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陈欢欢
单位:计算机科学与技术学院
地址:中国科学技术大学计算机科学与技术学院
邮编:230026
电话:
个人主页: http://staff.ustc.edu.cn/~hchen/
实验室介绍:
 
个人简历 Personal resume
    陈欢欢,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,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、ECAI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,申请人获得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)。
    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、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: 
01. IEEE Transactions on Neural Networks and Learning Systems,Associate Editor 副编(2016-) 
02. IEEE Computational Intelligence Society Social Media Committee Chair, 2015 
03. IEEE World Congress on Computational Intelligence (IEEE WCCI) Publications Integrity Chair, 2016
 
研究方向 Research direction
1、计算智能
2、机器学习
3、数据挖掘
 
招生信息 Enrollment information
对计算智能、机器学习与数据挖掘感兴趣,并有一定数学背景的本科生、硕士、博士研究生。联系邮件地址为:hchen@ustc.edu.cn
 
论文专著 The monograph
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
 
报考意向 Ambition
 
 
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