科研项目：
面向多组学癌症数据的多视图生存分析算法的研究, 国家自然科学基金项目, 青年基金项目 （2022-2024）， 30 万，主持
基于图分布对齐的多视图学习算法研究及其在不完备多组学癌症数据分析的应用, 广东省自然科 学基金项目面上项目 2025-2028）, 10 万，主持
自适应多任务学习算法研究及其在癌症数据分析中的应用, 广东省自然科学基金项目面上项目 （2022-2024）, 10 万，主持
结构化稀疏模型及其生物数据的应用, 广东省教育厅青年创新人才项目，5 万，主持
基于组学数据方面的智能模型的快速实现应用开发服务， 中国科学技术大学苏州高等研究院， 10 万，主持
基于正则化结构化稀疏模型及其医疗数据应用， 汕头大学卓越人才科研启动基金， 100 万，主持
多网络视角学习增强的微生物和疾病复杂联系预测 (2024-2027) ，50 万元, 国家自然科学基金面 上项目，62372282，第一参与人
基于最优传输和单细胞转录组测序研究肿瘤浸润淋巴细胞的空间异质性 (2023-2025), 30 万，广 东省自然科学基金，青年提升项目，第一参与人
发表的学术论文：一作/通讯/共同通讯发表论文： 15 篇 CCF-A 或中科院一区，10 篇 CCF-B 或中科院二区，2 篇 CCF-C，(IEEE TKDE-2，IEEE TNNLS-3，IEEE TCYB-2，IEEE TCBB-3, IEEE TBME-1, PR-1, ASOC-2, Information Science-1, Neurocomputing-1, KBS-1, Bioinformatics-1, CAIS-1, AAAI-1，IJCAI-1，ACMMM-1，COLING-1, ICME-2, ICONIP-1, IEEE SMC-1); 一篇热点论文（TKDE），一篇高被引 论文（TNNLS）
[IEEE TKDE] Cheng Liu, Rui Li, Hangjun Che, Man-Fai Leung, Si Wu, Zhiwen Yu and Hau-San Wong: Latent Structure-Aware View Recovery for Incomplete Multi-view Clustering. IEEE Transactions on Knowl- edge and Data Engineering. (2024) [JCR Q1] [CCF A] [数据挖掘顶级期刊] [影响因子 8.9]
[IEEE TNNLS] Cheng Liu, Rui Li, Hangjun Che, Man-Fai Leung, Si Wu, Zhiwen Yu and Hau-San Wong: Beyond Euclidean Structures: Collaborative Topological Graph Learning for Multiview Clustering. IEEE Transactions on Neural Networks and Learning Systems. (2024) [JCR Q1] [CCF B] [CAAI-A] [中科院 1 区] [Top 顶刊] [影响因子 10.4]
[IEEE TKDE] Cheng Liu, Si Wu, Rui Li, Dazhi Jiang, Hau-San Wong: Self-Supervised Graph Completion for Incomplete Multi-View Clustering. IEEE Transactions on Knowledge and Data Engineering (2023) [JCR Q1] [CCFA] [数据挖掘顶级期刊] [影响因子 8.9] ESI 热点论文
[IEEE TNNLS] Cheng Liu, Rui Li, Hangjun Che, Si Wu, Dazhi Jiang, Zhiwen Yu and Hau-San Wong: Self-Guided Partial Graph Propagation for Incomplete Multi-View Clustering. IEEE Transactions on Neural Networks and Learning Systems (2023) [CCF B] [CAAI-A] [中科院 1 区] [Top 顶刊] [影响因子 10.4]
[IEEE TNNLS] Cheng Liu, Wenming Cao, Si Wu, Wenjun Shen, Dazhi Jiang, Zhiwen Yu, Hau-San Wong: Asymmetric Graph-Guided Multi-Task Survival Analysis with Self-Paced Learning. IEEE Transactions on Neural Networks and Learning Systems (2022) [CCF B] [CAAI-A] [中科院 1 区] [Top 顶刊] [影响因子 10.4] ESI 高被引论文
[IEEE TCYB] Cheng Liu, Chutao Zheng, Si Wu, Zhiwen Yu, Hau-San Wong: Multi-task feature selection by graph-clustered feature sharing. IEEE Transactions on Cybernetics (2020) [JCR Q1] [CCF B] [CAAI-A] [中科院 1 区] [Top 顶刊] [影响因子 9.4]
[IEEE TBME] Cheng Liu, Si Wu, Dazhi Jiang, Zhiwen Yu, Hau-San Wong: View-Aware Collaborative Learning for Survival Prediction and Subgroup Identification. IEEE Transactions on Biomedical and Engi- neering (2022) [JCR Q1]
[IEEE TCBB] Cheng Liu, Wenming Cao, Si Wu, Wenjun Shen, Dazhi Jiang, Zhiwen Yu, Hau-San Wong: Supervised graph clustering for cancer subtyping based on survival analysis and integration of multi-omic tumor data. IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020) [JCR Q1] [CCF B]
