在读研期间，所有与你读研相关的事情，可能都需要经过你的导师同意，所以说，选择导师真的很重要，也希望大家能够认真对待这件事，怎样才能选择适合自己的导师呢?这就要我们提前做足功课，尽可能多的搜集有关你准备报考的导师的信息，下面新东方在线考研频道为大家分享：“北京交通大学硕士研究生导师信息：王涛”文章。
北京交通大学硕士研究生导师信息：王涛
王涛
博士、教授
基本信息
办公电话：51688566电子邮件： twang@bjtu.edu.cn
通讯地址：北京交通大学计算机学院九教北525邮编：100044
教育背景
2013年1月，北京交通大学 计算机科学与技术专业 博士学位
2004年4月，北京交通大学 计算机应用技术专业 硕士学位
2001年7月，北京交通大学 计算机科学与技术专业 学士学位
工作经历
2021.12至今，北京交通大学计算机学院 教授
2020.12至今，北京交通大学计算机学院 科学系教师党支部书记
2016.12-2021.11，北京交通大学计算机学院 副教授
2014.12-2015.12，美国天普大学计算机系 访问学者
2006.12-2016.11，北京交通大学计算机学院 讲师
2004.04-2006.11，北京交通大学计算机学院 助教
研究方向
机器学习与认知计算
计算机技术
软件工程
人工智能
大数据技术与工程
数字媒体信息处理与智能分析
新一代电子信息技术
招生专业
计算机科学与技术硕士
计算机技术硕士
软件工程硕士
人工智能硕士
大数据技术与工程硕士
计算机科学与技术博士
新一代电子信息技术(含量子技术等)硕士
软件工程博士
新一代电子信息技术(含量子技术等)博士
人工智能博士
计算机技术博士
科研项目
国家自然科学基金"面上项目"：可信赖异质图神经网络研究，2024-01-01--2027-12-31，主持
国家自然科学基金"面上项目"：面向关系推理的图神经网络关键问题研究，2021-01-01--2024-12-31，主持
国家自然科学基金"面上项目"：基于多模态超图的社群图像检索研究，2017-01-01--2020-12-31，主持
国家自然科学基金"青年项目"：基于组合地图模型的图像检索算法研究，2014-01-01--2016-12-31，主持
北京市自然科学基金“面上项目”：面向关系推理的深度神经网络模型及算法研究，2020-01-01--2022-12-31，主持
国家级"科技委"：XXXX系统构建与计算推演算法，2022-05-01--2023-06-30，主持
国家级平台专项：面向移动通信网络的大图数据分析与挖掘算法研究，2022-04-01--2020-03-30，主持
横向课题：交通产业元宇宙技术与应用发展趋势研究，2024-05-01--2024-12-31，主持
横向课题：视频监控智能分析技术，2016-05-01--2016-12-31，主持
基本科研业务费：面向AR的高精度目标跟踪技术研究，2018-04-01--2020-03-30，主持
基本科研业务费：基于内容安全的视频分析技术，2015-01-01--2016-12-31，主持
基本科研业务费：基于组合地图的图像匹配与检索算法研究，2012-03-01--2014-02-28，主持
国家级"科技委"：基于XXXX数据计算理论与方法，2022-08-29--2027-08-31，参加
国家级"科技委"：高动态微光战场环境下的目标感知与认知一体化技术研究，2020-08-01--2022-07-31，参加
国家(工信部等)专项：自动驾驶模拟仿真平台，2021-07-01--2023-06-30，参加
国家(工信部等)专项：工业互联网创新发展工程-工业企业侧安全数据采集设备，2019-08-01--2021-07-31，参加
国家重点研发计划-课题：异构交通主体群体智能协同行为仿真分析与评估，2019-03-01--2021-12-31，参加
国家重点研发计划-任务：社区基础数据采集、处理、应用、共享技术，2018-07-01--2021-06-30，参加
教学工作
本科课程：《面向对象程序设计与C++》。
研究生课程：《机器视觉基础》。
论文/期刊
Google Scholar:
https://scholar.google.com/citations?user=F3C5oAcAAAAJ&hl=zh-CN
2023:
[1] F Luo, J Wu, T Wang. Discrete Listwise Content-aware Recommendation. ACM Transactions on Knowledge Discovery from Data, 2023.
[2] H Liu, T Wang, Y Li, C Lang, Y Jin, H Ling. Joint graph learning and matching for semantic feature correspondence. Pattern Recognition, 2023.
[3] Z Xu, L Wei, C Lang, S Feng, T Wang, AG Bors, H Liu. SSR-Net: A Spatial Structural Relation Network for Vehicle Re-identification. ACM Transactions on Multimedia Computing, Communications and Applications, 2023.
[4] K Li, H Liu, T Wang. Centroid-based graph matching networks for planar object tracking. Machine Vision and Applications, 2023.
[5] H Liu, X You, T Wang, Y Li. Object detection via inner-inter relational reasoning network. Image and Vision Computing, 2023.
