李向涛-人工智能学院

李向涛，吉林大学人工智能学院教授，国家级青年人才，入选了《麻省理工科技评论》“2023年中国智能计算创新人物”，连续三年（2020-2022年）入选斯坦福大学全球前 2%顶尖科学家榜单，主持国家自然科学面上基金和青年基金，吉林省青年和面上基金项目，纵向经费累积达到500万元。以第一作者或通讯作者在学术期刊上发表相关论文约100篇，中科院一区及生物信息学顶级期刊约60篇，其中在顶级期刊 Nature Communications、Advanced Science、Nucleic Acids Research 上发表论文8篇；在生物信息学权威期刊发表论文24篇，包括Bioinformatics 8篇，PLoS Computational Biology 1篇，Briefings in Bioinformatics 12篇，Communications Biology 2篇；IEEE Trans系列期刊及CCF A类会议发表论文20篇，包括IEEE Transactions on Cybernetics 4篇，IEEE Transactions on Systems, Man, and Cybernetics: Systems 1篇，AAAI 2篇，IEEE/ACM Transactions on Computational Biology and Bioinformatics 7篇，IEEE Journal of Biomedical and Health Informatics 1篇，IEEE Transactions on NanoBioscience 2篇，IEEE Transactions on Engineering Management 2篇。

根据Google Scholar统计，论文被引用4000余次，H-index=34。其中，一篇论文入选ESI高被引论文（被引频次前1%），单篇引用最高次数300次，9篇论文引用次数超过100次。带领团队以第一完成人及第二完成人完成省级自然科学学术成果奖各一项。围绕近年来国内外演化计算与无监督学习计算算法层面的工作进展，出版英文专著《Natural Computing for Unsupervised Learning》，由Springer 出版社出版。也是NeurIPS 2024 (Area Chair)及多个国际SCI期刊BMC Biology (中科院一区), BMC Bioinformatics (CCF C), BMC Genomics副主编或编委。

个人主页：https://lixt314.github.io/BDCI.github.io///publications_Xiangtao/

2020.03 —— 至今吉林大学人工智能学院教授

2017.03 —— 2019.04 香港城市大学高级研究助理

2015.11 —— 2016.11 英国萨里大学访问学者

2015.07 —— 2020.03 东北师范大学信息科学与技术学院副教授

2012.09 —— 2015.06 东北师范大学博士

2009.09 —— 2012.06 东北师范大学硕士

2005.09 —— 2009.06 东北师范大学本科

作为主持国家自然科学基金2项、吉林省自然科学基金2项，累计参与项目达10项。

1．国家高层次青年人才计划项目，2023，主持

2. 国家自然科学基金委员会，面上项目，62472195，面向单细胞ATAC测序数据的深度学习模型与可解释性研究，2025-01至2028-12，主持；

3. 国家自然科学基金委员会，面上项目，62076109，高维稀疏数据下进化深度聚类方法研究，2021-01至2024-12，主持；

4. 国家自然科学基金委员会，青年项目，61603087，基于代理模型和层次进化算法的多目标双层规划问题研究，2017-01至2019-12，主持；

5．吉林省优秀青年科技人才项目，2023，主持

6. 吉林省科技厅青年基金项目，20190103006JH，基于多目标群智能算法的混合调度问题研究，2019-01至2020-12，主持；

7. 吉林省自然科学基金面上项目，20160101253JC，基于代理模型和层次进化算法的双层规划问题研究2016-01至2018-12，主持。

部分论文信息如下：

1. H. Zhu, Y. Yang, Y. Wang, F. Wang, Y. Huang, Y. Chang, K. Wong*, X. Li* , Dynamic characterization and interpretation for protein–RNA interactions across diverse cellular conditions using HDRNet, Nature Communications , 2023. (IF= 17.694, Q1)

2. Z. Yu, Y. Su, Y. Lu, F. Wang, S. Zhang, Y. Chang, K. Wong*, X. Li* , Topological Identification and Interpretation for Single-cell Gene Regulation Elucidation across Multiple Platforms using scMGCA, Nature Communications , 2023. (IF= 17.694, Q1)

