Daoyuan Wang

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王道远 Ph.D. Candidate
Central South University Email Google Scholar GitHub ORCID

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About

I am a Ph.D. candidate in the School of Computer Science and Engineering at Central South University (中南大学), jointly supervised by Prof. Fei Guo (郭菲教授) and Prof. Cheng Liang (梁成教授).

I received my M.S. degree in Software Engineering from the School of Computer Science and Artificial Intelligence at Shandong Normal University (山东师范大学), under the supervision of Prof. Cheng Liang. My research focuses on bioinformatics and machine learning.

Research Interests

Multi-View ClusteringLearning shared structure from complementary data views.
Incomplete Multi-View LearningRobust learning with missing and heterogeneous observations.
AI for ScienceMachine learning methods for scientific discovery.
BioinformaticsMulti-omics and spatial transcriptomics analysis.

Education

2024–Present

Ph.D. in Computer Science and Engineering
Central South University
Supervisors: Prof. Cheng Liang and Prof. Fei Guo

2021–2024

M.Eng. in Software Engineering
Shandong Normal University
Supervisor: Prof. Cheng Liang

Selected Publications

# Equal contribution · * Corresponding author

  1. Daoyuan Wang, Fengyi Zhou, Wenlan Chen, Cheng Liang*, Fei Guo*. Accurate delineation of cellular niches via integrated spatial transcriptomics and histological imaging with SYMOL. Genome Research, 2026.

  2. Wenlan Chen, Lu Gao, Daoyuan Wang, Fei Guo*, Cheng Liang*. Geometry-Aware Variational Information Maximization for Deep Incomplete Multi-view Clustering. AAAI, 2026.

  3. Lu Gao, Wenlan Chen, Daoyuan Wang, Fei Guo*, Cheng Liang*. Disentangled cross-modal representation learning with enhanced mutual supervision. NeurIPS, 2026

  4. Cheng Liang, Wenchao Zang, Daoyuan Wang*, Fei Guo. High-Order Correlation and Consistency-Aware Multi-View Clustering via Anchor Graph Learning. Neural Networks, 2026.

  5. Cheng Liang, Daoyuan Wang, Fei Guo*, Shichao Zhang*. Incomplete Multi-view Clustering via Robust Representation Learning and Tensor-based Co-regularizations. IEEE TCSVT, 2026.

  6. Xiaoyu Liu#, Daoyuan Wang#, Guanghui Li, Cheng Liang*. Prototype-Calibrated Multimodal Fusion with Relational Consistency for Spatial Domain Identification in Spatial Transcriptomics. IEEE BIBM, 2025.

  7. Daoyuan Wang, Lu Gao, Wenlan Chen, Cheng Liang*, Fei Guo*. Image-enhanced Hybrid Encoding with Reinforced Contrastive Learning for Spatial Domain Identification in Spatial Transcriptomics. IJCAI, 2025.

  8. Juntong Zhu#, Daoyuan Wang#, Siqi Chen, Lili Meng, Yahui Long*, Cheng Liang*. stGNN: Spatially Informed Cell-type Deconvolution Based on Deep Graph Learning and Statistical Modeling. Interdisciplinary Sciences, 2025.

  9. Daoyuan Wang, Lianzhi Wang, Wenlan Chen, Hong Wang, Cheng Liang*. Unsupervised Multi-view Feature Selection Based on Weighted Low-rank Tensor Learning and Its Application in Multi-omics Datasets. EAAI, 2025.

  10. Daoyuan Wang, Fujian Ren, Yuntang Zhuang, Cheng Liang*. Robust High-order Graph Learning for Incomplete Multi-view Clustering. Expert Systems with Applications, 2025.

  11. Cheng Liang, Daoyuan Wang, Huaxiang Zhang, Shichao Zhang*, Fei Guo*. Robust Tensor Subspace Learning for Incomplete Multi-view Clustering. IEEE TKDE, 2024.