Yueming Wang





Yueming Wang received the Ph.D. degree in Computer Science from Zhejiang University in 2007. From 2007 to 2010, he was a postdoctoral fellow in the Microsoft Research Asia (MSRA) and the Department of Information Engineering, the Chinese University of Hong Kong. He was an associate professor in QAAS, Zhejiang University from 2010, and is a professor since 2016. His research interests are in the area of brain-machine interfaces, data mining, and pattern recognition. More specifically, he studies the problems in connecting biological systems to computer systems to generate more powerful cyborg intelligent systems via BMIs.

He has published more than 40 papers in the prestigious journals and conferences in his research area, including IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Transactions on Image Processing (TIP), Journal of Neural Engineering, and IEEE Computational Intelligence Magazine (CIM). He has gotten the funding support from the National Natural Science Foundation of China (2), the National 863 Program of China (1), Zhejiang Provincial Natural Science Foundation of China (Key Program, 1), and the Ph.D. Programs Foundation of Ministry of Education of China (1). The work on rat cyborg was nominated for the Annual BCI Research Award at BCI Meeting 2016. The work on bidirectional brain-machine integration won the WUWENJUN Innovative Research Award, 2016. 

He is an IEEE member, CCF member, and CAAI member. He was a program chair of IEEE Computational Intelligence Society (CIS) Summer School on Neuromorphic and Cyborg Intelligent Systems, 2015 and a program chair of the Forum of Cyborg Intelligence in China National Computer Congress, 2013. He serves as the under-secretary-general of the cyborg intelligence branch, Chinese Association for Artificial Intelligence. He acts as a reviewer for the TPAMI, IJCV, TIFS, TCSVT, and Pattern Recognition. He also acts as a program committee member for ICCV'09, ICCV'11, ICCV'13, ICCV'15 and CVPR'13, CVPR'14, CVPR'15, CVPR'16. 


Selected publications:

[1] Z. Hu, G. Pan,Y. Wang*, Z. Wu, "Sparse Principal Component Analysis via Rotation and Truncation", IEEE Transactions on Neural Networks and Learning Systems, 27(4): 875-890, 4/2016. 

[2] G. Pan, X. Zhang,Y. Wang*, Z. Hu, X. Zheng, Z. Wu. "Establishing Point Correspondence of 3D Faces via Sparse Facial Deformable Model". IEEE Transactions on Image Processing (TIP), 22(11): 4170-4181, 11/2013.

[3] Y. Wang, M. Lu, G. Pan*, L. Tian, K. Xu, X. Zheng, Z. Wu, "A Visual Cue-guided Rat Cyborg for Automatic Navigation", IEEE Computational Intelligence Magazine, 10(2):42-52, 4/2015. 

[4] Y. Wang, Y. Qi, Y. Wang*, Z. Lei, X. Zheng, G. Pan, "Delving into α-stable distribution in noise suppression for seizure detection from scalp EEG", J Neural Eng., 13(5):056009, 8/2016.

[5] Y. Wang*, Y. Qi, J. Zhu, J. Zhang, Y. Wang, X. Zheng, Z. Wu, "A Cauchy-based State-space Model for Seizure Detection in a EEG Monitoring System", IEEE Intelligent Systems, 30(1): 6-12, 12/2014. 

[6] Y. Wang, L. Jiang, Y. Wang, B. Cai,Y. Wang*, W. Chen, X. Zheng, "An Iterative Approach for EEG based Rapid Face Search: A Refined Retrieval by Brain Computer Interfaces", IEEE Transactions on Autonomous Mental Development, 7(3): 211-222, 6/2015.

[7] Y. Zhang, G. Pan*, K. Jia, M. Lu,Y. Wang, Z. Wu, "Accelerometer-Based Gait Recognition by Sparse Representation of Signature Points with Clusters", IEEE TRANSACTIONS ON CYBERNETICS, 45(9): 1864-1875, 9/2015.

[8] K. Xu, Y. Wang*,Y. Wang, F. Wang, Y. Hao, S. Zhang, Q. Zhang, W. Chen, X. Zheng. "Local-learning-based Neuron Selection for Grasping Gesture Prediction in Motor Brain Machine Interfaces". J Neural Eng. 10(2):026008, 4/2013. 

[9] Y. Wang, J. Liu, and X. Tang, "Robust 3D Face Recognition by Local Shape Difference Boosting," IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(10): 1858-1870, 2010. (IEEE TPAMI).

[10] S. Chen, L. Cao,Y. Wang, J. Liu, and X. Tang, "Image Segmentation by MAP-ML Estimations," IEEE Transactions on Image Processing, 19(9): 2254-2264, 2010. (TIP).

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