3. Y. Su, Z. Yu, Y. Yang, X. Li* , Distribution-agnostic Deep Learning Enables Accurate Single‐Cell Data Recovery and Transcriptional Regulation Interpretation, Advanced Science , 2024. (IF= 17.521, Q1)

4. Y. Fan, Y. Wang, F. Wang, L. Huang, Y. Yang, K. Wong, X. Li* , Reliable Identification and Interpretation of Single-cell Molecular Heterogeneity and Transcriptional Regulation using Dynamic Ensemble Pruning, Advanced Science , 2023. (IF= 17.694, Q1)

5. Y. Yang, G. Li, K. Pan, W. Cao, Z. Zhang*, X. Li* , Deciphering 3’ UTR Mediated Gene Regulation Using Interpretable Deep Representation Learning, Advanced Science , 2024. (IF= 14.3, Q1)

6. Z. Zheng, J. Chen, X. Chen, L. Huang, W. Xie, Q. Lin, X. Li* , K. Wong*, Enabling Single-cell Drug Response Annotations from Bulk RNA- seq using SCAD, Advanced Science , 2023. (IF=17.521, Q1)

7. F. Wang, H. Alinejad-Rokny, J. Lin, T. Gao, X. Chen, L. Meng, X. Li* , K. Wong*, A lightweight framework for chromatin loop detection on single-cell Hi-C, Advanced Science , 2023. (IF= 17.521, Q1)

8. N. Chen, J. Yu, Z. Liu, L. Meng, X. Li* , K. Wong*, Discovering DNA shape motifs with multiple DNA shape features: generalization, methods, and validation, Nucleic Acids Research , 2024, (IF = 14.9, Q1)

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9. Y. Zhang, Z. Yu, K. Wong, X. Li* , Unraveling Spatial Domain Characterization in Spatially Resolved Transcriptomics with Robust Graph Contrastive Clustering, Bioinformatics , 2024. (IF=6.931,Q1)

10. Y. Wang, Y. Zhu, S. Li, C. Bian, Y. Liang, K. Wong, X. Li* , scBGEDA: Deep Single-cell Clustering Analysis via a Dual Denoising Autoencoder with Bipartite Graph Ensemble Clustering, Bioinformatics , 2023. (IF=6.931,Q1)

11. Q. Qi, Y. Wang, Y. Huang, Y. Fan*, X. Li* , PredGCN: A Pruning-enabled Gene-Cell Net for Automatic Cell Annotation of Single Cell Transcriptome Data , Bioinformatics , 2024. (IF=4.4,Q1)

12. P. Sun, S. Fan, S. Li, Y. Zhao, C. Lu*, K. Wong, X. Li* , Automated Exploitation of Deep Learning for Cancer Patient Stratification across Multiple Types, Bioinformatics , 2023. (IF=6.931,Q1)

13. Y. Su, F. Wang, S. Zhang, Y. Liang, K. Wong, X. Li* , scWMC: Weighted Matrix Completion-based Imputation of scRNA-seq Data via Prior Subspace Information, Bioinformatics , 2022. (IF=6.931,Q1)

14. F. Lu, Z. Yu, Y. Wang, Z. Ma, K. Wong, X. Li* , GMHCC: High-throughput Analysis of Biomolecular Data using Graph-based Multiple Hierarchical Consensus Clustering, Bioinformatics , 2022. (IF=6.931,Q1)

15. Y. Wang, Y. Yang, Z. Ma, K. Wong, X. Li* , EDCNN: Identification of Genome-Wide RNA-binding Proteins Using Evolutionary Deep Convolutional Neural Network, Bioinformatics , 2021. (IF=6.931, Q1)

16. X. Li , S. Zhang, K. Wong. Single-cell RNA-seq Interpretations using Evolutionary Multiobjective Ensemble Pruning, Bioinformatics , 2019. (IF=6.937, Q1)

17. Y. Wang, C. Bian, K. Wong, X. Li* , S. Yang*. Multiobjective Deep Clustering and Its Applications in Single-cell RNA-seq Data, IEEE Transactions on Systems, Man, and Cybernetics: Systems , 2021. (IF=13.451, Q1)

