教師信息個人照片
姓    名王楊性    別  男

出生年月
最終學位博士
畢業學校

新南威爾士大學

從事專業

模式識別,機器學習

職    務
所屬院系

計算機科學與技術系

所屬科室(研究所)

多媒體計算所

職     稱  教 授
聯系方式
辦公電話
E-mail

yangwang@hfut.edu.cn

通訊地址

安徽省合肥市蜀山區丹霞路485號合肥工業大學翡翠湖校區計算機與信息學院

郵  編230601
簡    歷

本科畢業于大連理工大學并于2015年9月在澳大利亞新南威爾士大學計算機與工程學院獲得博士學位,現為合肥工業大學多媒體計算所 教授,黃山青年學者。擔任信息搜索領域國際頂級雜志 ACM Transactions on Information Systems (ACM TOIS, CCF Rank A) 副主編,在模式識別相關領域頂級雜志與會議上發表文章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. 獲得2014年亞太數據挖掘大會 (PAKDD)最佳論文獎亞軍,以及Neurocomputing 杰出審稿人獎。任多個頂級會議程序委員會委員例如 IJCAI,AAAI, ACM Multimedia, ACM Multimedia Asia, ECMLPKDD etc 同時為荷蘭阿姆斯達丹大學 (University of Amsterdam, Netherlands)博士學位海外評審委員會委員,擔任15個以上頂級雜志審稿人例如 IEEE TPAMI, IEEE TIP, IEEE TNNLS, Machine Learning (Springer), Pattern Recognition (Elsevier) ACM TKDD, IEEE TMM. 擔任ACM Transactions on Multimedia (ACM TOMM), IEEE Multimedian Magazine, 等雜志首席客座主編。Google 學術引用2000+, H-因子 25.目前主持國家自然科學基金一項以及黃山青年學者人才項目一項。


詳細信息 請參考個人主頁:https://sites.google.com/view/wayag/home

研究方向

模式識別,機器學習,多媒體計算。



教學工作


獲獎情況

Best Research Paper Runner-up Award, PAKDD 2014. Taiwan. 
主要論著

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: 120

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: 141

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: 102

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: 118

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: 92

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: 69

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: 95 

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: 66

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:32

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:109.

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.




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