Huanhuan Chen is a professor in School of Computer Science, University of Science & Technology of China (USTC), Hefei, China. He received the B.Sc. degree from USTC, Hefei, China, in 2004, and Ph.D. degree, sponsored by Dorothy Hodgkin Postgraduate Award, in computer science at the University of Birmingham, Birmingham, UK, in 2008. He worked in University of Birmingham and University of Leeds in the UK from 2008 to 2012, respectively. From 2012, he has been selected to young thousand talent program by central government and became a professor in USTC.
His PhD thesis "Diversity and Regularization in Neural Network Ensembles" has received 2011 IEEE Computational Intelligence Society Outstanding PhD Dissertation award (the only winner) and 2009 CPHC/British Computer Society Distinguished Dissertations Award (the runner up).
His work “Probabilistic Classification Vector Machines” on Bayesian machine learning published in IEEE Transactions on Neural Networks, has been awarded as IEEE Transactions on Neural Networks Outstanding 2009 Paper Award (bestowed in 2011, and only one paper in 2009 receive this award).
His research interests include computational intelligence, statistical machine learning, data fusion, neural networks, Bayesian inference and evolutionary computation, etc.
1) Model-based Kernel for Efficient Time Series Analysis , KDD'13 , 2013 ,
2) Probabilistic Classification Vector Machines (IEEE Transactions on Neural Networks Outstanding 2009 Paper Award) , IEEE Transactions on Neural Networks , 2009 , 2009, no. 6
3) Learning in the Model Space for Cognitive Fault Diagnosis , IEEE Transactions on Neural Networks and Learning , 2013 , DOI: TNNLS.2013.2256797
4) Multi-objective Neural Network Ensembles based on Regularized Negative Correlation Learning , IEEE Transactions on Knowledge & Data Engineering , 2010 , 2010, no. 12
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