18. Su, H. Zhu, K. Wong, Y. Chang, X. Li* , Hyperspectral Image Denoising via Weighted Multidirectional Low-rank Tensor Recovery, IEEE Transactions on Cybernetics , 2022. (IF=19.118,Q1)

19. Y. Wang, X. Li* , K. Wong, Y. Chang, S. Yang. Evolutionary Multiobjective Clustering Algorithms with Ensemble for Patient Stratification, IEEE Transactions on Cybernetics , 2021. (IF=19.118,Q1)

20. X. Li , S. Zhang, K. Wong. Multiobjective Genome-Wide RNA-Binding Event Identification from CLIP-seq Data, IEEE Transactions on Cybernetics , 2019. (IF=19.118,Q1)

21. X. Li , K. Wong. Evolutionary Multi-objective Clustering and Its Applications to Patient Stratification, IEEE Transactions on Cybernetics , 2018. (IF=19.118,Q1)

22. Y. Wang, Z. Hou, Y. Yang, K. Wong, X. Li*, Genome-wide Identification and Characterization of DNA Enhancers with a Stacked Multivariate Fusion Framework, PLOS Computational Biology , 2022. (Q1)

23. X. Li , S. Li, L. Huang, S. Zhang, K. Wong. High-throughput Single-cell RNA-seq Data Imputation and Characterization with Surrogate-assisted Automated Deep Learning, Briefings in Bioinformatics , 2021. (IF=13.994, Q1)

24. Y. Cheng, Y. Su, Z. Yu, Y. Liang, K. Wong, X. Li* , Unsupervised Deep Embedded Fusion Representation of Single-cell Transcriptomics, Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023) , 2022. (Q1, Oral)

25. Z. Yu, Y. Lu, Y. Wang, F. Tang, K. Wong, X. Li* , ZINB-based Graph Embedding Autoencoder for Single-cell RNA-seq Interpretations, Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022) , 2021. (Q1, Oral)

26. M. Toseef, O. O. Petinrin, F. Wang, S. Rahaman, Z. Liu, X. Li* , K. Wong*, Deep transfer learning for clinical decision-making based on high-throughput data: comprehensive survey with benchmark results, Briefings in Bioinformatics , 2023. (IF=9.5, Q1)

27. Z. Hou, Y. Yang. Z. Ma, K. Wong, X. Li* , Learning the Protein Language of Proteome-wide Protein-protein Binding Sites via Explainable Ensemble Deep Learning, Communications Biology , 2022.

28. F. Wang, T. Gao, J. Lin, Z. Zheng, L. Huang, M. Toseef, X. Li* , K. Wong*, GILoop: robust chromatin loop calling across multiple sequencing depths on Hi-C data, iScience , 2022. (IF=6.107, Cell Press)

29. L. Huang, J. Lin, R. Liu, Z. Zhang, L. Meng, X. Chen, X. Li* , K. Wong*, CoaDTI: Multi-modal Co-attention based framework for drug-target interaction annotation, Briefings in Bioinformatics , 2022. (IF=13.994, Q1)

30. M. Toseef, X. Li* , K. Wong*, Reducing healthcare disparities using multiple multiethnic data distributions with fine-tuning of transfer learning, Briefings in Bioinformatics , 2022. (IF=11.622, Q1)

31. Y. Yang, Z. Hou, Y. Wang, H. Ma, P. Sun, Z. Ma, K. Wong, X. Li* , HCRNet: High-throughput circRNA-Binding Event Identification from CLIP-seq Data using Deep Temporal Convolutional Network, Briefings in Bioinformatics , 2022. (IF=11.622, Q1)

32. L. Huang, J. Lin, X. Li*, L. Song, Z. Zheng, and K. Wong*, EGFI: Drug-Drug Interaction Extraction and Generation with Fusion of Enriched Entity and Sentence Information, Briefings in Bioinformatics , 2021. (IF=11.622, Q1)

33. X. Li , S. Li, L. Huang, S. Zhang, K. Wong. High-throughput Single-cell RNA-seq Data Imputation and Characterization with Surrogate-assisted Automated Deep Learning, Briefings in Bioinformatics , 2021. (IF=11.622, Q1)

