任玉丹

职称:副教授/硕士生导师

个人简介:

      20193月毕业于西北工业大学自动化学院,获得工学博士学位,2015年9月-2018年2月在澳大利亚昆士兰医学院及昆士兰大学访问学习。近年来致力于医学图像分析,计算神经科学,认知与神经科学启发的人工智能等方向的研究。主持国家自然科学基金1项、陕西省自然科学基金1项,同时作为参与了多项国家自然科学基金项目以及国家重点研发计划课题。近五年在Nature Communications(第一作者,影响因子12.124)Human Brain MappingCortexMICCAI等国际权威期刊及会议发表学术论文16篇,其中第一作者发表论文累计影响因子27.2

主要研究方向:医学图像分析,计算神经科学,认知与神经科学启发的人工智能等。

欢迎加入我的科研团队,工作邮箱:yudan.ren@nwu.edu.cn


部分科研成果:

1. Ren, Y., Nguyen, V. T., Sonkusare, S., Lv, J., Pang, T., Guo, L., ... & Guo, C. C*. (2018). Effective connectivity of the anterior hippocampus predicts recollection confidence during natural memory retrieval. Nature communications, 9(1), 1-10.

2. Ren, Y., Fang, J., Lv, J., Hu, X., Guo, C. C., Guo, L., ... & Liu, T*. (2017). Assessing the effects of cocaine dependence and pathological gambling using group-wise sparse representation of natural stimulus FMRI data. Brain imaging and behavior, 11(4), 1179-1191.

3. Ren, Y., Nguyen, V. T., Guo, L., & Guo, C. C*. (2017). Inter-subject functional correlation reveal a hierarchical organization of extrinsic and intrinsic systems in the brain. Scientific reports, 7(1), 1-12.

4. Ren, Y., Guo, L., & Guo, C. C*. (2019). A connectivity-based parcellation improved functional representation of the human cerebellum. Scientific reports, 9(1), 1-12.

5. Ren, Y., Lv, J., Guo, L., Fang, J., & Guo, C. C*. (2017). Sparse coding reveals greater functional connectivity in female brains during naturalistic emotional experience. PloS one, 12(12), e0190097.

6. Ren, Y.*, Hu, X., Lv, J., Quo, L., Han, J., & Liu, T. (2016, April). Identifying autism biomarkers in default mode network using sparse representation of resting-state fMRI data. In 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) (pp. 1278-1281). IEEE.

7. Ren, Y.*, & Wang, S. (2019). Exploring Functional Connectivity Biomarker in Autism Using Group-Wise Sparse Representation. In Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy (pp. 21-29). Springer, Cham.

8. Ren, Y.*, Tao, Z, Zhang, W., & Liu, T. (2021, April). Modeling Hierarchical Spatial and Temporal Patterns of Naturalistic fMRI Volume via Volumetric Deep Belief Network with Neural Architecture Search. In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI). IEEE. 口头报告.

9. Tao, Z, Ren, Y.*, Zhang, W., & Liu, T. (2020, December). Identifying Hierarchical Individual Functional Network under Naturalistic Paradigm via Two-stage DBN with Neural Architecture Search. In 2020 4th International Symposium on Image Computing and Digital Medicine (ISICDM). 口头报告.

部分科研项目:

1. 基于深度神经网络的自然范式脑功能网络分析框架及其应用,国家自然科学基金青年项目,主持。

2. 基于自然范式功能磁共振成像的大脑功能网络检测分析及其应用,陕西省科技厅自然基础研究项目,主持。


教学情况:

本科教学:数字电子系统,C语言与嵌入式系统,计算机安全

研究生教学:数字视频图像处理


其他信息:

担任Frontiers in Neuroscience杂志的Review Editor,以及NeuroImage、Frontiers in Neurology、Frontiers in Psychology、Brain Topography、MICCAI、ISBI等国际权威期刊及会议的审稿人


地址:西安市长安区郭杜教育科技产业园区学府大道1号  邮编:710127

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