[IEEE TCBB] Cheng Liu, Hau-San Wong: Structured Penalized Logistic Regression for Gene Selection in Gene Expression Data Analysis. IEEE/ACM Transactions on Computational Biology and Bioinformatics (2017) [JCR Q1] [CCF B]
[IEEE TCBB] Hang Gao, Wenjun Shen, and Cheng Liu# and Si Wu: Collaborative Structure-Preserved Missing Data Imputation for Single-Cell RNA-Seq Clustering. IEEE/ACM Transactions on Computational Biology and Bioinformatics (2024) [JCR Q1] [CCF B] (共同通讯作者，指导老师)
[IEEE TCYB] Jian Zhong, Xiangping Zeng, Wenming Cao, Si Wu, Cheng Liu, Zhiwen Yu, Hau-San Wong: Semisupervised Multiple Choice Learning for Ensemble Classification. IEEE Transactions on Cybernetics 2020 [JCR Q1] [CCFB] [CAAI-A] [中科院 1 区] [Top 顶刊] [影响因子 9.4] (共同通讯作者)
[PR] Cheng Liu, Chutao Zheng, Sheng Qian, Si Wu and Hau-San Wong: Encoding Sparse and Competitive Structures among Tasks in Multi-Task Learning. Pattern Recognition (2019) [JCR Q1] [CCF B] [中科院 1 区] [Top 顶刊] [影响因子 7.5]
[KBS] Cheng Liu, Wenming Cao, Si Wu, Wenjun Shen, Dazhi Jiang, Zhiwen Yu, Hau-San Wong: Joint Subspace and Discriminative Learning for Self-Paced Domain Adaptation. Knowledge-Based Systems (2020) [JCR Q1] [CCF C] [中科院 1 区] [Top 顶刊] [影响因子 7.2]
[NEURO] Cheng Liu, Sentao Chen, Lin Zheng, Dazhi Jiang, Si Wu and Hau-San Wong: Adaptive Dual Graph Regularization for Clustered Multi-Task Learning Neurocomputing 2024 [JCR Q1] [CCF C] [影响因子5.5][ASOC] Cheng Liu, Yong Liang, Xin-Ze Luan, Kwong-Sak Leung, Tak-Ming Chan, Zongben Xu, Hai Zhang: The L1/2 regularization method for variable selection in the Cox model. Applied Soft Computing (2014) [JCR Q1] [中科院 1 区] [Top 顶刊] [影响因子 7.5]
[CAIS] Zhen Zheng (Student), Rui Li, and Cheng Liu#: Learning Robust Features Alignment for Cross- Domain Medical Image Analysis. Complex & Intelligent System (2023) [JCR Q1] [影响因子 5.0] (通讯作 者，指导老师)
[Bioinformatics] Xindian Wei, Tianyi Chen, Cheng Liu#, Wenjun Shen, Si Wu, Hau-San Wong#: COME: Constrative Mapping Learning for Spatial Reconstruction of scRNA-seq Data. (2025) [JCR Q2] [CCF-B] (共 同通讯作者)
[ASOC] Sijin Zhou, Dongmin Huang, Cheng Liu#, Dazhi Jiang#: Objectivity meets subjectivity: A subjec- tive and objective feature fused neural network for emotion recognition. Applied Soft Computing. [JCR Q1] [中科院 1 区] [Top 顶刊] [影响因子 7.5] (共同通讯作者，合作指导老师)
[INS] Jiaxin Li, Haohong Zhou, Si Wu#, Cheng Liu#, Hau-San Wong: Collaborative Learning-based Unknown- class Instance Identification for Open-set Domain Adaptation. Information Science (2023). [JCR Q1] [CCF-B] (共同通讯作者，合作指导老师)
[BMC Bioinformatics] Yong Liang (导师), Cheng Liu, Xin-Ze Luan, Kwong-Sak Leung, Tak-Ming Chan, Zongben Xu, Hai Zhang: Sparse logistic regression with an L1/2 penalty for gene selection in cancer classi- fication. BMC Bioinformatics (2013) [CCF-C] [JCR Q2] (硕士论文研究主题)
[IEEE TSIPN] Xuanhao Yang, Hangjun Che, Man-Fai Leung, Cheng Liu, Shiping Wen Auto-weighted Multi-view Deep Non-negative Matrix Factorization with Multi-kernel Learning. IEEE Transactions on Sig- nal and Information Processing over Networks. 2024 [JCR Q1]
