刘诚，特聘研究员, IEEE 高级会员，硕士生导师，2018 年7月博士毕业于香港城市大学。主要研究方向为机器学习算法：多视图学习，多任务学习，生存分析算法等，同时运用人工智能算法解决与临床癌症相关的生物信息学应用问题。期间主持了 6 个科研项目，包含国家自然科学基金青年基金项目，两项广东省自然科学基金面上项目，广东省教育厅青年创新人才项目，中国科学技术大学苏州高等研究院横向项目，汕头大学卓越人才科研启动基金 (100 万)，并以第一参与人参与国家自然科学基金面上项目和广东省自然科学基金青年提升项目。在研究领域发表论文 70 余篇，其中作为第一作者/通讯作者（含共 同通讯作者、合作指导老师）的身份在包含顶级期刊和会议上（IEEE TKDE，IEEE TNNLS，IEEE TCSVT IEEE TCYB，IEEE TCBB, IEEE TBME, PR, Bioinformatics, AAAI，IJCAI，ACMMM，ICME 等）发表了28篇论文，其中15篇 CCF-A 或中科院一区，11 篇 CCF-B 或中科院二区，2 篇 CCF-C, 包含一篇 ESI（IEEE TNNLS，CCF-B，CAAI-A，中科院一区）高被引论文和一篇热点论文（IEEE TKDE，CCF-A）。Google Scholar 引用 2000+，H-index 26i-index 40。

项目信息：

• 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（横 向），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

本科竞赛指导：

• 2024 中国机器人及人工智能大赛全国总决赛 三等奖

• 2024 广东省算法调优竞赛项目 三等奖

• 2024 中国创意挑战大赛(国赛普通高等院校赛道) 二等奖

• 2024 全国大学生数学建模大赛 二等奖

• 第十四届“挑战杯”广东大学生创业计划竞赛 铜奖

• 2024 年广东省大学生计算机设计大赛 三等奖

• 第12届 “泰迪杯”数据挖掘挑战赛 二等奖

• 第二十六届中国机器人及人工智能大赛广东省选拔赛二等奖

• 第六届全球校园人工智能算法精英大赛广东赛区省赛二等奖

• 中国国际大学生创新大赛2024- 广东省分赛铜奖

• 第六届全球校园人工智能算法精英大赛全国总决赛优秀指导老师

发表论文：

期刊：

• [IEEE JBHI] Cheng Liu, Baoyuan Zheng, Hang Gao, Xibiao Wang, Fei Wang, Wenjun Shen, Si Wu : Deep Self-Reinforced Multi-View Subspace Clustering for Cancer Subtyping. IEEE Journal of Biomedical and Health Informatics 2025. [JCR Q1] [CCF-C]

• [IEEE TCSVT] Liang Peng, Yixuan Ye, Cheng Liu#, Hangjun Che, Fei Wang, Zhiwen Yu, Si Wu and Hau-San Wong: SMART: Semantic Matching Contrastive Learning for Partially View-Aligned Clustering. IEEE Transactions on Circuits and Systems for Video Technology (2025) [JCR Q1] [CCF B] (Corresponding author)

• [IEEE TKDE] Liang Peng, Yixuan Ye, Cheng Liu#, Hangjun Che, Si Wu and Hau-San Wong: Trustworthy Neighborhoods Mining: Homophily-Aware Neutral Contrastive Learning for Graph Clustering. IEEE Transactions on Knowledge and Data Engineering (2025) [JCR Q1] [CCF A] (Corresponding author)

• [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 Knowledge and Data Engineering (2024) [JCR Q1] [CCF A]

• [IEEE TNNLS] Cheng Liu, Rui Li, Hangjun Che, Man-Fai Leung, Si Wu, Zhiwen Yu and Hau-San Wong: Collaborative Topological Graph Learning for Multi-View Clustering. IEEE Transactions on Neural Networks and Learning Systems (2024) [JCR Q1] [CCF B]

• [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] [CCF A]

• [IEEE TNNLS] Cheng Liu, Rui Li, Hangjun Che, Si Wu, Dazhi Jiang, Zhiwen Yu and Hau-San Wong: Self-Guided Graph Partial Propagation for Incomplete Multi-View Clustering. IEEE Transactions on Neural Networks and Learning Systems (2023) [JCR Q1] [CCF B]

• [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) [JCR Q1] [CCF B]

• [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]

• [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 Engineering (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 Q2] [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 Q2] [CCF B]

