Publications

🌟 Selected Publications

Highlighting key contributions across my research areas

Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey
Zhiqiang Zhong, Anastasia Barkova, Davide Mottin
CSUR 2025 · [Paper] [GitHub Project Page]
Read-Only Zero-Shot Classifier Expansion from Pairwise Semantics
Zhiqiang Zhong, Jun Pang
NeurIPS 2026 · [Paper] [Code]

Hierarchical Message-Passing Graph Neural Networks
Zhiqiang Zhong, Cheng-Te Li, Jun Pang
ECML-PKDD 2022 · [Paper] [Code]

Automatic Auxiliary Task Selection and Adaptive Weighting Boost Molecular Property Prediction
Zhiqiang Zhong, Davide Mottin
NeurIPS 2025 · [Paper] [Code]
Automatic Annotation Augmentation Boosts Translation between Molecules and Natural Language
Zhiqiang Zhong, Simon Sataa-Yu Larsen, Haoyu Guo, Tao Tang, Kuangyu Zhou, Davide Mottin
NAACL 2025 · [Paper] [Code]
Harnessing Large Language Models as Post-hoc Correctors
Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin
ACL 2024 · [Paper] [Code]

Read-Only Zero-Shot Classifier Expansion from Pairwise Semantics
Zhiqiang Zhong, Jun Pang
Annual Conference on Neural Information Processing Systems (NeurIPS) · [Paper] [Code]
What matters in a bridge? Analysing Bridge Networks for Molecular Property Prediction
Pushkar Jajoria, Zhiqiang Zhong, Jesujoba Oluwadara Alabi, Dietrich Klakow
ML4Molecules workshop at Annual Conference on Neural Information Processing Systems (NeurIPS)

Automatic Auxiliary Task Selection and Adaptive Weighting Boost Molecular Property Prediction
Zhiqiang Zhong, Davide Mottin
Annual Conference on Neural Information Processing Systems (NeurIPS) · [Paper] [Code]
“Double vaccinated, 5G boosted!”: Learning Attitudes towards COVID-19 Vaccination from Social Media
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
ACM Transactions on the Web · [Paper]
Automatic Annotation Augmentation Boosts Translation between Molecules and Natural Language
Zhiqiang Zhong, Simon Sataa-Yu Larsen, Haoyu Guo, Tao Tang, Kuangyu Zhou, Davide Mottin
NAACL 2025 · [Paper] [Code]
EVOL3D: A Large-Scale 3D Structure Dataset for Investigating Mutational Effects in Homologous Proteins
Zhiqiang Zhong, Yinghua Yao, Davide Mottin, Jun Pang
AI4X 2025 International Conference · [Paper] [Dataset Page]
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey
Zhiqiang Zhong, Anastasia Barkova, Davide Mottin
ACM Computing Surveys (CSUR) IF 23.8 🏆 · [Paper] [GitHub Project Page]

Harnessing Large Language Models as Post-hoc Correctors
Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin
ACL 2024 · [Paper] [Code]
Exploring Graph Structure Comprehension Ability of Multimodal Large Language Models: Case Studies
Zhiqiang Zhong, Davide Mottin
Learning on Graphs Conference (LoG’24) · [Paper] [Code]
Efficiently Predicting Mutational Effect on Homologous Proteins by Evolution Encoding
Zhiqiang Zhong, Davide Mottin
ECML-PKDD 2024 · [Paper] [Code]
Hierarchical Bipartite Graph Convolutional Network for Recommendation
Yi Wei Cheng, Zhiqiang Zhong, Jun Pang, Cheng-Te Li
IEEE Computational Intelligence Magazine (CIM) · [Paper]
Bridging Performance of X (formerly known as Twitter) Users: A Predictor of Subjective Well-Being During the Pandemic
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
ACM Transactions on the Web · [Paper] [Code]
A tale of two roles: exploring topic-specific susceptibility and influence in cascade prediction
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
Data Mining and Knowledge Discovery (DMKD) - Journal Track of ECML-PKDD · [Paper]
Benchmarking Large Language Models for Molecule Prediction Tasks
Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin
arXiv Preprint · [Paper] [Code]

On the Robustness of Post-hoc GNN Explainers to Label Noise
Zhiqiang Zhong, Yangqianzi Jiang, Davide Mottin
Learning on Graphs Conference (LoG’23) · [Paper] [Code]
How Faithful are Self-Explainable GNNs?
Marc Christiansen*, Lea Villadsen*, Zhiqiang Zhong, Stefano Teso, Davide Mottin
Learning on Graphs Conference (LoG’23) · [Paper] [Code]
Knowledge-augmented Graph Machine Learning for Drug Discovery: From Precision to Interpretability
Zhiqiang Zhong, Davide Mottin
KDD 2023 (Tutorial) · [Paper] [Web Page]
Multi-grained Semantics-aware Graph Neural Networks
Zhiqiang Zhong, Cheng-Te Li, Jun Pang
IEEE Transactions on Knowledge and Data Engineering (TKDE) · [Paper] [Code]

Hierarchical Message-Passing Graph Neural Networks
Zhiqiang Zhong, Cheng-Te Li, Jun Pang
Data Mining and Knowledge Discovery (DMKD) - Journal Track of ECML-PKDD · [Paper] [Code]
Unsupervised Network Embedding Beyond Homophily
Zhiqiang Zhong, Guadalupe Gonzalez, Daniele Grattarola, Jun Pang
Transactions on Machine Learning Research (TMLR) · [Paper] [Code]
Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation
Zhiqiang Zhong, Sergey Ivanov, Jun Pang
Transactions on Machine Learning Research (TMLR) · [Paper] [Code]
Personalised Meta-path Generation for Heterogeneous Graph Neural Networks
Zhiqiang Zhong, Cheng-Te Li, Jun Pang
Data Mining and Knowledge Discovery (DMKD) - Journal Track of ECML-PKDD · [Paper] [Code]
Exploring Spillover Effects for COVID-19 Cascade Prediction
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
Journal of Entropy · [Paper]
The Burden of Being a Bridge: Analysing Subjective Well-Being of Twitter Users during the COVID-19 Pandemic
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
ECML-PKDD 2022 · [Paper]

From #Jobsearch to #Mask: Improving COVID-19 Cascade Prediction with Spillover Effects
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang
ASONAM 2021 · [Paper]
An Exploratory Study of COVID-19 Information on Twitter in the Greater Region
Ninghan Chen, Zhiqiang Zhong, Jun Pang
Journal of Big Data and Cognitive Computing · [Paper]

NeuLP: An End-to-end Deep-learning Model for Link Prediction
Zhiqiang Zhong, Yang Zhang, Jun Pang
WISE 2020 · [Paper] [Code]

A Graph-based Approach to Explore Relationship between Hashtags and Images
Zhiqiang Zhong, Yang Zhang, Jun Pang
WISE 2019 · [Paper]

Last updated: September 2026 ✨