斯博国际app

教师信息个人照片
姓    名王杨性    别  男

出生年月
最终学位博士
毕业学校

新南威尔士大学

从事专业

模式识别,机器学习

职    务
所属院系

计算机科学与技术系

所属科室(研究所)

多媒体计算所

职     称  教 授
联系方式
办公电话
E-mail

yangwang@hfut.edu.cn

通讯地址

安徽省合肥市蜀山区丹霞路485号合肥工业大学翡翠湖校区斯博国际app

邮  编230601
简    历

本科毕业于大连理工大学并于2015年9月在澳大利亚新南威尔士大学计算机与工程学院获得博士学位,现为合肥工业大学多媒体计算所 教授,黄山青年学者。担任信息搜索领域国际顶级杂志 ACM Transactions on Information Systems (ACM TOIS, CCF Rank A) 副主编,在模式识别相关领域顶级杂志与会议上发表文章60篇,例如IEEE TIP, IEEE TNNLS, IEEE TMM, IEEE TCSVT, ACM TOIS, IEEE TKDE, IEEE TCYB, Neural Networks, Pattern Recognition, VLDB Journal, IJCAI, ACM SIGIR, ACM Multimedia, IEEE ICDM, ACM CIKM. 获得2014年亚太数据挖掘大会 (PAKDD)最佳论文奖亚军,以及Neurocomputing 杰出审稿人奖。任多个顶级会议程序委员会委员例如 IJCAI,AAAI, ACM Multimedia, ACM Multimedia Asia, ECMLPKDD etc 同时为荷兰阿姆斯达丹大学 (University of Amsterdam, Netherlands)博士学位海外评审委员会委员,担任15个以上顶级杂志审稿人例如 IEEE TPAMI, IEEE TIP, IEEE TNNLS, Machine Learning (Springer), Pattern Recognition (Elsevier) ACM TKDD, IEEE TMM. 担任ACM Transactions on Multimedia (ACM TOMM), IEEE Multimedian Magazine, 等杂志首席客座主编。Google 学术引用1900+, H-因子 25.目前主持国家自然科学基金一项以及黄山青年学者人才项目一项。


详细信息 请参考个人主页:https://sites.google.com/view/wayag/home

研究方向

模式识别,机器学习,多媒体计算。



教学工作


获奖情况

Best Research Paper Runner-up Award, PAKDD 2014. Taiwan. 
主要论著

Y.Wang et al., Iterative Views Agreement: An Iterative Low-Rank based structured Optimization Method to Multi-view Spectral Clustering, IJCAI 2016, New York. Google Scholar citations: 116

Y.Wang et al., Robust Subspace Clustering for Multi-view Data by Exploiting Correlations Consensus, IEEE Trans. Image Processing, 24(11):3939-3949, 2015. Google Scholar citations: 138

Y.Wang et al., Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval. IEEE Trans. Image Processing, 26(3):1393-1404,2017. google scholar citations: 101

Y.Wang et al. Multi-view Spectral Clustering via Structured Low-Rank Matrix Factorizations. IEEE Trans. Neural Networks and Learning Systems, 29(10):4833-4843, 2018. Google scholar citations: 114

Y.Wang et al., Unsupervised metric fusion over Multiview Data by Graph Random Walk based cross-view diffusion. IEEE Trans. Neural Networks and Learning Systems,28(1):57-70, 2017. Google scholar citations: 91

L. Wu, Y. Wang*, L. Shao. Cycle-Consistent Deep Generative Hashing for Cross-modal Retrieval IEEE Trans. Image Processing 28(4):1602-1612,2019.

Google scholar citations: 67

L. Wu, Y. Wang*, J. Gao et al., Deep Attention-based Spatially Recursive Neural Networks for Fine-grained Visual Recognition. IEEE Trans. Cybernetics, 49(5):1791-1802,2019. Google Scholar Citations: 90 

Y. Wang et al., Effective Multi-Query Expansions: Robust Landmark Retrieval, ACM Multimedia 2015, 79-88, Brisbane, Australia.     

Google Citations: 52

L. Wu, Y. Wang*, J. Gao et al., Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification. IEEE Trans. Multimedia, 21(6):1412-1424, 2019,Google Citations: 64

Y. Wang et al., LBMCH:Learning Bridging mapping for cross-modal Hashing, ACM SIGIR 2015, Google Citations: 65

Y. Chen, P. Ren, Y. Wang*, Maarten de Rijke. Bayesian Personalized Feature Interaction Selection for Factorization Machines, ACM SIGIR 2019, 665-674,Pairs, France. 

L. Wu, Y. Wang*,L. Shao, M. Wang. 3-D PersonVLAD: Learning Deep Global Representations for Video-Based Person Reidentification. IEEE Trans. Neural Networks and Learning Systems, 30(11):3347-3359,2019, Google Citations:31

L. Wu, Y. Wang*, H. Yin, M. Wang, L. Shao. Few-Shot Deep Adversarial Learning for Video-based Person Re-identification. IEEE Trans. Image Processing, 29(1):1233-1245,2020.

L. Wu, Y. Wang*, J. Gao et al. Deep Adaptive Feature Embedding with Local Sample Distribution for Person Re-identification. Pattern Recognition, 73:275-288,2018. Google Citations:108.

Y. Chen, Y. Wang*, X. Zhao, H.Yin, Maarten de Rijke. Local Variational Feature-based Similarity Models for Recommending Top-N New Items. ACM Trans. Information Systems (ACM TOIS), 2019.