陈宁

2021.04.22 18:11

职称 工程师 电话 62796945
邮箱 ningchen@mail.tsinghua.edu.cn

姓名:陈宁
职称:工程师

电话:62796945

邮箱:ningchen@mail.tsinghua.edu.cn

个人主页:https://scholar.google.com/citations?user=cSxeVz0AAAAJ&hl=zh-CN

教育背景:

2007,西北工业大学,学士

2012,清华大学,博士

2014,清华大学,博士后

社会兼职:

中国计算机学会 会员;IEEE 会员;

研究领域:

1. 机器学习方法及应用,包括互联网数据、生物信息宏基因组学数据、医疗电子病历数据分析2. 高性能计算平台的测试服务。

研究概况:

从事人工智能/机器学习和互联网、医疗、生物数据分析等相关领域基础理论、关键技术与应用研究,及高性能平台的测试服务工作。针对复杂数据(如多模态与关系数据)的隐含结构挖掘及预测问题,系统而深入地研究了隐层空间模型的模型表示、判别式学习、模型复杂度问题。在生物信息学数据处理方面,针对大规模基因序列数据的聚类层次树开销大、聚类效率低的问题,提出基于局部敏感哈希(LSH)和非参数化贝叶斯方法(DP-means)的高效聚类方法,是当时生物信息领域处理大规模聚类问题最高效和高准确性的方法之一。提出基于分层贝叶斯隐层空间模型的微生物关联网络预测方法,显著提高在微生物关联和微生物与环境因素关联的预测任务中的准确性和实用性。在统计学习与数据挖掘、生物信息学等领域国际顶级期刊如IEEE TPAMIIEEE TNNBioinformaticsCell Systems以及顶级会议如IJCAINIPSRECOMB等发表多篇学术论文。另获发明专利授权4项。过去几年中,受邀担任人工智能顶级国际会议NIPSICMLIJCAIAAAI的程序委员会委员或审稿人。近年来作为项目负责人,受到国家自然科学基金面上项目、青年项目、中国博士后基金等多个国家级项目资助;并作为核心成员参与国家自然科学基金地区合作重点、国际合作重点项目等多个国家级项目中。

奖励与荣誉:

2017年中国计算机学会自然科学奖一等奖(排名第3

2012年中国人工智能学会优秀博士论文奖

部分科研成果:

[1] Yuqing Yang, Xin Wang, Congmin Zhu, Ning Chen*, Ting Chen*. Inferring multiple metagenomic association networks based on variation of environmental factors, in Genomics, Proteomics &Bioinformatics, 2020. in press. (JCR Q1,IF 7.15)

[2] Kaikun Xie, Zehua Liu, Ning Chen*, Ting Chen*. redPATH: Reconstructing the Pseudo Development Time of Cell Lineages in Single-Cell RNA-Seq Data and Applications in Cancer, in Genomics, Proteomics &Bioinformatics, 2020. in press.(JCR Q1,IF 7.15)

[3] Ning Chen*, Jun Zhu, Jianfei Chen, Ting Chen. Dropout training for SVMs with data augmentation. In Frontiers of Computer Science, Vol. 12(4), pp 694–713, 2018. (JCR Q3,IF 1.105,)[SCI: GK4FX,EI:20175004520496]

[4] Linhao Jiang, Yichao Dong, Ning Chen*, Ting Chen*. DACE: A Scalable DP-means Algorithm for Clustering Extremely Large Sequence Data. Bioinformatics. 33(6):834-842 (ISSN: 1367-4811), 2017. (JCR Q1,IF 5.6) [SCI:EQ3QB]

[5] Yuqing Yang, Ning Chen*, Ting Chen*. Inference of environmental-factor–microbe and microbe–microbe associations from metagenomics data using a hierarchical Bayesian statistical model. Cell Systems, Volume 4, Issue 1, p129–137.e5, 25 January 2017. (JCR Q1, IF 8.982) [SCI:EN1PV]

[6] Ning Chen*, Jun Zhu,Fei Xia,Bo Zhang,Discriminative Relational Topic Models,IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI),2015,37(5):973-986。(JCR Q1, CCF A, IF 17.86)[SCI: CF4PS,EI: 20151500731743]

[7] Ning Chen*,Jun Zhu,Fuchun Sun,Bo Zhang,Learning Harmonium Models With Infinite Latent Features,IEEE Transactions on Neural Networks and Learning Systems (TNNLS),,2014,25(3):520-532。(JCR Q1, CCF B, IF 11.8)[SCI:AB7QJ,EI: 20141017435354]

[8] Ning Chen*, J. Zhu, F. Sun, E. P. Xing. Large Margin Predictive Latent Subspace Learning for Multi-view Data Analysis, IEEE Trans. on Pattern analysis and Machine Intelligence (TPAMI), Vol. 34(12), 2365 – 2378, 2012.(JCR Q1, CCF A, IF 17.86)[SCI: 021VO,EI:20124415615130]

[9] Xingxing Wei*, Siyuan Liang, Ning Chen*and Xiaochun Cao. Transferable Adversarial Attacks for Image and Video Object Detection, in International Joint Conference on Artificial Intelligence (IJCAI), 2019. (CCF A) [EI: 20194607696696]

[10] Tian Tian, Ning Chen, and Jun Zhu. Learning Attributes from the Crowdsourced Relative Labels, In Proc. of Thirty-First AAAI Conference on Artificial Intelligence (AAAI), San Francisco, California, 2017. (CCF A) [EI:20174104242803]

[11] Ning Chen, J. Zhu, J. Chen, Bo Zhang. Dropout Training for Support Vector Machines. Proceedings of the 28th AAAI conference , 2014. (CCF A)[EI:20144400144125]

[12] Ning Chen, J. Zhu, F. Xia, B. Zhang. Generalized Relational Topic Models with Data Augmentation, in Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI), 2013, Beijing, China. (CCF A)[EI:20140617282626]

[13] Ning Chen, J. Zhu, E. P. Xing. Predictive Subspace Learning for Multi-view Data: A large Margin Approach, in Proceedings of the Advances in Neural Information Processing Systems (NIPS), Vancouver, 2010. (CCF A) [EI:20121915006617]

[14] Bei Chen, Ning Chen*, Jun Zhu, Jiaming Song, Bo Zhang. Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation,the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), phoenix, 2016.2.12-2016.2.17. (CCF A) [EI:20165203195702]

[15] Jianqiao Wangni, Ning Chen*. Nonlinear Feature Extraction with Max-Margin Data Shifting,the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), phoenix, 2016.2.12-2016.2.17. (CCF A) [EI:20165203195771]

F. Xia, Ning Chen, Jun Zhu, Aonan Zhang, Xiaoming Jin. Max-margin latent feature relational models for entity-attribute networks. in International Joint Conference on Neural Networks 2014. (CCF C) [EI:20144500172116]



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