Subphenotype Identification for Sepsis-Associated Acute Kidney Injury using Graph Bidirectional Mamba Networks

Haowei Xu, Wentie Liu, Tongyue Shi, Guilan Kong

IEEE Journal of Biomedical and Health Informatics 2025 Journal

We introduce a bidirectional Mamba-based graph learning framework that uncovers clinically meaningful subphenotypes for sepsis-associated acute kidney injury by modeling multimodal EHR dynamics and cross-patient relationships.

Neural Granger Causal Discovery for Derangements in ICU-Acquired Acute Kidney Injury Patients

Haowei Xu, Wentie Liu, Tongyue Shi, Guilan Kong

AMIA Annual Symposium Proceedings 2025 Conference

This work discovers causal pathways driving acute kidney injury in the ICU by pairing neural Granger causality with temporal multimodal measurements, enabling actionable risk stratification for critical care teams.

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SIGRL: Sociologically-Informed Graph Representation Learning for Social Influence Prediction

Haowei Xu, Chao Gao, Xingyu Li, Zhihai Wang

IEEE Transactions on Network Science and Engineering 2025 Journal

SIGRL integrates sociological priors into graph representation learning to model influence propagation with improved fidelity across complex social interaction networks.

Learning Complex Heterogeneous Multimodal Fake News via Social Latent Network Inference

Mingxin Li, Yuchen Zhang, Haowei Xu, Xingyu Li, Chao Gao, Zhihai Wang

AAAI 2025 Conference

The model infers latent social structures that fuse multimodal signals, advancing fake news detection with structured reasoning across text, vision, and interaction cues.

[DOI]

D2: Customizing Two-Stage Graph Neural Networks for Early Rumor Detection through Cascade Diffusion Prediction

Haowei Xu, Chao Gao, Xingyu Li, Zhihai Wang

WSDM 2025 Conference

We design a diffusion-aware dual-stage graph neural network that anticipates rumor spread patterns and flags misinformation during its early cascade evolution across social platforms.

HyperIDP: Customizing Temporal Hypergraph Neural Networks for Multi-Scale Information Diffusion Prediction

Haowei Xu, Chao Gao, Xingyu Li, Zhihai Wang

COLING 2025 Conference

HyperIDP leverages temporal hypergraph neural modeling to capture multi-scale diffusion signals across heterogeneous communities, improving forecasting accuracy for evolving narratives.

RumorMixer: Exploring Echo Chamber Effect and Platform Heterogeneity for Rumor Detection

Haowei Xu, Chao Gao, Xingyu Li, Zhihai Wang

ECML-PKDD 2024 Conference

RumorMixer disentangles echo chambers and cross-platform heterogeneity through a multi-view graph design, enabling robust rumor detection in diverse social media ecosystems.