陈欢欢

电 话:

E-Mail:  hchen@ustc.edu.cn

个人主页:http://staff.ustc.edu.cn/~hchen/   


主要研究方向:机器学习、数据挖掘、计算智能、地下管网探测与数据融合、演化计算等。


陈欢欢,1982年1月生,博士、教授、博导。2004年获中国科技大学学士学位,2008年获英国伯明翰大学博士学位,现为中国科学技术大学计算机学院教授。获2011年IEEE计算智能协会优秀博士论文奖、全英杰出博士论文奖。在国外重要学术期刊IEEE Transactions on Neural Networks and Learning Systems,IEEE Transactions on Knowledge and Data Engineering,IEEE Transactions on Evolutionary Computation和人工智能领域重要国际学术会议 IJCAI、KDD、AAAI等发表论文70余篇。其中,在神经网络的国际权威期刊IEEE Transactions on Neural Networks上的论文获2012年度最佳论文奖。由于在神经网络与学习系统等方面的贡献,获得2015年度国际神经网络学会(International Neural Network Society (INNS))青年科学家奖(Young Investigator Award);培养的博士生获得2019年中国科学院院长特别奖,本人获得2019年中国科学院优秀导师奖。

主持承担了首批国家重点研发计划“大数据知识工程基础理论及其应用研究”五课题之一“知识导航中的交互机理”、国家基金委重大研究计划培育项目(已获滚动支持)、国家基金委重点项目、国家基金委面上项目、国家基金委与英国皇家学会合作交流项目、国家基金委青年项目等。


国际学术服务

  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS),Associate Editor 副编(2016-)

  • IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), Associate Editor 副编(2016-)

  • IEEE Computational Intelligence Society Student Activities Committee Chair, 2015-

  • IEEE World Congress on Computational Intelligence (IEEE WCCI) Publications Integrity Chair, 2016


获奖情况

  1. 2019年中国科学院优秀导师奖

  2. 2018年教育部自然科学二等奖

  3. 2015年国际神经网络学会青年科学家奖(International Neural Network Society (INNS) Young Investigator Award)

  4. 2009年度IEEE Transactions on Neural Networks Outstanding最佳论文奖 (2012年颁发)

  5. 2011年IEEE计算智能学会杰出博士论文奖 (Outstanding PhD Dissertation Award)

  6. 英国计算机学会杰出博士论文奖


十篇代表性论著

  1. Junyuan Hong, Yang Li, Huanhuan Chen. Variant Grassmann Manifolds: a Representation Augmentation Method for Action Recognition. ACM Transactions on Knowledge Discovery from Data, Accepted 2019.

  2. Yang Li, Junyuan Hong, Huanhuan Chen. Short Sequence Classification through Discriminable Linear Dynamical System. IEEE Transactions on Neural Networks and Learning Systems, Accepted 2019.

  3. Xiren Zhou, Huanhuan Chen, Tong Hao. Efficient Detection of Buried Plastic Pipes by Combining GPR and Electric-field Methods IEEE Transactions on Geoscience and Remote Sensing, Accepted 2019.

  4. Bingbing Jiang, Chang Li, Maarten de Rijke, Xin Yao, Huanhuan Chen. Probabilistic Feature Selection and Classification Vector Machine. ACM Transactions on Knowledge Discovery from Data, Accepted.

  5. Yang Li, Bingbing Jiang, Huanhuan Chen, and Xin Yao. Symbolic Sequence Classification in the Fractal Space. IEEE Transactions on Emerging Topics in Computational Intelligence, Accepted 2018.

  6. Bingbing Jiang, Xingyu Wu, Kui Yu, Huanhuan Chen. Joint Semi-supervised Feature Selection and Classification through Bayesian Approach. In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI'19), US, 2019.

  7. Junyuan Hong, Huanhuan Chen, Feng Lin. Disturbance Grassmann Kernels for Subspace-Based Learning. In Proceedings of the ACM SIGKDD international conference on Knowledge Discovery and Data Mining (KDD'18). , London, UK, August 19-23, 2018.

  8. Kui Yu, Lin Liu, Jiuyong Li, and Huanhuan Chen Mining Markov Blankets without Causal Sufficiency. IEEE Transactions on Neural Networks and Learning Systems, Accepted.

  9. Yaqiang Yao, Yan Liu, Zhenyu Liu Huanhuan Chen. Human Activity Recognition with Posture Tendency Descriptors on Action Snippets. IEEE Transactions on Big Data, 10.1109/TBDATA.2018.2803838.

  10. Bingbing Jiang, Zhengyu Li, Huanhuan Chen, Anthony Cohn. Latent Topic Text Representation Learning on Statistical Manifolds. IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2018.2808332.