Jian Yang
Also known as J. Yang, Jian Jun Yang, Yang Jian, 杨健
Jian Yang is a computer vision researcher whose work on two-dimensional image representation and discriminant analysis includes methods for face recognition. He studied mathematics at Xuzhou Normal University and Changsha Railway University, earned a doctorate in pattern recognition at NUST, and held research posts in Spain, Hong Kong and New Jersey before becoming a professor at NUST in 2007. He coauthored a 2006 book on biometric image discrimination, became an IAPR Fellow in 2016, and coauthored Selective Kernel Networks, a convolutional network that adapts its receptive fields to input information. As of October 2026, he is a professor and doctoral supervisor at NUST, where he leads a project on autonomous-driving perception.
- Now at
- Nanjing University of Science and Technology
- Works
- 889
- Citations
- 45,770
- h-index
- 92
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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1991–2002
Mathematics and pattern recognition
He earns a mathematics bachelor’s at Xuzhou Normal University in 1995, a master’s in applied mathematics at Changsha Railway University in 1998, and a pattern-recognition doctorate at NUST in 2002.
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2003–2007
Postdoctoral posts and a professorship
He takes postdoctoral posts at the University of Zaragoza, NUST, Hong Kong Polytechnic University and NJIT between 2003 and 2007. In September 2007, he becomes a professor at NUST.
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2004–2005
Two-dimensional face analysis
He coauthors Two-Dimensional PCA: a New Approach to Face Representation and Recognition in 2004. In 2005, he coauthors Two-dimensional discriminant transform for face recognition, which develops 2DLDA for image feature extraction and recognition.
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2006
A biometric imaging book
With David Zhang and Xiaoyuan Jing, he coauthors Biometric Image Discrimination Technologies, published by Idea Group in 2006.
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2016
An IAPR fellowship
IAPR elects him a Fellow in 2016 for contributions to 2D image representation and discriminant analysis.
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2019
Selective Kernel Networks
In 2019, he coauthors Selective Kernel Networks, a convolutional neural network that combines branches with different kernel sizes through softmax attention and lets neurons adjust their receptive fields to input information.
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2025–2028
Professor and project lead
As of October 2026, he is a professor and doctoral supervisor in NUST’s School of Computer Science and Technology. He leads a 2025–2028 project on robust 3D environment perception and accurate prediction for autonomous driving.
Sources and credits
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