清华合成与系统生物学中心
Tsinghua Center for Synthetic and Systems Biology
chenning
陈宁 (Ning Chen)

助理研究员
清华大学,清华信息科学与技术国家实验室(筹),
生物信息学部/合成与系统生物学中心







联系方式:
电子邮件:
ningchen@mail.tsinghua.edu.cn

教育背景:
2007.09-2012.07,清华大学,计算机科学与技术,博士
2003.09-2007.07,西北工业大学,计算机科学,学士

工作经历:
2012.09-2014.07,清华大学,计算机科学与技术系(博士后)

研究方向:
My main research interests lie in both machine learning and computational biology. For machine learning, I am interested in developing Predictive Latent Variable Models for learning discriminative and interpretable latent representations using large margin learning in the formalism of probabilistic graphical models based on multi-view data and relational network data; For computational biology, I am interested in developing statistical machine learning techniques for large-scale metagenomic data analysis as well as discovering the underlying biological interpretations of metagenomics.

期刊论文:
1. Ning Chen, J. Zhu, F. Xia and B. Zhang. Discriminative Relational Topic Models, IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), 2015. (in press)
2. Ning Chen, F. Sun, B. Zhang. Learning Harmonium Models with Infinite Latent Features, IEEE Transaction on Neural Networks and Learning Systems (TNNLS), Vol. 25(3),520–532, 2014.
3. Ning Chen, J. Zhu, F. Sun, E.P. Xing. Large Margin Predictive Latent Subspace Learning for Multi-view Data Analysis, IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 34(12), 2365–2378, 2012.
4. Ning Chen, J. Zhu, J. Chen and B. Zhang. Dropout Training for Support Vector Machines, AAAI conference on Arti_cial Intelligence (AAAI), 2014.
5. Ning Chen, J. Zhu, F. Xia and B. Zhang. Generalized Relational Topic Models with Data Augmentation, in Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, 2013.
6. Ning Chen, J. Zhu, E.P. Xing. Predictive Subspace Learning for Multi-view Data: A Large Margin Approach, in Proceedings of Advances in Neural Information Processing Systems (NIPS), Vancouver, Canada, 2010.
7. F. Xia, Ning Chen, et. al. Max Margin Latent Feature Relational Models for Entity-Attribute Networks. in International Joint Conference on Neural Networks (IJCNN), Beijing, 2014.


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