刘育松博士，主要研究方向为生物医学信息学、机器学习与人工智能。于2022年在哈尔滨工程大学获控制科学与工程学科工学博士学位，博士导师为叶秀芬教授，曾获国家留学基金委资助赴美国印第安纳大学医学院黄昆教授实验室联合培养两年。2023年通过校优秀人才计划加入哈尔滨医科大学医工交叉学院。 

目前主要从事转录组数据的网络化分析方法、空间转录组数据挖掘以及机器学习方法在生物信息学中的应用等研究工作，也参与水下图像增强等图像处理领域研究。曾发表SCI检索论文10余篇，担任学术期刊《Briefings in Bioinformatics》、《BMC Bioinformatics》审稿人。

教育经历

2015.09 – 2022.12     哈尔滨工程大学         控制科学与工程         工学博士

2011.09 – 2015.06     哈尔滨工程大学         电子信息工程             工学学士

工作经历

2023.05 - 至今           哈尔滨医科大学          医工交叉学院                     讲师

2018.09 - 2020.10     印第安纳大学医学院 计算生物与生物信息研究所 公派联培

承担项目

国家自然科学基金委员会，青年科学基金项目，基于多层级基因共表达特征的空间转录组数据空间域识别方法研究（62402144），2025.01-2027.12，30万元

代表性论文

1. Yusong Liu, Tongxin Wang, Ben Duggan, Sharpnack Michael, Kun Huang, Jie Zhang*, Xiufen Ye*, Travis S. Johnson*. SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression, Briefings in Bioinformatics, 2022, 23(3): bbac116. (IF: 9.5)

2. Yusong Liu, Xiufen Ye, Xiaohui Zhan, Christina Y Yu, Jie Zhang, Kun Huang*. TPQCI: A topology potential-based method to quantify functional influence of copy number variations, Methods, 2021, 192: 46-56. (IF: 4.6)

3. Yusong Liu, Xiufen Ye*, Christina Y Yu, Wei Shao, Jie Hou, Weixing Feng, Jie Zhang, Kun Huang*. TPSC: A Module Detection Method Based on Topology Potential and Spectral Clustering in Weighted Networks and Its Application in Gene Co-expression Module Discovery, BMC Bioinformatics, 2021, 22(Suppl 4):111. (IF: 3.3)

4. Qian Ding#, Wenyi Yang#, Guangfu Xue#, Hongxin Liu, Yideng Cai, Jinhao Que, Xiyun Jin, Meng Luo, Fenglan Pang, Yuexin Yang, Yi Lin, Yusong Liu, Haoxiu Sun, Renjie Tan, Pingping Wang*, Zhaochun Xu*, Qinghua Jiang*. Dimension reduction, cell clustering, and cell–cell communication inference for single-cell transcriptomics with DcjComm, Genome Biology, 2024, 25: 241.

5. Junting Wang, Xiufen Ye*, Yusong Liu, Xinkui Mei, Xing Wei. Learning mapping by curve iteration estimation For real-time underwater image enhancement, Optics Express, 2024, 32(6): 9931-9945.

6. Yunpeng Jia, Xiufen Ye*, Xinkui Mei, Yusong Liu, Shuxiang Guo. MLTU: mixup long-tail unsupervised zero-shot image classification on vision-language models, Multimedia Systems, 2024, 30: 169.

7. Yunpeng Jia, Xiufen Ye, Yusong Liu, Shuxiang Guo. Multi-modal recursive prompt learning with mixup embedding for generalization recognition. Knowledge-Based Systems, 2024, 294: 111726.

8. Xinkui Mei, Xiufen Ye*, Junting Wang, Xuli Wang, Yusong Liu, Yunpeng Jia, Shengya Zhao. UIEOGP: an underwater image enhancement method based on optical geometric properties, Optics Express, 2023, 31(22): 36638-36655 (IF: 3.8)

9. Xiaohui Zhan, Yusong Liu, Asha Jacob Jannu, Shaoyang Huang, Bo Ye, Wei Wei, Pankita H. Pandya, Xiufen Ye, Karen E. Pollok, Jamie L. Renbarger, Kun Huang, Jie Zhang*. Identify Potential Driver Genes for PAX-FOXO1 Fusion-Negative Rhabdomyosarcoma Through Frequent Gene Co-expression Network Mining, Frontiers in Oncology, 2023, 13: 1080989. (IF: 4.7)

10. Junting Wang, Xiufen Ye*, Yusong Liu, Xinkui Mei, Jun Hou. Underwater self-supervised monocular depth estimation and its application in image enhancement, Engineering Applications of Artificial Intelligence, 2023, 120: 105846. (IF: 8.0)

11. Xinkui Mei, Xiufen Ye*, Xiaofeng Zhang, Yusong Liu, Junting Wang, Jun Hou, Xuli Wang. UIR-Net: A Simple and Effective Baseline for Underwater Image Restoration and Enhancement, Remote Sensing, 2023, 15(1): 39. (IF: 5.0)

12. Jie Hou, Xiufen Ye*, Weixing Feng, Qiaosheng Zhang, Yatong Han, Yusong Liu, Yu Li, Yufen Wei. Distance correlation application to gene co-expression network analysis, BMC Bioinformatics, 2022, 23: 81. (IF: 3.0)

13. Xiaohui Zhan*, Yusong Liu, Christina Y Yu, Tianfu Wang, Jie Zhang, Ni Dong*, Kun Huang*. A pan-kidney cancer study identifies subtype specific perturbations on pathways with potential drivers in renal cell carcinoma, BMC Medical Genomics, 2020, 13 (Suppl 11): 190. (IF: 3.1)

14. Yatong Han, Xiufen Ye, Chao Wang, Yusong Liu, Siyuan Zhang, Weixing Feng, Kun Huang*, Jie Zhang*. Integration of molecular features with clinical information for predicting outcomes for neuroblastoma patients, Biology Direct, 2019, 14: 16. (IF: 7.2)

获奖情况

2024年度黑龙江省人工智能学会优秀博士学位论文  二等奖