个人信息
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


所在部门 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计算机与信息学院
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****。入选安徽省***计划， 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80篇，其中 ESI 高被引文章6篇，4篇进入top 1% 列表, 发表源包括 IEEE TPAMI, IEEE TIP, IEEE TNNLS, IEEE TMM, IEEE TCSVT, ACM TOIS, Machine Learning (Springer), IEEE TKDE, IEEE TCYB, Neural Networks, Pattern Recognition, VLDB Journal, IJCAI, AAAI, 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 TIFS, ACM TOIS (Special Issue Proposal), IEEE TNNLS, Machine Learning (Springer), Pattern Recognition (Elsevier)，ACMTKDD, IEEE TMM.担任ACM Transactions on Multimedia (ACM TOMM), IEEE Multimedian Magazine,等杂志首席客座主编. IEEE ICME (CCF Rank B) 2021, special track (Knowledge Driven Multi-modal Deep Analysis for Multimedia), PC Chair.Google scholar学术引用3000+,H-因子 26.目前主持国家自然科学基金两项（含通用联合重点基金子课题一项）以及黄山****人才项目一项。

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

请访问以下链接 了解我的招生要求：
https://sites.google.com/view/wayag/call-for-postgraduates

　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
(* denotes the corresponding author)
Yang Wang.Survey on Deep Multi-modal Data Analytics: Collaboration, Rivalry and Fusion,ACM Trans. Multimedia Computing, Communications and Applications, 17(1), 2021.
X. Li, Yang Wang*, J. Ouyang, Meng Wang.Topic Extraction from Extremely Short Texts with Variational Manifold Regularization. Machine Learning, 2021, Springer.
Y. Wei, Z. Zhang*, Yang Wang*, Mingliang Xu, Y. Yang, Shuicheng Yan, Meng Wang. DerainCycleGAN: Rain Attentive CycleGAN for Single Image Deraining and Rainmaking. IEEE Trans. Image Processing, 2021.
B. Qian, Yang Wang*, R. Hong, Meng Wang, Ling Shao. Diversifying Inference Path Selection: Moving-Mobile-Network for Landmark Recognition. IEEE Trans. Image Processing, 2021.
L. Wu，Y. Wang*, J. Wang, Q. Tian, M. Wang.Towards Generating Discriminant Person Images with Manifold Mixup.IEEE Trans. Pattern Analysis and Machine Intelligence, IF:17.73, 2020. (minor revision)
J. Peng,Y. Wang*, H. Wang, Z. Zhang, X.Fu, M.Wang.Unsupervised Vehicle Re-identification with Progressive Adaptation.IJCAI 2020, Yokohama, Japan.
X. Li,Y. Wang*.Recovering Accurate Labeling Information from Partially Valid Data for Effective Multi-Label Learning.IJCAI 2020, Yokohama, Japan.
D. Guo,Y. Wang*, P. Song, M. Wang.Recurrent Relational Memory Network for Unsupervised Image Captioning.IJCAI 2020, Yokohama, Japan.
Y. Zhang, Z. Zhang*, Yang Wang*, Z. Zhang, L. Zhang, S. Yan, Meng Wang. Partial-Label and Structure-constrained Deep Coupled Factorization Network. AAAI 2021.
T. Chen, H. Yin, G. Ye, Z. Huang,Y. Wang, M. Wang.Try this Instead:Personalized and Interpretable Substitute Recommendation.ACM SIGIR 2020, Xian, China.
Y. Chen, P. Ren,Y. Wang*, Maarten de Rijke.Bayesian Personalized Feature Interaction Selection for Factorization Machines,ACM SIGIR 2019,665-674,Pairs, France.
J. Chi, J. Ouyang, X. Li,Yang Wang, Meng Wang.Approximate Optimal Transport for Continuous Densities with Copulas.IJCAI 2019, Macao, China.
Y.Wanget al.,IterativeViewsAgreement: An Iterative Low-Rank based structured Optimization Method to Multi-view Spectral Clustering,IJCAI 2016, New York. Google Scholar citations: 145
S. Pan, J. Wu, X. Zhu, C. Zhang,Yang Wang.Tri-party Deep Network Representation. IJCAI 2016.New York City, USA.
Y. Wanget al.,Effective Multi-Query Expansions: Robust Landmark Retrieval,ACM Multimedia 2015, Google Citations: 60.
Y. Wang et al.,LBMCH:Learning Bridging mapping for cross-modal Hashing,ACM SIGIR 2015, Google Citations: 70
Z Zhang, Y Sun,Yang Wang, Z Zhang, L Wu, M Wang.MDPL-net: Multi-layer Dictionary Learning Network with Added Skip Dense Connections. IEEE ICDM 2020. Italy.
Z. Zhang, Y. Sun, Z. Zhang,Yang Wang,G. Liu, Meng Wang.Learning Structured Twin-Incoherent Twin-Projective Latent Dictionary Pairs for Classification. IEEE ICDM, 2019. Beijing China.
Z Zhang, L Wang,Yang Wang, S Li, Z Zhang, Z Zha, M Wang.Adaptive Structure-Constrained Robust Latent Low-Rank Coding for Image Recovery. IEEE ICDM. 2019. Beijing China.
H. Yin, H Chen, X Sun, H Wang,Yang Wang,N Quoc.SPTF: A Scalable Probabilistic Tensor Factorization Model for Semantic-Aware Behavior Prediction. IEEE ICDM 2017.
Y. Chen, X. Zhao, X. Lin,Yang Wang.Towards Frequent Subgraph Mining on Single Large Uncertain Graphs. IEEE ICDM 2015. Atlantic City, USA.
