation Learning

Oct 1, 2024

Deep Learning Approaches for Similarity Computation: A Survey

*IEEE Transactions on Knowledge and Data Engineering (**TKDE**) 2024*

Jul 3, 2024

Bipartite Graph Analytics: Current Techniques and Future Trends

*IEEE 40th International Conference on Data Engineering (**ICDE '24**)*

May 13, 2024

Simple and Deep Graph Attention Networks