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.

🎉 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

🎉 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

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

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

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

*Knowledge-Based Systems 2024*

Mar 19, 2024

STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model

*Arxiv*

Mar 18, 2024

Influence Maximization on Hypergraphs via Multi-Hop Influence Estimation

*Information Processing and Management 2024*

Jan 16, 2024

TIformer: A Transformer-Based Framework for Time-Series Forecasting with Missing Data

Jan 1, 2024

GQ*: Towards Generalizable Deep Q-Learning for Steiner Tree in Graphs

Jan 1, 2024

FPGN: follower prediction framework for infectious disease prevention

*World Wide Web 2023*

Sep 16, 2023

Group-based Fraud Detection Network on e-Commerce Platforms

*29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (**KDD '23**)*

Aug 4, 2023

Denoising Variational Graph of Graphs Auto-Encoder for Predicting Structured Entity Interactions

*IEEE Transactions on Knowledge and Data Engineering (**TKDE**) 2023*

Jul 24, 2023

Neural Similarity Search on Supergraph Containment

*IEEE Transactions on Knowledge and Data Engineering (**TKDE**) 2023*

May 25, 2023

TMN: Trajectory Matching Networks for Learning Similarity Computation

*IEEE 38th International Conference on Data Engineering (**ICDE '22**)*

Mar 25, 2022

Neural Subgraph Counting with Wasserstein Estimator

*ACM Special Interest Group in Management Of Data 2022 (**SIGMOD '22**)*

Mar 8, 2022

Reinforcement Learning Based Query Vertex Ordering Model for Subgraph Matching

*IEEE 38th International Conference on Data Engineering (**ICDE '22**)*

Jan 18, 2022

Polarity-based Graph Neural Network for Sign Prediction in Signed Bipartite Graphs

*World Wide Web 2022*

Jan 12, 2022

Bipartite Graph Capsule Network

*World Wide Web 2022*

Jan 11, 2022

Powerful Graph of Graphs Neural Network for Structured Entity Analysis

*World Wide Web 2021*

Jun 4, 2021

Binarized Graph Neural Network

*World Wide Web 2021*

Apr 8, 2021

T3S: Effective Representation Learning for Trajectory Similarity Computation

*IEEE 37th International Conference on Data Engineering (**ICDE '21**)*

Jan 18, 2021

EI-LSH: An early-termination driven I/O efficient incremental c-approximate nearest neighbor search

*The VLDB Journal 2020 (**VLDBJ**)*

Sep 30, 2020

GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions

*Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (**IJCAI '20**)*

Apr 6, 2020

I/O Efficient Algorithm for c-Approximate Furthest Neighbor Search in High-Dimensional Space

*Database Systems for Advanced Applications (**DASFAA-2020**)*

Apr 1, 2020

Skyline Nearest Neighbor Search on Multi-layer Graphs

*IEEE 35th International Conference on Data Engineering Workshops (**ICDEW-2019**)*

Apr 20, 2019

I-LSH: I/O Efficient c-Approximate Nearest Neighbor Search in High-Dimensional Space

*IEEE 35th International Conference on Data Engineering (**ICDE-2019**)*

Apr 6, 2019