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华侨大学计算机科学与技术学院导师教师师资介绍简介-范文涛

本站小编 Free考研考试/2021-05-12




学历:
博士研究生




职称:
副教授




电子邮箱:
fwt@hqu.edu.cn



























个人简介
范文涛:男,工学博士,副教授,硕士研究生导师,福建省引进高层次人才。分别于2009年和2014年在加拿大康考迪亚大学 (Concordia University) 获得信息系统安全(Information Systems Security)硕士和电子与计算机工程(Electrical and Computer Engineering)博士学位。在攻读博士期间获得加拿大魁北克省自然与技术研究基金(FQRNT) 博士研究生奖学金,以及康考迪亚大学工程与计算机科学学院高素质新博士研究生特别奖学金。并于2012年分别获得国际通信和信息技术会议 (ICCIT 2012) ,以及国际多媒体通信、服务与安全会议 (MCSS 2012)最佳论文奖。博士毕业后曾获得加拿大自然科学与工程研究理事会(NSERC)博士后奖学金。2014年7月起在华侨大学计算机科学与技术学院工作。近年来发表被SCI/EI检索的国际期刊论文以及国际会议论文50余篇。长期担任以下国际核心期刊审稿人:IEEE Transactions on Neural Networks and Learning Systems,IEEE Transactions on Knowledge and Data Engineering,Pattern Recognition,Neurocomputing,Computer Vision and Image Understanding Registration,Journal of Electronic Imaging。
研究方向:
模式识别与机器学习、深度学习、计算机视觉、数据挖掘、生物信息。
学生要求:
对模式识别、机器学习、深度学习和计算机视觉等研究领域感兴趣。勤奋刻苦,具备较强的自学能力和钻研精神。有较强的编程能力(如C、C++、Matlab等)。
主持的科研项目:
华侨大学高层次人才引进科研启动项目,600005-Z15Y0016,基于分层Pitman-Yor过程的高维数据聚类方法,2015/06-2017/05,10万元。
国家自然科学基金青年项目,**,分层贝叶斯非参数模型的聚类方法,2016/01-2018/12,19万元。
华侨大学中青年教师科技创新资助计划,ZQN-PY510,基于方向混合模型的高维方向数据的聚类分析,2017/10-2021/09,40万元。
论文发表情况(部分):
一、学术著作章节:
W. Fanand N. Bouguila, “Recognition and Clustering of Dirichlet Mixtures”, in Wiley Encyclopedia of Electrical and Electronics Engineering, John Wiley & Sons, Inc., 2015
W. Fanand N. Bouguila, “Incremental Learning of an Infinite Beta-Liouville Mixture Model for Video Background Subtraction”, in Background Modeling and Foreground Detection for Video Surveillance, T. Bouwmans et al. (Eds.), Chapman and Hall/CRC, 2014.
二、国际期刊论文:
W. Fan, H. Sallay, N. Bouguila, “Online Learning of Hierarchical Pitman-Yor Process Mixture of Generalized Dirichlet Distributions with Feature Selection”, IEEE Transactions on Neural Networks and Learning Systems, Vol. 28 (9), pp. 2048-2061, 2017
W. Fan, F. R. Al-Osaimi, N. Bouguila, J. Du: "Proportional Data Modeling via Entropy-Based Variational Bayes Learning of Mixture Models". Applied Intelligence. Vol. 47(2): pp.473-487, 2017
W. Fan, H. Sallay, N. Bouguila and S. Bourouis, “Variational Learning of Hierarchical Infinite Generalized Dirichlet Mixture Models and Applications”, Soft Computing, Vol. 20, pp. 979-990, 2016
W. Fan, H. Sallay, N. Bouguila and S. Bourouis, “A Hierarchical Dirichlet Process Mixture of Generalized Dirichlet Distributions for Feature Selection”, Computers & Electrical Engineering, Vol. 43, pp. 48-65,2015
W. Fanand N. Bouguila, “Expectation Propagation Learning of a Dirichlet Process Mixture of Beta-Liouville Distributions for Proportional Data Clustering”, Engineering Applications of Artificial Intelligence, Vol. 43, pp. 1-14, 2015
W. Fanand N. Bouguila, “Online Variational Generalized Dirichlet Mixture Model with Feature Selection”, Neurocomputing, Vol. 126, pp. 166-179, 2014
W. Fanand N.Bouguila, “Online Learning of a Dirichlet Process Mixture of Beta-Liouville Distributions via Variational Inference”, IEEE Transactions on Neural Networks and Learning Systems, Vol. 24, No. 11, pp. 1850-1862, 2013
W. Fanand N. Bouguila, “Non-Gaussian Data Clustering via Expectation Propagation Learning of Finite Dirichlet Mixture Models and Applications”, Neural Processing Letters, Vol. 39, pp. 115-135, 2014
W. Fanand N. Bouguila, “Variational Learning of a Dirichlet Process of Generalized Dirichlet Distributions for Simultaneous Clustering and Feature Selection”, Pattern Recognition, Vol.46, No.10, pp. 2754-2769, 2013
W. Fan, N.Bouguila and D. Ziou, “Unsupervised Feature Selection for High-Dimensional Non-Gaussian Data Clustering with Variational Inference”, IEEE Transactions on Knowledge and Data Engineering, Vol. 25, No. 7, pp. 1670-1685, 2013
W. Fanand N. Bouguila, “Infinite Dirichlet Mixture Models Learning via Expectation Propagation”, Advances in Data Analysis and Classification, Vol. 7, No. 4, pp. 465-489, 2013
W. Fanand N. Bouguila, “Variational Learning for Dirichlet Process Mixtures of Dirichlet Distributions and Applications”, Multimedia Tools and Applications, Vol. 70, No. 3, pp. 1685-1702, 2012