Y. Wanget al.,Robust Subspace Clustering for Multi-view Data by Exploiting Correlations Consensus,IEEE Trans. ImageProcessing, 24(11):3939-3949, 2015. Google Scholar citations: 168
Y. Wanget al.,Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval.IEEE Trans. Image Processing, 26(3):1393-1404,2017. Google scholar citations: 130
Y. Chen,Yang 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), 2020.
Y. Chen,Yang Wang, X. Zhao, Maarten de Rijke.Block-aware Item Similarity Models for Top-N Recommendation. ACM Trans. Information Systems (ACM TOIS), 2020.
Y. Wanget 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: 173 (ESI Highly cited paper Top 1%)
Y. Wanget 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: 101
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: 124 (ESI Highly Cited Paper)
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: 130 (ESI Highly Cited Paper)
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: 119 (ESI Highly Cited Paper, Top 1%)
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.
J. Ren, Z. Zhang, S. Li,Yang Wang,G. Liu, ShuichengYan, Meng Wang.Learning Hybrid Representation by Robust Dictionary Learning in Factorized Compressed Space.IEEE Trans. Image Processing, 2020.
L. Wu, R. Hong,Yang Wang*, Meng Wang.Cross-Entropy Adversarial View Adaptation for Person Re-identification.IEEE Trans. Circuits and Systems for Video Technology, 30(7):2081-2092, 2020.
L. Wu, Yang Wang, S. Pan. Exploiting attribute correlations: A novel trace lasso-based weakly supervised dictionary learning method。 IEEE Trans. Cybernetics, 2017.
Z. Zhang,Y. Sun,Yang Wang*, Z. Zhang, H. Zhang, G. Liu, Meng Wang.Twin-Incoherent Self-Expressive Locality-Adaptive Latent Dictionary Pair Learning for Classification.IEEE Trans. Neur Netw. Learning Syst, 2021.
H. Wang,Yang Wang*, Z. Zhang, X. Fu, Z. Li, M. Xu, Meng Wang.Kernelized Multiview Subspace Analysis by Self-weighted Learning. IEEE Trans. Multimedia, 2020.
X. Zhao, C. Xiao, X. Lin, Yang Wang. Efficient Structure Similarity Searches: A Partition-Based Approach. VLDB Journal, 2018.
L. Wu,Yang Wang*, J. Gao, Meng Wang, Z. Zha, Dacheng Tao.Deep Co-attention based Comparators for Relative Representation Learning in Person Re-identification.IEEE Trans. Neur Netw. Learning Syst, 2021.
X. Gao, Yang Wang*, J. Cheng, M. Xu, Meng Wang.Meta-learning Based Relation and Representation Learning Networks for Single-image Deraining. Pattern Recognition, 2021, Elsevier.
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: 50
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:127. (ESI Highly Cited Paper Top 1%)
L. Wu,Yang Wang, X. Li, J. Gao.What-and-Where to Match: Deep Spatially Multiplicative Integration Networks for Person Re-identification. Pattern Recognition, 76:727-738, 2018.Google Citations: 100 .(ESI Highly Cited Paper Top 1%)
X. Du, H. Yin, L. Chen,Yang Wang, Y. Yang, X. Zhou.Personalized Video Recommendation Using Rich Contents from Videos. IEEE Trans. Knowledge and Data Engineering, 2020.
Y. Chen, X. Zhao, X. Lin,Yang Wang, D. Guo.Efficient Mining of Frequent Patterns on Uncertain Graphs. IEEE Trans. Knowledge and Data Engineering, 2019.
X. Li, Y. Wang*, Z. Zhang et al., RMoR-AION: Robust Multi-output Regression by Simultaneously Alleviating Input and Output Noises. IEEE Trans. Neural Networks and Learning Systems, 2021.
M. Fang, J. Zhou, J, Yin, Y. Wang, D. Tao.Data Subset Selection with Imperfect Multiple Labels. IEEE Trans. Neural Networks and Learning Systems, 2019.
S. Hao, T. Chen, Yang Wang*, R. Guo, Meng Wang.Adaptive Multi-Task Dual-Structured Learning with Its Application on Alzheimer’s Disease Study. ACM Trans. Internet Technology, 2021.
Yang Wang, L. Wu.Beyond Low-Rank Representations: Orthogonal Clustering Basis Reconstruction with Optimized Graph Structure for Multi-view Spectral Clustering. Neural Networks, 2018 Elsevier, Google Citations： 78.
Z. Zhang, Z. Tang, Yang Wang*, Z. Zhang, C. Zhan, Z. Zha, Meng Wang.Dense Residual Network: Enhancing Global Dense Feature Flow for Character Recognition. Neural Networks, 2021, Elsevier.
L. Wu, Y. Wang, J. Shepherd.Efficient image and tag co-ranking: a bregman divergence optimization method. ACM Multimedia, 2013.
Yang Wang, X. Lin, Lin Wu. Exploiting correlation consensus: towards subspace clustering for multi-modal data. ACM Multimedia 2014.
Yang Wang,X. Lin, Q. Zhang.Towards metric fusion on multi-view data: a cross-view based graph random walk approach. ACM CIKM, BullingGame, CA, USA.2013.