800x600个人简介：北京科技大学工学博士，2011年6月清华大学多维多尺度计算摄像北京市重点实验室博士后出站，并于同年7月入职北京工商大学，2012年晋升为计算机与信息工程学院副教授，硕士生导师。
科研工作经历：
2012.10 - 至今 北京工商大学 副教授
2011.07 - 2012.09 北京工商大学 讲师
2009.04 - 2011.06 清华大学 博士后
2005.09 - 2009.04 北京科技大学 工学博士
2016.02 - 2017.02 美国宾夕法尼亚大学医学院放射系 访问
联系方式
邮箱(Email)：wangyu@btbu.edu.cn
电话(Tel.)：+86-
主讲课程：信号分析与处理，科技英语写作等课程。
主要研究领域：模式识别，图像处理，计算机视觉
主要学术成果
近年来已在科学出版社出版学术专著2部，在Optics Letters、Optics Communications、Optical Engineering、Journal of Visual Communication and Image Representation、电子学报、ICPR等国际国内期刊与会议发表/录用论文30余篇，其中SCI收录7篇(一作)，EI收录18篇。目前为中国自动化学会、中国电子学会和中国人工智能学会高级会员，生物信息学与人工生命专委会委员，IEEE和计算机学会会员，CCF YOCSEF委员，Optics Letters、Optics Communications、IEEE Transactions on Instrumentation & Measurement等国际期刊审稿人。申请国家发明专利15项，其中已授权7项，已公开7项，获批软件著作权5项。主持国家自然科学基金面上项目2项，北京市自然科学基金面上项目，北京市“高创计划”青年拔尖人才资助项目，北京市高等学校青年拔尖人才培养计划项目，北京市组织部优秀人才培养资助项目，中国博士后科学基金面上项目，国家留学基金委资助项目，北京工商大学青年教师科研启动基金等项目各1项。
出版专著：
王瑜，《多模态生物特征识别——基于人脸与人耳信息》，科学出版社，2013；
王瑜，《荧光显微图像3D重建技术与应用》，科学出版社，2015.
发表文章：
[1] Yu Wang, Yongsheng Zhao, et al. A varied local edge pattern descriptor and its application to texture classification. Journal of Visual Communication and Image Representation, 2016, 34(1): 108-117.
[2] Yu Wang, Huan Jiang. Three-dimensional reconstruction of microscopic images using different order intensity derivatives. Optical Engineering, 2015, 54(2): 023103-023103.
[3] Yu Wang, Yongsheng Zhao, et al. Texture Classification Using Rotation Invariant Models on Integrated Local Binary Pattern and Zernike Moments. EURASIP Journal on Advances in Signal Processing, 2014, 182(1): 1-12.
[4] YuWang,Qionghai Dai, et al. Blinddeconvolution subject to sparse representation for fluorescence microscopy. OpticsCommunications, 2013, 286(1): 60-68.
[5] Yu Wang, Dejian He, et al. Multimodal biometrics approach using face and ear recognition to overcome adverse effects of pose changes. Journal of Electronic Imaging, 2012, 21(4): 043026-043026.
[6] Wang Yu, Ji Xiangyang, Dai Qionghai. Fourth-order Oriented Partial-differential Equations for Noise Removal of Two-photon Fluorescence Images. Optics Letters, 2010, 35(17): 2943-2945.
[7] Wang Yu, JI XiangYang, Dai QiongHai. Key Technologies of Light Field Capture for 3D Reconstruction in Microscopic Scene. Science in China Series F: Information Sciences, 2010, 53(10): 1917-1930.
[8] Yu Wang, Huan Jiang. Light field creating and imaging with different order intensity derivatives. SPIE/COS Photonics Asia 2014: Optoelectronic Imaging and Multimedia Technology III, Beijing, China, October 9-11, 2014.
[9] Yu Wang, Zhichun Mu, Hui Zeng. Block-based and Multi-resolution Methods for Ear Recognition Using Wavelet Transform and Uniform Local Binary Patterns. The 19th International Conference on Pattern Recognition (ICPR 08), Tampa, USA, 2008.
[10] 王瑜, 穆志纯, 付冬梅. 基于小波变换和规范型纹理谱描述子的人耳识别研究. 电子学报, 2010, 38(1): 239-243.
专利与软著：
[1] 戴琼海, 王瑜.一种微观光场采集与三维重建方法及装置. (授权)
[2] 戴琼海, 王瑜. 一种图像去噪方法(基于四阶偏微分方程与对比度增强). (授权)
[3] 王瑜等. 基于盲反卷积和稀疏表示的荧光显微图像复原方法和装置. (授权)
[4] 王瑜等. 一种人脸检测与跟踪方法及系统. (授权)
[5] 王瑜等. 相似图像分类方法及系统. (授权)
[6] 王瑜等. 基于局部二值模式和Zernike矩的纹理图像分类方法及系统. (授权)
[7] 王瑜等. 基于局部边缘模式的纹理图像分类方法及系统. (授权)
[8] 王瑜. 图像局部边缘模式与非边缘模式判别方法及其判别装置.
