个人简历

Dr. Huawen Liu is a professor with the College of Mathematics and Computer Sciences of Zhejiang Normal University, P.R.China since July, 2010. He received his Ph.D. and Ms.D. of Computer Science from Jilin University, P.R.China. He was a post-doctor at University of South Australia from 2012 to 2013, and a visiting fellow at University of Texas at San Antonio from 2018 to 2019. His research interests are in the fields of multimedia systems, feature selection, data mining, machine learning and their applications in image processing and multimedia data. He has published above 30 refereed papers in international journals and conference proceedings, including IEEE Trans Neural Netw & Learning Syst., IEEE Trans. on Cybernetics, IEEE Trans. on Multimedia, IEEE Trans. on Syst. Man and Cybern., Pattern Recognition, Information Sciences, and so on. He has served as an editor of J. Fuzzy and Intelligent Systems from 2016. He served a lead guest editor of two international journals including Neural Computing and Applications (NCAA) and Computing and Informatics (CAI), and served as the organising chair of the 2015 National Conf. of Theoretical Computer Science, the 2014 China Conference on Data Mining, and a PC member for several conferences such as ADMA, ICBK and KSEM.
教育经历
2004-9~2007-7
吉林大学 | 计算机科学与技术 | 硕士学位 | 硕士研究生毕业
2007-9~2010-6
吉林大学 | 计算机科学与技术 | 博士学位 | 博士研究生毕业

工作经历
2018-1~2019-1
Department of Computer Science | University of Texas at San Antonio | Visiting fellow
2012-3~2013-2
澳大利亚南澳大学 | 访问学者
2013-6~2015-6
数学所 | 中科院数学与系统科学研究院 | 博士后
2010-7~至今
数理与信息工程学院 | 浙江师范大学 | 讲师、副教授、教授
科研项目
面向大数据的特征选择算法关键技术研究, 结题
多标记数据分类及其特征选择算法研究, 2011-08-01, 结题
多源数据挖掘的关键技术研究, 2015-08-01, 在研
著作成果
office高级应用
专利
一种用于智能教学的计算机辅助测试方法
获奖信息
吉林省科学技术奖（二等奖）
授课信息
数据挖掘
Python程序设计
C语言程序设计

研究领域

人工智能、机器学习、数据挖掘""

近期论文

Huawen Liu, Xuelong Li, Shichao Zhang.Learning Instance Correlation Functions for Multi-label Classification.IEEE Trans. on Cybernetics.2017,47(2):499-510
Huawen Liu, Lin Liu, Thuc Duy Le, Ivan Lee, Shiliang Sun, Jiuyong Li.Nonparametric Sparse Matrix Decomposition for Cross-View Dimensionality Reduction.IEEE Trans. Multimedia.2017,19(8):1848-1859
Huawen Liu, Xindong Wu, Shichao Zhang.Neighbor Selection for Multilabel Classification.Neurocomputing.2016,182:187-196
Huawen Liu, Zongjie Ma, Shichao Zhang, Xindong Wu.Penalized Partial Least Square Discriminant Analysis with l1-norm for Multi-label Data.Pattern Recognition.2015,48(5):1724-1733
基于kNN的多标签分类预处理方法.计算机科学.2015(第5期):106-108，131
Regression analysis of locality preserving projections via sparse penalty.Information Sciences.2015,Vol.303:1-14
Regularized partial least squares for multi-label learning.International Journal of Machine Learning and Cybernetics.2018,Vol.9(No.2):335-346
Fisher discrimination based low rank matrix recovery for face recognition.Pattern Recognition.2014,Vol.47(No.11):3502-3511
抵制多敏感属性关联攻击的(l,m)-多样性模型.小型微型计算机系统.2013(第6期):1387-1391
访问控制策略的分类方法研究.武汉理工大学学报(信息与管理工程版).2011(第6期):878-882
A multi-label classification algorithm based on label-specific features.Wuhan University Journal of Natural Sciences.2011,Vol.16(No.6):520-524
An ensemble multi-label classification method using feature selection..Computer Engineering & Science / Jisuanji Gongcheng yu Kexue.2013,Vol.35(No.10):130-136
miRLAB: An R Based Dry Lab for Exploring miRNA-mRNA Regulatory Relationships.PLOS ONE.2015:2015
An Ensemble Method for High-Dimensional Multilabel Data.Mathematical Problems in Engineering.2013,Vol.2013
基于邻域离散度的异常点检测算法^*.计算机科学与探索.2016,第10卷(第12期):1763-1772
Penalized partial least square discriminant analysis with l(1)-norm for multi-label data.PATTERN RECOGNITION.2015,Vol.48(No.5):1724-1733
A NEW SUPERVISED FEATURE SELECTION METHOD FOR PATTERN CLASSIFICATION.Computational intelligence.2014,Vol.30(No.2)
Learning Instance Correlation Functions for Multilabel Classification.IEEE TRANSACTIONS ON CYBERNETICS.2017,Vol.47(No.2):499-510
Foreword to the special issue on recent advances on pattern recognition and artificial intelligence.NEURAL COMPUTING & APPLICATIONS.2018,Vol.29(No.1):1-2
基于信息增益的多标签特征选择算法.计算机科学.2015(第7期):52-56
一种基于局部加权回归的分类方法`*.计算机工程与科学.2015,第37卷(第10期):1959-1964
网站设计教学改革中的慕课资源建设.计算机教育.2016(第3期):43-45
A Comparison of Outlier Detection Techniques for High-Dimensional Data.INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS.2018,Vol.11(No.1):652-662
Neighbor selection for multilabel classification.Neurocomputing.2016,Vol.182:187-196
基于奇异值分解—偏最小二乘回归的多标签分类算法.计算机应用.2014(第7期):2058-2060，2089
Nonparametric Sparse Matrix Decomposition for Cross-View Dimensionality Reduction.IEEE Transactions on Multimedia.2017,Vol.19(No.8):1848-1859
基于特征选择的集成多标签分类算法.计算机工程与科学.2013(第10期):137-143
Differential Evolution for Prediction of Longitudinal Dispersion Coefficients in Natural Streams.Water Resources Management.2013,Vol.27(No.15):5245-5260
A Multi-Label Classification Algorithm Based on Label-Specific Features.Wuhan University Journal of Natural Sciences.2011(第6期):520-524
Efficient Outlier Detection for High-Dimensional Data.IEEE Transactions on Systems, Man, and Cybernetics: Systems.2017:1-11
Noisy data elimination using mutual k-nearest neighbor for classification mining.Journal of Systems and Software.2012,Vol.85(No.5):1067-1074
MLSLR: Multilabel Learning via Sparse Logistic Regression..Inform. Sci..2014,Vol.281:310-320
MAGE: A semantics retaining K-anonymization method for mixed data.Knowledge-Based Systems.2014,Vol.55:75-86
Efficient Ordering Heuristics in Binary Decision Diagrambased Fault Tree Analysis.QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL.2013,Vol.29(No.3):307-315
基于典型相关分析的复杂网络模块挖掘算法.吉林大学学报(工学版).2013(第2期):424-428
线上线下混合式教学中学习评价机制研究.中国信息技术教育.2018(第8期):95-97
Huawen Liu, Shichao Zhang, Xindong Wu.MLSLR: Multilabel Learning via Sparse Logistic Regression.Information Science.2014,281:310-320
2016-10~至今
J. Fuzzy and Intelligent Systems
2015-1~至今
中国计算机学会（CCF）理论计算机科学专委会委员