• [IEEE TCBB] Hang Gao (Student), Wenjun Shen, 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) [CCF B] (Corresponding author)

• [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 (Co-corresponding author) [JCR Q1] [CCF B]

• [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]

• [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 System (2020) [JCR Q1] [CCF C]

• [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]

• [NEURO] Cheng Liu, Sentao Chen, Lin Zheng, Dazhi Jiang: Adaptive Graph-Guided Co-Regularization for Clustered Multi-Task Learning. Neurocomputing (2024) [JCR Q1]

• [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] (Co-corresponding author)

• [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] (Co-corresponding author)

• [CAIS] Zhen Zheng (Student), Rui Li, and Cheng Liu#: Learning Robust Class-level Alignment for Cross Domain Medical Image Analysis via Dual Consistency Regularizations. Complex \& Intelligent System (2023) [JCR Q1] (Corresponding author)

• [ASOC] Sijin Zhou, Dongmin Huang, Cheng Liu#, Dazhi Jiang#: Objectivity meets subjectivity: A subjective and objective feature fused neural network for emotion recognition. Applied Soft Computing (2024) [JCR Q1] (Co-corresponding author)

• [BMC Bioinformatics] Yong Liang (Supervisor), 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 classification. BMC Bioinformatics (2013) [CCF C] [JCR Q1] (Thesis of the master degree; Citation > 180)

• [IEEE TIP] Jichang Li, Si Wu, Cheng Liu, Zhiwen Yu, Hau-San Wong: Semi-Supervised Deep Coupled Ensemble 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 TCSVT] Hang Gao, Cheng Liu, Wei Du, Ying Li and Gaoyang Li: A Novel Approach for Effective Partially View-Aligned Clustering with Triple-Consistency. IEEE Transactions on Circuits and Systems for Video Technology. 2025. [JCR Q1] [CCF B]

• [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 Engineering (2022) [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

• [IEEE TCBB] Yingqing Lin, Zhihui He, Cheng Liu, Dazhi Jiang: ICE: A Driver Genes Identification Method With Improved Cross-Entropy Measure. IEEE/ACM Transactions on Computational Biology and Bioinformatics (2025) [CCF B]

• [IEEE TSPN] 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 Signal and Information Processing over Networks (2025)

• [IEEE TCBB] Hangjun Che, Wei Guo, Man-Fai Leung, Yuting Cao, Cheng Liu: Robust diverse multi-view learning for cancer subtyping. IEEE/ACM Transactions on Computational Biology and Bioinformatics (2025) [CCF B]

• [Bioinformatics] Multi-scale topology and position feature learning and relationship-aware graph reasoning for prediction of drug-related microbes. Ping Xuan, Jing Gu, Hui Cui, Shuai Wang, Nakaguchi Toshiya, Cheng Liu, Tiangang Zhang Bioinformatics 2024. [JCR Q2] [CCF B]

• [BMC Bioinformatics] Xianyong Zhou, Xindian Wei, Cheng Liu, Ping Xuan, Wenjun Shen, Si Wu and Hau-San Wong: Robust Subspace Structure Discovery for Cell Type Identification in scRNA-seq Data BMC bioinformatics [JCR Q2] [CCF C].

• [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 (2024) [JCR Q1] [CCF-B]

• [PR] Hang Gao, Cheng Liu, Wei Du, Ying Li and Gaoyang Li: Multi-level Cross-view Feature Embedding for Partial View-aligned Clustering. Pattern Recognition (2025) [CCF B]

• [NN] Hang Gao, Zuosong Cai, Tao Liang, Cheng Liu, Ying Li, You Zhou, Wei Du: Cross-View Discrepancy-Driven Dynamic Weighting for Missing View Completion in Incomplete Multi-View Clustering. Neural Networks. [JCR Q1] [CCF B]

• [NN] Xiao Zhang, Xinyu Pu, Cheng Liu, Jun Qin, Hangjun Che: Two-step Graph Propagation for Incomplete Multi-view Clustering. Neural Networks. [JCR Q1] [CCF B]

• [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 intelligent model for acute hypotensive episode prediction with large-scale data. Information Science 546: 787-802 (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]

• [PR] Wenming Cao, Zhongfan Zhang, Cheng Liu, Rui Li, Qianfen Jiao, Zhiwen Yu, Hau-San Wong: Unsupervised discriminative feature learning via finding a clustering-friendly embedding space. Pattern Recognition (2022) [PR][CCF B][JCR Q1]