W. Fan, N.Bouguila and D.Ziou, “Variational Learning for Finite Dirichlet Mixture Models and Applications”, IEEE Transactions on Neural Networks and Learning Systems, Vol. 23, No. 5, pp. 762-774, 2012
W. Fanand N. Bouguila, “Novel Approaches for Synthesizing Video Textures”, Expert Systems with Applications, Vol.39, No.1, pp. 828-839, 2012
三、国际学术会议论文:
W. Fan, N. Bouguila and X. Liu, "A Hierarchical Dirichlet Process Mixture of GID Distributions with Feature Selection for Spatio-Temporal Video Modeling and Segmentation", 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2771-2775, New Orleans, LA, USA, 2017
W. Fan, F. R. Al-Osaimi, N. Bouguila, J. Du, "Accelerated variational inference for Beta-Liouville mixture learning with application to 3D shapes recognition", International Conference on Control, Decision and Information Technologies (CoDIT), pp. 394-398, Saint Julian's, Malta, 2016
W. Fan, F. R. Al-Osaimi, N. Bouguila, "A novel 3D Model Recognition Approach using Pitman-Yor Process Mixtures of Beta-Liouville Distributions", IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1986-1989, Montréal, QC, Canada, 2016
W. Fanand N. Bouguila, "A Nonparametric Hierarchical Bayesian Model and Its Application on Multimodal Person Identity Verification", International Symposium on Visual Computing (ISVC), pp. 399-409, Las Vegas, NV, USA, 2016
W. Fanand N. Bouguila, "Dynamic Textures Clustering Using a Hierarchical Pitman-Yor Process Mixture of Dirichlet Distributions”, Proc. of the IEEE International Conference on Image Processing (ICIP), Quebec City, Canada, Sep. 2015.
W. Fan, H. Sallay, N. Bouguila and J. Du, "3D Object Modeling and Recognition via Online Hierarchical Pitman-Yor Process Mixture Learning”, Proc. of the IEEE Global Conference on Signal and Information Processing (GlobalSIP), Orlando, Florida, USA, Dec. 2015.
W. Fanand N. Bouguila, “Spatio-Temporal Object Recognition Using Variational Learning of An Infinite Statistical Model”, Proc. Of the 21st European Signal Processing Conference (EUSIPCO), Marrakech, Morocco, Sep. 2013
W. Fanand N. Bouguila, “Unsupervised Feature Selection for Proportional Data Clustering Via Expectation Propagation”, Proc. Of the International Joint Conference on Neural Networks (IJCNN), Dallas, USA, Aug. 2013
W. Fanand N. Bouguila, “Learning Finite Beta-Liouville Mixture Models via Variational Bayes for Proportional Data Clustering”, Proc.Of the 23rdInternational Joint Conference on Artificial Intelligence (IJCAI), pp.1323-1329, Beijing, China, Aug. 2013
W. Fanand N. Bouguila, “Online Facial Expression Recognition Based on Finite Beta-Liouville Mixture Models”, Proc. Of the 10thConference on Computer and Robot Vision (CRV), pp. 37-44, Regina, Canada, May 2013
W. Fanand N. Bouguila, “Online Learning of a Dirichlet Process Mixture of Generalized Dirichlet Distributions for Simultaneous Clustering and Localized Feature Selection”, Journal of Machine Learning Research - Proceedings Track 25: pp. 113-128, 2012
W. Fanand N. Bouguila, “Nonparametric Localized Feature Selection via a Dirichlet Process Mixture of Generalized Dirichlet Distributions”. Proc. Of the 19thInternational Conference on Neural information processing (lCONlP), pp. 25-33, Doha, Qatar, Nov. 2012
W. Fanand N. Bouguila, “A Variational Component Splitting Approach for Finite Generalized Dirichlet Mixture Models”. Proc. Of the International Conference on Communications and Information Technology (ICCIT), pp.53-57, Tunisia, Jun. 2012. [最佳论文奖]
W. Fanand N. Bouguila, “Face Detection and Facial Expression Recognition Using A Novel Variational Statistical Framework”. Proc. Of the 5thInternational Conference on Multimedia, Communications, Services and Security (MCSS), pp. 95-106, Krakow, Poland, May 2012. [最佳论文奖]
W. Fan, N. Bouguila and D.Ziou, “Unsupervised Anomaly Intrusion Detection via Localized Bayesian Feature Selection”. Proc. Of the 11th IEEE International Conference on Data Mining (ICDM), pp. 1032-1037, Vancouver, Canada, Dec. 2011
W. Fanand N. Bouguila, “Online Video Textures Generation”. Proc. Of the 5thInternational Symposium on Visual Computing (ISVC), pp. 450-459, Las Vegas, USA, Nov. 2009


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