[IEEE TIP] Jichang Li, Si Wu, Cheng Liu, Zhiwen Yu, Hau-San Wong: Semi-Supervised Deep CoupledEn- semble Learning With Classification Landmark Exploration. IEEE Transactions on Image Processing (2020) [CCF A] [JCR Q1]
[IEEE TIP] Si Wu, Shufeng Wang, Robert Laganiere, Cheng Liu, Hau-San Wong, Yong Xu: Exploiting Target Data to Learn Deep Convolutional Networks for Scene-Adapted Human Detection. IEEE Transactions on Image Processing (2018) [CCF A] [JCR Q1]
[IEEE TIP] Haohong Zhou, Mohamed Azzam, Jian Zhong, Cheng Liu, Si Wu, Hau-San Wong: Knowledge Exchange Between Domain-Adversarial and Private Networks Improves Open Set Image Classification. IEEE Transactions on Image Processing (2021) [CCF A] [JCR Q1]
[IEEE TKDE] Zhiwen Yu, Zhongfan Zhang, Wenming Cao, Cheng Liu, CL Philip Chen, Hau-San Wong:
GAN-based enhanced deep subspace clustering networks. IEEE Transactions on Knowledge and Data Engi- neering [CCF A] [JCR Q1]
[IEEE TAI] Geng Tu, Jintao Wen, Cheng Liu, Dazhi Jiang, Erik Cambria: Context-and sentiment-aware networks for emotion recognition in conversation. IEEE Transactions on Artificial Intelligence.
[BIB] Tianyi Chen, Xindian Wei, Lianxin Xie, Yunfei Zhang, Cheng Liu, Wenjun Shen, Si Wu and Hau- San Wong: SELF-Former:Multi-scale Gene Filtration Transformer for Single-cell Spatial Reconstruction. Briefings in Bioinformatics [JCR Q1] [CCF-B]
[PR] Wenming Cao, Zhongfan Zhang, Cheng Liu, Rui Li, Qianfen Jiao, Zhiwen Yu, Hau-San Wong: Unsu- pervised discriminative feature learning via finding a clustering-friendly embedding space. Pattern Recogni- tion (2022) [CCF B][JCR Q1]
[INFFUS] Jintao Wen, Dazhi Jiang, Geng Tu, Cheng Liu, Erik Cambria: Dynamic interactive multiview memory network for emotion recognition in conversation. Information Fusion [JCR Q1]
[INFFUS] Projected cross-view learning for unbalanced incomplete multi-view clustering. Yiran Cai, Hangjun Che, Baicheng Pan, Man-Fai Leung, Cheng Liu, Shiping Wen. Informaion Fusion (2024) [JCR Q1]
[INS] Chenglu Li, Hangjun Che, Man-Fai Leung, Cheng Liu, Zheng Yan: Robust multi-view non-negative matrix factorization with adaptive graph and diversity constraints. Information Sciences. [CCF B][JCR Q1]
[INS] Dazhi Jiang, Geng Tu, Donghui Jin, Kaichao Wu, Cheng Liu, Lin Zheng, Teng Zhou: A hybrid intel- ligent model for acute hypotensive episode prediction with large-scale data. Information Science. 2021 [CCF B] [JCR Q1]
[INS] Qianfen Jiao, Jian Zhong, Cheng Liu, Si Wu, Hau-San Wong: Perturbation-insensitive cross-domain image enhancement for low-quality face verification. Information Science [CCF B] [JCR Q1]
[KBS] Sentao Chen, Hanrui Wu, Cheng Liu: Domain invariant and agnostic adaptation. Knowledge-Based Systems. [CCF C] [JCR Q1]
[KBS] Rui Li, Cheng Liu, Dazhi Jiang: Efficient dynamic feature adaptation for cross language sentiment analysis with biased adversarial training. Knowledge-Based Systems. [CCF C] [JCR Q1]
[NEURO] Chutao Zheng, Cheng Liu, Hau-San Wong: Corpus-based topic diffusion for short text clustering. Neurocomputing (2018) [CCF C] [JCR Q1]
[NEURO] Sheng Qian, Hua Liu, Cheng Liu, Si Wu, Hau-San Wong: Adaptive activation functions in con- volutional neural networks. Neurocomputing (2018) [CCF C] [JCR Q1]
