刘艳霞

发布时间:2018-06-14 浏览次数:8453

基本信息

姓名:刘艳霞

办公室:B7-410(前座)

E-mail:cslyx@scut.edu.cn

所在团队:数据科学与智能软件


个人简介

刘艳霞,女,博士,副教授,硕士生导师,大数据与智能机器人教育部重点实验室成员,中国医药质量管理协会医学人工智能质量专委会委员,从事智慧医疗、工业智能检测、智能算法与智能软件研究。以第一或通信作者在国际刊物和国际会议发表论文20余篇,授权发明专利4项,软件著作权10余项,先后主持广东省科技计划重点项目、广东省自然科学基金、广州市应用基础研究计划等项目,承担多项企事业单位委托技术开发与信息化咨询项目,并作为主要成员参与多项国家自然科学基金和国家重点研发计划等项目。

学历

华南理工大学计算机应用专业,工学博士

教学经历

主要承担《软件分析设计与建模》、《软件测试》、《Java语言程序设计》、《软件开发综合实训》等课程教学。

工作经历

2007.9~2008.1 University of Maryland 访问学者

2019.3~2020.7 University of South Carolina 访问学者

2002.7~2004.7 华南理工大学计算机科学与工程学院

2004.7~至今,华南理工大学软件学院

社会兼职

中国医药质量管理协会医学人工智能质量专委会委员,担任IEEE Transaction on Image Processing, Neural Networks, Data Mining and knowledge Discover, Knowledge-Based System等多个学术期刊和会议审稿人

研究方向

人工智能、智慧医疗、工业智能检测、智能软件领域研究

获奖情况

曾获本科教学优秀奖二等奖、本科毕业论文优秀指导教师、研究生专业实践优秀指导教师、省级教学成果奖一等奖(排名第5)、优秀班主任; 指导本科生荣获第二届中国云移动互联网创新大奖赛一等奖、第三届粤港澳大学生计算机软件应用大赛一等奖和最佳创意奖;指导研究生荣获CCF大数据与计算智能大赛二等奖、放疗学术年会首届CSTRO AI勾画大赛冠军、DataFountain用车体验内容判别与标注大赛冠军。

科研项目

  1. 基于多源信号融合的隐性误吸动态监测方法研究,广东省自然科学基金,2024~2026 

  2. 基于体表多源时序信号与脑功能网络映射关联的脑卒中后隐性误吸实时动态监测方法研究,国家自然科学基金,2023~2026 (子课题)

  3. 面向高密度电子电路板的超精微缺陷检测技术研究,广东省普通高校特色创新,2023~2025 

  4. 小样本条件下的自适应机器学习理论与模型生成,科技部新一代人工智能重大项目,2020~2023(核心成员)

  5. 面向高效类脑智能和脑机接口的大数据与云计算技术研究,广州市科技计划重大专项, 2020~2023(核心成员)

  6. 近海运输无人船全自主航行关键技术研究及应用,广东省科技计划重点,2017~2019 

  7. 基于深度学习的eHCC肝癌智能诊断模型研究,软件学院青年教师专项,2018~2019

  8. 机器学习与语义规则融合的商品智能分类,企业委托开发,2019~2020

发表文章

1.Zhiqiang Liu, Yuhong Li, Chengkai Huang, KunTing Luo, Yanxia Liu*. Boosting fine-tuning via Conditional Online Knowledge Transfer. Neural Networks,2024,169: 325-333. (JCR Q1)

2.Yanxia Liu, Wenqi Wang, Yuhong Li, Haoyu Lai, Sijuan Huang and Xin Yang. Geometry-Consistent Adversarial Registration Model for Unsupervised Multi-Modal Medical Image Registration. IEEE Journal of Biomedical and Health Informatics, 2023,27(7):3455-3466. (JCR Q1)