• [NN] Lisheng Wen, Sentao Chen, Mengying Xie, Cheng Liu, Lin Zheng: Training Multi-Source Domain Adaptation Network by Mutual Information Estimation and Minimization, Neuroal Networks 2023 [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]

• [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]

• [KBS] Diverse Semantic Image Synthesis with various conditioning modalities. Chaoyue Wu, Rui Li, Cheng Liu, Si Wu, Hau-San Wong. Knowledge-Based Systems 2024. [JCR Q1] [CCF C]

• [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 convolutional neural networks. Neurocomputing 272: 204-212 (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 recognition. Neurocomputing 448: 140-151 (2021) [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]

• [Information Fusion] Jintao Wen, Dazhi Jiang, Geng Tu, Cheng Liu, Erik Cambria: Dynamic interactive multiview memory network for emotion recognition in conversation. Information Fusion [CCF B][JCR Q1]

• [Information Fusion] 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] [CCF B]

• [Information Fusion] Sarcasm Driven by Sentiment: A Sentiment-Aware Hierarchical Fusion Network for Multimodal Sarcasm Detection. Hao Liu, Runguo Wei, Geng Tu, Jiali Lin, Cheng Liu and Dazhi Jiang. Information Fusion 2024. [JCR Q2] [CCF B]

会议论文：

• [AAAI] Liang Peng, Haopeng Liu, Yixuan Ye, Cheng Liu#, Wenjun Shen, Si Wu, Hau-San Wong: Refinement Contrastive Learning of Cell–Gene Associations for Unsupervised Cell Type Identification. AAAI 2025 [CCF A] (Corresponding author)

• [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 [CCF B] (Corresponding author)

• [ACM MM 2024] Xibiao Wang, Hang Gao, Liang Peng, Xindian Wei, Cheng Liu#, Si Wu, Hau-San Wong: Contrastive Graph Distribution Alignment for Partially View-aligned Clustering. ACM MM 2024 [CCF A] (Corresponding author)

• [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] (Co-corresponding author)

• [AAAI] Xue Wen, Lianxin Xie, Le Jiang, Tianyi Chen, Si Wu#, Cheng Liu#, Hau-San Wong. RetouchFormer: Semi-supervised High-quality Face Retouching Transformer with Prior-based Selective Self-attention. AAAI 2024 [CCF A] (Co-corresponding author)

• [IEEE ICME] Junjie Liang (Student), Hang Gao (Student), Haojun Sun, Rui Li, and Cheng Liu#. Reliable self-supervised information mining for deep subspace clustering. IEEE ICME 2022 [CCF B] (Corresponding author)

• [COLING] Rui Li, Cheng Liu#, Yu Tong and Jiang Dazhi. Feature Structure Matching for Multi-source Sentiment Analysis with Efficient Adaptive Tuning. COLING 2024 [CCF B] (Co-corresponding author)

• [ICONIP] Cheng Liu, Wen-Ming Cao, Chutao Zheng, Hau-San Wong. Learning With Partially Shared Features in Multi-Task Learning. The 24th International Conference on Neural Information Processing ICONIP [CCF C]

• [IEEE ICASSP] Rui Li, Tao Yang, Cheng Liu, Dazhi Jiang, Hau-San Wong, Si Wu: Prompt-augmented Feature with Cross-domain Contrastive Learning for Efficient Multi-domain Sentiment Analysis. ICASSP 2025 [CCF-B]

• [ACM MM 2024] 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]

• [IEEE ICME] Reference-conditional Makeup-aware Discrimination for Face Image Beautification, ZhenPing Li, Xindian Wei, Qianfen Jiao, Rui Li, Cheng Liu and Si Wu. ICME 2024.

• [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)

• [IJCAI] Sheng Qian, Guanyue Li, Wen-Ming Cao, Cheng Liu, Si Wu, Hau-San Wong. Improving representation learning in autoencoders via multidimensional interpolation and dual regularizations. IJCAI 2019: 3268-3274 (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: 1-6 (CCF B)

• [IEEE SMC] Chutao Zheng, Cheng Liu, Hau-San Wong. Iterative Term Weighting for Short Text Data. IEEE International Conference on Systems, Man, and Cybernetics. IEEE, 2015: 1687-1692. (Nominee of Best Paper Award) (CCF C)

• [IEEE SMC] Hang Gao (Student), Yunshan Li (Student) and Cheng Liu#. Progressive Deep Subspace Clustering based on Sample Reliability. IEEE SMC 2022 [CCF C] (Corresponding author)