2022:
[1] G Zhao, T Wang, Y Li, Y Jin, C Lang, S Feng. Neighborhood Pattern Is Crucial for Graph Convolutional Networks Performing Node Classification. IEEE Transactions on Neural Networks and Learning Systems, 2022.
[2] F Luo, J Wu, T Wang. Discrete Listwise Personalized Ranking for Fast Top-N Recommendation with Implicit Feedback. IJCAI, 2022.
[3] XT You, H Liu, T Wang, S Feng, C Lang. Object detection by crossing relational reasoning based on graph neural network. Machine Vision and Applications. 2022.
[4] T Liang, Y Jin, W Liu, S Feng, T Wang, Y Li. Keypoint-Guided Modality-Invariant Discriminative Learning for Visible-Infrared Person Re-identification. ACM MM, 2022.
[5] Z Zhang, Y Jin, S Feng, Y Li, T Wang, H Tian. FENet: An Efficient Feature Excitation Network for Video-based Human Action Recognition. ICSP, 2022.
[6] X Li, T Liang, Y Jin, T Wang, Y Li. Camera-Aware Style Separation and Contrastive Learning for Unsupervised Person Re-Identification. ICME, 2022.
[7] X Deng, S Feng, G Lyu, T Wang, C Lang. Beyond word embeddings: Heterogeneous prior knowledge driven multi-label image classification. IEEE Transactions on Multimedia, 2022.
[8] L Wei, C Lang, L Liang, S Feng, T Wang, S Chen. Weakly supervised video object segmentation via dual-attention cross-branch fusion. ACM Transactions on Intelligent Systems and Technology , 2022.
2021:
[1] Z Li, C Lang, T Wang, Y Li, J Feng. Deep spatio-frequency saliency detection. Neurocomputing, 2021, 453:645-655.
[2] G Lyu, S Feng, Y Jin, T Wang, C Lang, Y Li. Prior Knowledge Regularized Self-Representation Model for Partial Multilabel Learning. IEEE Transactions on Cybernetics, 2021.
[3] G Zhao, T Wang, Y Li, C Lang. Entropy-aware Self-training for Graph Convolutional Networks. Neurocomputing, 2021.
[4] Z Xu, L Wei, C Lang, S Feng, T Wang, AG Bors. HSS-GCN: A Hierarchical Spatial Structural Graph Convolutional Network for Vehicle Re-identification. ICPR, 2021.
[5] M Wang, C Lang, L Liang, G Lyu, S Feng, T Wang. Class-balanced Text to Image Synthesis with Attentive Generative Adversarial Network. IEEE MultiMedia, 2021.
[6] M Wang, C Lang, S Feng, T Wang, Y Jin, Y Li. Text to photo-realistic image synthesis via chained deep recurrent generative adversarial network. Journal of Visual Communication and Image Representation, 2021.
2020:
[1] T Wang, H Liu, Y Li, Y Jin, H Ling*. Learning Combinatorial Solver for Graph Matching. CVPR, 2020. (oral)
[2] G Lyu, S Feng, T Wang, C Lang. A Self-Paced Regularization Framework for Partial-Label Learning. IEEE Transactions on Cybernetics, 2020.
[3] M Wang, C Lang, L Liang, S Feng, T Wang, Y Gao. End-to-End Text-to-Image Synthesis with Spatial Constrains. ACM Transactions on Intelligent Systems and Technology (TIST), 2020, 11(4):1-19.
[4] M Wang, C Lang, L Liang, G Lyu, S Feng, T Wang. Attentive Generative Adversarial Network To Bridge Multi-Domain Gap For Image Synthesis. ICME, 2020, pp. 1-6.
[5] Z Li, Y Jin, Y Li, C Lang, S Feng, T Wang. Learning part-alignment feature for person re-identification with spatial-temporal-based re-ranking method. World Wide Web, 23(3):1907-1923.
[6] Y Li, K Liu, Y Jin, T Wang, W Lin. VARID: Viewpoint-aware re-identification of vehicle based on triplet loss. IEEE Transactions on Intelligent Transportation Systems. 2020.
[7] T Liang, Y Jin, Y Li, T Wang. EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising. ICSP, 2020.
2019:
[1] T Wang, H Ling*, C Lang and S Feng. Deformable Surface Tracking by Graph Matching. ICCV, 2019.
[2] L Sun, S Feng, T Wang, C Lang and Y Jin. Partial Multi-Label Learning by Low-Rank and Sparse Decomposition. AAAI, 2019.
[3] G Lyu, S Feng, T Wang*, C Lang, Y Li. GM-PLL: Graph Matching based Partial Label Learning. IEEE Trans. on KDE, 2019. (online avaliable)
[4] Z Li, C Lang, J Feng, Y Li, T Wang, S Feng. Co-saliency Detection with Graph Matching, ACM Trans. on TIST, 10(3): 22-30. 2019.
[5] M Yin, C Lang, Z Li, S Feng, T Wang. Recurrent convolutional network for video-based smoke detection, Multimedia Tools and Applications, 78(1):237-256, 2019.