[9] 王瑜. 一种基于颜色-形状特征的自动目标跟踪方法及系统.
[10] 王瑜等. 基于图像强度各阶导数的荧光显微图像3D重建方法及装置.
[11] 王瑜等. 基于空间变化点扩散函数的荧光显微图像重建方法及系统. (授权)
[12] 王瑜等. 基于改进的分裂Bregman算法的荧光显微图像复原方法和装置.
[13] 王瑜等. 基于复合正则化技术的荧光显微图像3D重建方法及装置.
[14] 王瑜等. 一种多尺度多分辨率的方形算子边缘提取方法及装置.
[15] 王瑜等. 一种基于圆形算则的图像边缘提取方法和装置.
[16] 王瑜等. 绿色植物识别系统V1.0. 登记号: 2014SR177053.
[17] 王瑜等. 基于视频文件的车牌分析系统V1.0. 登记号: 2014SR161214.
[18] 王瑜等. 荧光显微图像显示与分析系统V1.0. 登记号: 2015SR150801.
[19] 王瑜等. 人脸识别门禁系统V1.0. 登记号: 2016SR235108.
[20] 王瑜等. 荧光显微图像显示与分析系统V2.0. 登记号: 2016SR226823.
主持项目：
[1] 融合结构和功能磁共振成像的阿尔茨海默型痴呆辅助鉴别关键技术研究, 国家自然科学基金面上资助项目(No. **)；
[2] 免于释文解释的精细图像分类新方法研究, 北京市自然科学基金面上资助项目(No. **)；
[3] 绿色植物物种识别关键技术研究, 北京市委组织部“高创计划”青年拔尖人才支持计划项目(No. 20**ZK14)；
[4] 计算机视觉中从属层对象分类关键技术研究, 北京市属高等学校高层次人才引进与培养计划项目(No.CIT&TCD)；
[5] 荧光显微样本3D重建与分析关键技术研究, 国家自然科学基金面上资助项目(No. **) (已结题) ；
[6] 3D光场显微镜基础理论研究, 北京市优秀人才培养资助项目(No. 2012D) (已结题)；
[7] 基于磁共振成像的脑部疾病的分析与诊断, 国家留学基金委公派高级研究及访问资助项目(No. 2) (已结题)；
[8] 微观光场高质量获取与三维重建研究，中国博士后科学基金面上资助项目 (No. ) (已结题)；
[9] 薄样本显微图像3D重建与分析，北京工商大学青年教师科研启动基金项目(No. QNJJ2012-22) (已结题)。
社会工作：
[1] 2012-至今，IEEE (美国电气与电子工程师协会)，会员；
[2] 2013-至今，中国自动化学会，高级会员；
[3] 2015-至今，中国电子学会，高级会员；
[4] 2013-至今，中国人工智能学会，高级会员，生物信息学与人工生命专委会委员；
[5] 2013-至今，中国计算机学会，会员；
[6] 2013-至今，中国计算机学会 YOCSEF，委员。
[7] 2010-至今，Optics Letters、Optics Communications、IEEE Transactions on Instrumentation & Measurement、Journal of Electronic Imaging等国际期刊审稿人。

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YU WANG
Ph.D., Associate Professor
School of Computer and Information Engineering
Phone: (86-10) 6898-5241
E-mail: wangyu @btbu.edu.cn
Office: Room 724, Gengyun Building, No. 11/33 Fucheng Road, Haidian District, Beijing 100048, P.R. China

Education and Employment
Oct. 2012 ~ Present Associate Professor, Beijing Technology and Business University, China
Jul. 2011 ~ Sep. 2012 Lecturer, Beijing Technology and Business University, China
Apr. 2009 ~ Jun. 2011 Postdoctor, Tsinghua University, China
Sep. 2005 ~ Jan. 2009 Ph. D., University of Science and Technology Beijing, China
Feb. 2016 ~ Feb. 2017 Visiting Scholar, School of Medicine, University of Pennsylvania, USA
Research Interests
Image processing
Pattern recognition
Computer vision
Projects
Principal Investigator
Key Technologies Research on aided discrimination of Alzheimer's disease fusing structural and functional magnetic resonance imaging. National Natural Science Foundation of China (No. **)
Key Technologies Research on 3D Reconstruction of Fluorescence Microscopic Specimen. National Natural Science Foundation of China (No. **)
Analysis and Diagnosis for Human Brain Diseases based on Magnetic Resonance Imaging. Foundation of China Scholarship Council (No. 2)
New annotation-free methods research on fine-grained image categorization. Beijing Natural Science Foundation(No. **)
Key Technologies Research on Object Categorization Belonging to Subordinate Level. The Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions (No. CIT&TCD)
Key Technologies Research on green plant recognition. Beijing Talents Fund (No. 20**ZK14)
Research on High-quality Acquisition and 3D Reconstruction for Microscopic Light Field. China Postdoctoral Science Foundation (No. )
Research on Basic Theories of 3D Light Field Microscope. Excellent Talents Training Foundation of Beijing (No. 2012D)
3D Reconstruction and Analysis on Microscopic Images of Thin Specimen. Research Foundation for Youth Scholars of Beijing Technology and Business University (No. QNJJ2012-22).