[NEURO] Dongmin Huang, Sentao Chen, Cheng Liu, Lin Zheng, Zhihang Tian, Dazhi Jiang: Differences first in asymmetric brain: A bi-hemisphere discrepancy convolutional neural network for EEG emotion recog- nition. Neurocomputing (2021) [CCF C] [JCR Q1]
[NN] Xiao Zhang, Xinyu Pu, Cheng Liu, Jun Qin, Hangjun Che: Two-step Graph Propagation for Incomplete Multi-view Clustering. Neural Networks (2024). [JCR Q1] [CCF B]
[NN] Training multi-source domain adaptation network by mutual information estimation and minimization. Lisheng Wen, Sentao Chen, Mengying Xie, Cheng Liu, Lin Zheng. Neural Networks (2024) [JCR Q1] [CCF B]
[KBS] Cluster-based Adversarial Decision Boundary for domain-adaptive open set recognition. Jian Zhong, Qianfen Jiao, Si Wu, Cheng Liu, Hau-San Wong. Knowledge-Based Systems 2024. [JCR Q1] [CCF C]
[BIOF] Multi-scale topology and position feature learning and relationship-aware graph reasoning for pre- diction of drug-related microbes. Ping Xuan, Jing Gu, Hui Cui, Shuai Wang, Nakaguchi Toshiya, Cheng Liu, Tiangang Zhang Bioinformatics 2024. [JCR Q2] [CCF B]
[CIBM] Zhihui He, Yingqing Lin, Runguo Wei, Cheng Liu, Dazhi Jiang: Repulsion and attraction in search- ing: A hybrid algorithm based on gravitational kernel and vital few for cancer driver gene prediction. Com- puters in Biology and Medicine. [JCR Q1]
[SP] Centric graph regularized log-norm sparse non-negative matrix factorization for multi-view clustering. Yuzhu Dong, Hangjun Che, Man-Fai Leung, Cheng Liu, Zheng Yan. Signal Processing (2023) [JCR Q2] [CCF C]
[FIM] Guoyun Wang, Cheng Lv, Cheng Liu, Wenjun Shen Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility. Frontiers in Microbiology. 2022
[Molecules] Wen-Jun Shen, Xun Zhang, Shaohong Zhang, Cheng Liu, Wenjuan Cui. The utility of supertype clustering in prediction for class II MHC-peptide binding. Molecules. 2018
[FAM] Keyuan Pu, Jiamin Qiu, Jiaying Li, Wei Huang, Xiaopin Lai, Cheng Liu, Yan Lin, Kwan-Ming Ng. MALDI-TOF MS protein profiling combined with multivariate analysis for identification and quantitation of beef adulteration. Food Analytical Methods. 2023
[SC] Xin-Ze Luan, Yong Liang, Cheng Liu, Kwong-Sak Leung, Tak-Ming Chan, Zongben Xu, Hai Zhang: A novel L1/2 regularization shooting method for Cox’s proportional hazards model. Soft Computing (2014) [JCR Q1]
[Applied Intelligence] Xuanhao Yang, Hangjun Che, Man-Fai Leung, Cheng Liu: Adaptive graph nonneg- ative matrix factorization with self-paced regularization. Applied Intelligence. [JCR Q1]
[MSSP] Guorong Xiao, Yunju Ma, Cheng Liu, Dazhi Jiang: A machine emotion transfer model for intelligent human-machine interaction based on group division Mechanical Systems and Signal Processing [JCR Q1]
[Connection Science] Dazhi Jiang, Runguo Wei, Zhihui He, Senlin Lin, Cheng Liu, Yingqing Lin: GASN:
gamma distribution test for driver genes identification based on similarity networks. Connection Science [CCF C]
会议论文