[6] C Qian, Y Jin, Y Li, C Lang, S Feng, T Wang. Deep Domain Adaptation for Asian Face Recognition via Ada-IBN. ICMEW, 2019.
[7] Z Li, Y Jin, Y Li, C Lang, S Feng, T Wang. Learning part-alignment feature for person re-identification with spatial-temporal-based re-ranking method. WWW, 2019.
[8] J Zhou, T Wang, Y Jin. The hypergraph matching based on CCRP. BESC, 2019.
2018:
[1] T Wang, H Ling*. Gracker: A Graph-based Planar Object Tracker. IEEE Trans. on PAMI. 40(6):1494-1501, 2018.
[2] T Wang, H Ling*, C Lang and S Feng. Branching and Adaptive Path Following for Graph Matching. IEEE Trans. on PAMI. 40(12):2853-2867, 2018.
[3] T Wang, H Ling*, C Lang and S Feng. Constrained confidence matching for planar object tracking. ICRA, 2018.
[4] J Zhou, T Wang*, C Lang, S Feng, Y Jin. A novel hypergraph matching algorithm based on tensor refining. Journal of Visual Communication and Image Representation, 57:69-75, 2018.
[5] S Xu, T Wang*, C Lang, S Feng, Y Jin. Graph-based visual odometry for VSLAM. Industrial Robot: An International Journal, 45(5):679-687, 2018.
[6] Z Li, C Lang, S Feng, T Wang. Saliency ranker: A new salient object detection method. Journal of Visual Communication and Image Representation, 50:16-26, 2018.
[7] D Xu, C Lang, S Feng, T Wang. A framework with a multi-task CNN model joint with a re-ranking method for vehicle re-identification. ICIMCS, 2018.
[8] K Yu, C Lang, S Feng, T Wang. Reasonably assign label distributions to GAN images in person re-identification baseline. BigMM, 2018.
[9] X Xu, Y Li, Y Jin, C Lang, S Feng, T Wang. Hierarchical Discriminant Feature Learning for Heterogeneous Face Recoginition. VCIP, 2018.
2017:
[1] S Feng, C Lang, J Feng, T Wang, J Luo. Human facial age estimation by cost-sensitive label ranking and trace norm regularization, IEEE Transactions on Multimedia, 19(1):136-148, 2017.
[2] R Chen, C Lang, T Wang*. Multiple path exploration for graph matching, Machine Vision and Applications, 28(7): 695-703, 2017.
[3] Y Chen, T Wang*. Recursive formulas for embedding distributions of cubic outerplanar graphs, Australasian Journal of Combinatorics, 68(1):131-146, 2017.
2016:
[1] Tao Wang*, Haibin Ling, Congyan Lang, Jun Wu. Branching path following for graph matching. ECCV, 2016.
[2] Tao Wang*, Haibin Ling. Path following with adaptive path estimation for graph matching. AAAI, 2016.
[3] Tao Wang*, Haibin Ling, Congyan Lang, Songhe Feng. Symmetry-aware graph matching. Pattern Recognition, 60: 657-668, 2016.
[4] Zhu Teng, Tao Wang, Feng Liu, et al., From samples selection to model update: A robust online visual tracking algorithm against. Neurocomputing. 173: 1221-1234, 2016.
Earlier:
[1]. Tao Wang*, Guojun Dai, Bingbing Ni, D. Xu. A distance measure between labeled combinatorial maps. Computer Vision and Image Understanding. 116(6): 1168-1177, 2012.
[2]. Tao Wang*, Hua Yang, Congyan Lang, S. Feng. An error-tolerant approximate matching algorithm for labeled combinatorial maps. Neurocomputing. 156: 211-220, 2015.
[3]. Tao Wang*, Guojun Dai, De Xu. A polynomial algorithm for submap isomorphism of general maps. Pattern Recognition Letters. 32(8): 1100-1107, 2011.
[4]. Tao Wang*, Yanpei Liu. Implements of some new algorithms for combinatorial maps. OR Transactions. 12(2): 58-66, 2008.
[5]. Tao Wang*, Congyan Lang, Songhe Feng. Joint tree of combinatorial maps. PAKDD 2014.
[6]. Tao Wang*, Weisheng Li. Fast low-cost shortest path tree algorithm. Journal of Software. 15(2): 660-665, 2004.
[7]. Tao Wang*, Weisheng Li. Shortest path subgraph. Journal of Northern Jiaotong University. 28(2):46-49, 2004.
[8]. Yichao Chen, Yanpei Liu, Tao Wang. The Total Embedding Distributions of Cacti and Necklaces. Acta Mathematica Sinica, English Series. Vol. 22, no. 5, pp. 1583-1590, 2006.
[9]. Shu Liu, Weisheng Li, Tao Wang. Advanced algorithm for fast lower-cost shortest path tree. Journal of Electronics and Information Technology. Vol. 27, no. 4, pp. 638-641, 2005.
以上就是小编为大家分享的：“北京交通大学硕士研究生导师信息：王涛”，更多研究生导师信息，欢迎继续浏览新东方在线研究生导师频道。