陈欢欢,男,1982年1月生,博士,中国科学技术大学计算机学院教授,博士生导师。
人物经历
获得荣誉
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。由于在神经网络与学习系统等方面的贡献,申请人获得2015年度国际神经网络学会(InternationalNeuralNetworkSociety(INNS))年度青年科学家奖(YoungInvestigatorAward)。
获奖时间
1.2019年中国科学院优秀导师奖
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
主要研究方向
科研项目
主持承担了多项科研项目,包括国家重点研发计划“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、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。
科研成果
在国内外重要学术期刊和国际学术会议上发表论文20余篇,包括IEEE Transaction on Neural Networks、IEEE Transaction on Knowledge and Data Engineering、IEEE Transaction on Evolutionary Computation、IJCAI、KDD、ECAI等。其中,2009年在IEEE Transaction on Neural Networks上发表的论文获得最佳论文奖。
论文专著
陈欢欢教授的论文专著包括:
1. Probabilistic Classification Vector Machines (IEEE Transactions on Neural Networks Outstanding 2009 Paper Award) - IEEE Transactions on Neural Networks - 2009 - 2009, no. 6
2. Model-based Kernel for Efficient Time Series Analysis - KDD'13 - 2013 -
3. Multi-objective Neural Network Ensembles based on Regularized Negative Correlation Learning - IEEE Transactions on Knowledge & Data Engineering - 2010 - 2010, no. 12
4. Learning in the Model Space for Cognitive Fault Diagnosis - IEEE Transactions on Neural Networks and Learning - 2013 - DOI: TNNLS.2013.2256797
5. Regularized Negative Correlation Learning for Neural Network Ensembles - IEEE Transactions on Neural Networks - 2009 - 2009, no. 12
6. Predictive Ensemble Pruning by Expectation Propagation - IEEE Transactions on Knowledge & Data Engineering - 2009 - 2009, no. 7
7. Evolving Least Squares Support Vector Machines for Stock Market Trend Mining - IEEE Transactions on Evolutionary Computation - 2009 - 2009, no. 2
8. Buried Utility Pipeline Mapping Based on Multiple Spatial Data Sources: A Bayesian Data Fusion Approach - IJCAI'11 - 2011 - 2011
9. Buried Utility Pipeline Mapping based on Street Survey and Ground Penetrating Radar - ECAI'10 - 2011 - 2011
10. Probabilistic Conic Mixture Model and its Applications to Mining Spatial Ground Penetrating Radar Data - Workshop in SIAM Conference on Data Mining (WSDM) - 2010 - 2010
11. Probabilistic Robust Hyperbola Mixture Model for Interpreting Ground Penetrating Radar Data - IEEE World Congress on Computational intelligence - 2010 - 2010
12. Evolutionary Random Neural Ensemble based on Negative Correlation Learning - IEEE Congress on Evolutionary Computation - 2007 - 2007
社会任职
陈欢欢教授在学术界担任多项重要职务,包括:
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS)副编(2016-)
- IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)副编(2016-)
- IEEE Computational Intelligence Society Student Activities Committee Chair(2015-)
- IEEE World Congress on Computational Intelligence (IEEE WCCI) Publications Integrity Chair(2016)
参考资料 1
- 教育部 — 教育部网站