3.Yanxia Liu, Anni Chen, Yuhong Li, Haoyu Lai, Sijuan Huang, Xin Yang,“CT synthesis from CBCT using a sequence-aware contrastive generative network”,Computerized Medical Imaging and Graphics, 2023,109:102300. (JCR Q1)

4.Suizhu Yang,Yanxia Liu*,Yuantong Jiang, Zhiqiang Liu,More refined superbag: Distantly supervised relation extraction with deep clustering,Neural Networks ,2023,157:193–201. (JCR Q1)

5.Liu, Yanxia, Xiaozhen Li, Rui Li, Sijuan Huang and Xin Yang. “A multi-view assisted registration network for MRI registration pre- and post-therapy.” Medical & Biological Engineering & Computing, 2023,61: 3181-3191. (JCR Q2)

6.Jia Qiao , Yuan-tong Jiang, Yong Dai, Yan-bin Gong , Meng Dai, Yan-xia Liu* and Zu-lin Dou ,Real-Time Dynamic Monitoring Method for Silent Aspiration after Stroke Based on Semisupervised Deep Learning: A Protocol Study, Digital Health,2023,9:1-12. (JCR Q2)

7.Hongbin Lin, Yifan Zhang,Zhen Qiu,Shuaicheng NiuChuang Gan,Yanxia Liu*,Mingkui Tan, Prototype-Guided Continual Adaptation for Class-Incremental Unsupervised Domain Adaptation, ECCV 2022. (CCF B)

8.Yanxia Liu, Anni Chen, Hongyu Shi, etc. CT Synthesis from MRI using Multi-Cycle GAN for Head-and-Neck Radiation Therapy, Computerized Medical imaging and Graphics, 2021,91:101953. (JCR Q1)

9.Deng Jiang, Haopeng Ren, Yi Cai, Jingyun Xu, Yanxia Liu*, Ho-fung Leung. Candidate region aware nested named entity recognition, Neural Networks, 2021,142:340-350. (JCR Q1)

10.Zhen Qiu,Yifan Zhang,Hongbin Lin,Shuaicheng Niu,Yanxia Liu,Qing Du,Mingkui Tan, Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation , IJCAI 2021(CCF A)

11.Zhiqiang Liu, Yanxia Liu*, Chengkai Huang. Semi-Online Knowledge Distillation, The British Machine Vision Conference, BMVC 2021(CCF C)

12.杨穗珠,刘艳霞*,张凯文,洪吟,黄翰.远程监督关系抽取综述. 计算机学报, 2021,44(8):1636-1660

13.Yin Hong, Yanxia Liu*, Suizhu Yang, et al. Joint extraction of entities and relations using graph convolution over pruned dependency trees[J]. Neurocomputing, 2020,411:302–312. (JCR Q2)

14.Yin Hong, Yanxia Liu*, Suizhu Yang, et al. Improving graph convolutional networks based on relation-aware attention for end-to-end relation extraction. IEEE Access, 2020,8:51315–51323. 

15.Yanxia Liu, Hongyu Shi, Sijuan Huang, Guohua Wang, Xin Yang. Early prediction of acute xerostomia during radiation therapy for nasopharyngeal cancer based on delta radiomics from CT images, Quantitative Imaging in Medicine and Surgery, 2019, 9(7): 1288-1302. (JCR Q2)

16.Liu Y, Chen X, Huang S, etc. Prediction of Acute Xerostomia in Nasopharyngeal Cancer for Radiotherapy using 3D Convolutional Neural Network, AAPM: The American Association of Physicists in Medicine Annual Meeting, 2019

17.Liu Y, Shi H, Huang S, etc. Prediction of Acute Xerostomia based on Delta Radiomics from CT images during Radiation Therapy for Nasopharyngeal Cancer, AAPM: The American Association of Physicists in Medicine Annual Meeting, 2019

18.Chen X, Liu Y, et al. Unmanned ship Path Planning Based on RRT, Lecture Notes in Computer Sciences, 2018 (EI)


        

TOP