[IEEE ICME] Yixuan Ye, Yang Zhang, Liang Peng, Cheng Liu #, Si Wu, Hau-San Wong: Cross-View Neighborhood Contrastive Multi-View Clustering with View Mixup Feature Learning. IEEE ICME 2025 [CCFB] (通讯作者，指导老师)
[ACM MM] Xibiao Wang, Hang Gao, Liang Peng, Xindian Wei, Cheng Liu#, Si Wu, Hau-San Wong: Con- trastive Graph Distribution Alignment for Partially View-aligned Clustering. ACM MM 2024 [CCF A] (通 讯作者，指导老师)
[ACM MM] Le Jiang, Yan Huang, Lianxin Xie, Wen Xue, Cheng Liu, Si Wu, Hau-San Wong: Hunting Blemishes: Language-guided High-fidelity Face Retouching Transformer with Limited Paired Data. ACM Multimedia 2024 [CCF A]
[IJCAI] Lu Lin, Wen Xue, Tianyi Chen, Cheng Liu#, Si Wu#, Hau-San Wong: SCTrans: Multi-scale scRNA- seq Sub-vector Completion Transformer for Gene-selective Cell Type Annotation IJCAI 2024 [CCF A] (共 同通讯作者，合作指导老师)
[AAAI] Wen Xue, Lianxin Xie, Le Jiang, Tianyi Chen, Si Wu#, Cheng Liu#, Hau-San Wong: Retouch- Former: Semi-supervised High-quality Face Retouching Transformer with Prior-based Selective Self-attention. AAAI 2024 [CCFA] ，(共同通讯作者，合作指导老师)
[COLING] Rui Li, Cheng Liu, Yu Tong and Jiang Dazhi. Feature Structure Matching for Multi-source Sen- timent Analysis with Efficient Adaptive Tuning. COLING 2024 [CCF B] (共同通讯作者)
[IEEE ICME] Junjie Liang (研究生), Hang Gao (研究生), Haojun Sun, Rui Li, and Cheng Liu#: Reliable self-supervised information mining for deep subspace clustering. IEEE ICME 2022 [CCF B]. (通讯作者，指 导老师)
[CVPR] Lianxin Xie, Bingbing Zheng, Wen Xue, Le Jiang, Cheng Liu, Si Wu, Hau-San Wong Learning Degradation-unaware Representation with Prior-based Latent Transformations for Blind Face Restoration. CVPR 2024 [CCF A]
[CVPR] Si Wu, Jichang Li, Cheng Liu, Zhiwen Yu, Hau-San Wong: Mutual Learning of Complementary Networks via Residual Correction for Improving Semi-Supervised Classification. CVPR 2019: 6500-6509 (CCF A)
[CVPR] Xiwen Wei, Zhen Xu, Cheng Liu, Si Wu, Zhiwen Yu, Hau San Wong: Text-Guided Unsupervised Latent Transformation for Multi-Attribute Image Manipulation. CVPR 2013 (CCF A)
[IEEE SMC] Hang Gao (研究生), Yunshan Li (本科生) and Cheng Liu#: Progressive Deep Subspace Clustering based on Sample Reliability. IEEE SMC 2022 [CCF C]. (指导老师)
[ICONIP] Yang Zhang, Cheng Liu and Hau-San Wong: Exploring the Fourier Domain for Fast Multi-View Subspace Clustering. ICONIP 2024 [CCF C]
[ICONIP] Cheng Liu, Wen-Ming Cao, Chutao Zheng, Hau-San Wong: Learning With Partially Shared Fea- tures in Multi-Task Learning. The 24th International Conference on Neural Information Processing ICONIP [CCF C]
[IJCAI] Sheng Qian, Guanyue Li, Wen-Ming Cao, Cheng Liu, Si Wu, Hau-San Wong: Improving repre- sentation learning in autoencoders via multidimensional interpolation and dual regularizations. IJCAI 2019 (CCF A)
[COLING] Rui Li, Cheng Liu, Dazhi Jiang: Asymmetric Mutual Learning for Multi-source Unsupervised Sentiment Adaptation with Dynamic Feature Network (CCF B)
[ICME] Zhongfan Zhang, Wenming Cao, Cheng Liu, Rui Li, Qianfen Jiao, Zhiwen Yu, C. L. Philip Chen, Hau-San Wong: Unsupervised Ensemble Learning Via Network Generation. ICME 2021 (CCF B）