34. Z. Hou, Y. Yang, H. Li, K. Wong, X. Li* . iDeepSubMito: Identification of protein sub-mitochondrial localization with deep learning, Briefings in Bioinformatics , 2021. (IF=11.622, Q1)

35. Z. Yu, C. Bian, G. Liu, S. Zhang, K. Wong, X. Li* . Elucidating Transcriptomic Profiles from Single-cell RNA sequencing Data using Nature-Inspired Compressed Sensing, Briefings in Bioinformatics , 2021. (IF=11.622, Q1)

36. X. Li , S. Zhang, K. Wong. Deep Embedded Clustering with Multiple Objectives on scRNA-seq Data, Briefings in Bioinformatics , 2021. (IF=11.622, Q1)

37. Y. Yang, S. Li, Y. Wang, K. Wong, X. Li* . Identification of Haploinsufficient Genes from Epigenomic Data using Deep Forest, Briefings in Bioinformatics , 2020. (IF=11.622, Q1)

38. X. Li , S. Li, Y. Wang, S. Zhang, K. Wong. Identification of Pan-cancer Ras Pathway Activation with Deep Learning, Briefings in Bioinformatics , 2020. (IF=11.622, Q1)

39. Y. Yang, Z. Hou, Z. Ma, X. Li* , K. Wong*, iCircRBP-DHN: identification of circRNA-RBP interaction sites using deep hierarchical network, Briefings in Bioinformatics , 2020. (IF=11.622, Q1)

40. X. Li , K. Wong. Multiobjective Patient Stratification using Evolutionary Multiobjective Optimization. IEEE Journal of Biomedical and Health Informatics , doi.10.1109/JBHI.2017.2769711, 2017. (Q1)

41. X. Li , S. Zhang, K. Wong. Evolving Transcriptomic Profiles from Single-cell RNA-seq Data using Nature-Inspired Multiobjective Optimization, IEEE/ACM Transactions on Computational Biology and Bioinformatics , doi. 10.1109/TCBB.2020.2971993, 2020.

42. Y. Wang, Q. Ma, K. Wong, X. Li* . Evolving Multiobjective Cancer Subtype Diagnosis from Cancer Gene Expression Data, IEEE/ACM Transactions on Computational Biology and Bioinformatics , doi.10.1109/TCBB.2020.2974953, 2020.

43. X. Li , K. Wong. Single-Cell RNA-seq Data Interpretation by Evolutionary Multiobjective Clustering, IEEE/ACM Transactions on Computational Biology and Bioinformatics , doi.10.1109/TCBB.2019.2906601, 2019.

44. X. Li , S. Zhang, K. Wong. Nature-Inspired Multiobjective Epistasis Elucidation from Genome-Wide Association Studies, IEEE/ACM Transactions on Computational Biology and Bioinformatics , doi. 10.1109/TCBB.2018.2849759, 2018.

45. X. Li, K. Wong. Elucidating Genome-Wide Protein-RNA Interactions using Differential Evolution, IEEE/ACM Transactions on Computational Biology and Bioinformatics , doi. 10.1109/TCBB.2017.2776224, 2017.

46. X. Li , K. Wong, A Comparative Study for Identifying the Chromosome-Wide Spatial Clusters from High-Throughput Chromatin Conformation Capture data, IEEE/ACM Transactions on Computational Biology and Bioinformatics , doi: 10.1109/TCBB.2017.2684800, 2017.

BMC Biology (2023~, 中科院一区)

BMC Bioinformatics (2022~)(CCF C, IF=3.328)

BMC Genomics (2022~)(CCF C, IF=4.558)

Nature Communications, PNAS, American Journal of Human Genetics (AJHG), Advanced Science, Cell Genomics, Cell Reports, Cell Reports Methods, Cell Reports Physical Science, Genome Biology, Bioinformatics, Briefings in Bioinformatics, PLoS Computational Biology, IEEE TPAMI, IEEE TKDE, IEEE TCYB, IEEE TNNLS, IEEE TEVC等期刊