Participator
Multi-dimension Media Perception and Understanding of Data Driven. National Natural Science Foundation of China (No. **)
Research on Multimodal Biometrics Recognition Based on the Information Fusion of Face and Ear. National Natural Science Foundation of China (No. **)
Research on Ear Recognition Technologies. National Natural Science Foundation of China (No. **)
Publications
Books
[1] Yu Wang. 3D reconstruction technologies and applications of fluorescence microscopic images. China, Beijing: Science Press, 2015.10.
[2] Yu Wang. Multi-modal biometrics recognition based on face and ear. China, Beijing: Science Press, 2013.12.
Papers
[1] Yu Wang, Yongsheng Zhao, et al. A varied local edge pattern descriptor and its application to texture classification. Journal of Visual Communication and Image Representation, 2016, 34(1): 108-117.
[2] Yu Wang, Huan Jiang. Three-dimensional reconstruction of microscopic images using different order intensity derivatives. Optical Engineering, 2015, 54(2): 023103-023103.
[3] Yu Wang, Yongsheng Zhao, et al. Texture Classification Using Rotation Invariant Models on Integrated Local Binary Pattern and Zernike Moments. EURASIP Journal on Advances in Signal Processing, 2014, 182(1): 1-12.
[4] YuWang,Qionghai Dai, et al. Blinddeconvolution subject to sparse representation for fluorescence microscopy. OpticsCommunications, 2013, 286(1): 60-68.
[5] Yu Wang, Dejian He, et al. Multimodal biometrics approach using face and ear recognition to overcome adverse effects of pose changes. Journal of Electronic Imaging, 2012, 21(4): 043026-043026.
[6] Wang Yu, Ji Xiangyang, Dai Qionghai. Fourth-order Oriented Partial-differential Equations for Noise Removal of Two-photon Fluorescence Images. Optics Letters, 2010, 35(17): 2943-2945.
[7] Wang Yu, JI XiangYang, Dai QiongHai. Key Technologies of Light Field Capture for 3D Reconstruction in Microscopic Scene. Science in China Series F: Information Sciences, 2010, 53(10): 1917-1930.
[8] Yu Wang, Huan Jiang. Light field creating and imaging with different order intensity derivatives. SPIE/COS Photonics Asia 2014: Optoelectronic Imaging and Multimedia Technology III, Beijing, China, October 9-11, 2014.
[9] Yu Wang, Zhichun Mu, Hui Zeng. Block-based and Multi-resolution Methods for Ear Recognition Using Wavelet Transform and Uniform Local Binary Patterns. The 19th International Conference on Pattern Recognition (ICPR), Tampa, USA, 2008.
Chinese Patents
[1] Qionghai Dai, Yu Wang, “A method and system about image noise removal based on fourth-order partial-differential equations and contrast enhancement”, ZL5.7. (Authorized)
[2] Qionghai Dai, Yu Wang, “A method and device about acquisition and 3D reconstruction of microscopic light field”, ZL5.7. (Authorized)
[3] Yu Wang, Jiang Tongqiang, Guo Peiyuan, “A method and device about restoration of fluorescence microscopic images based on blind deconvolution and spares representation”, ZLA. (Authorized)
[4] Yu Wang, Yu Chongchong, Zhang huiyan, “A method and device about face detection and tracking”, ZLA. (Authorized)
[5] Yu Wang, Cai Qiang, Zhang huiyan, “A method and device about classification of fine-grained images”, ZLA. (Authorized)
[6] Yu Wang, Chen Yi, “A method and device about classification of texture images based on Local Binary Pattern and Zernike moments”, ZLA. (Authorized)
[7] Yu Wang, Cai Qiang, “A method and device about classification of texture images based on Local Edge Pattern”, CNA. (Authorized)
[8] Yu Wang, “A method and device about discrimination of local edge pattern and non-local edge pattern in the images”, CNA. (Opened)
[9] Yu Wang, Huan Jiang, “A method and device about 3D reconstruction of fluorescence microscopic image based on different order intensity derivatives”, CN A. (Opened)
[10] Yu Wang, Huan Jiang, “A method and device about 3D reconstruction of fluorescence microscopic image based on space variant point spread function”, CNA. (Opened)
[11] Yu Wang, Changchun Zhang, Hongbing Xiao. “A method and device about fluorescence microscopy image restoration based on improved split Bregman method”, CN 1.0. (Opened)
Professional Affiliations
IEEE Member 2011~ Present
Chinese Association of Automation, Senior Member 2012~ Present
Chinese Association for Artificial Intelligence, Senior Member 2012~ Present
China Computer Federation Member, Senior Member 2012~ Present
China Computer Federation Young Computer Scientists & Engineers Forum Committee, Member
2012~ Present