Short Bio
Jifeng Shen received his M.S. and Ph.D degrees from Jiangsu University of Science and Technology, Zhenjiang, China, and Southeast university, Nanjing, China, in 2006 and 2013 respectively. He is currently an associated professor with School of Electronical and information Engineering in Jiangsu University since 2015. His research interests include computer vision, machine learning, especially focus on real-time object detection. He is a member of pattern recognition special Committee of Jiangsu artificial intelligence society and a member of pattern recognition committee of Chinese artificial intelligence society. He has published more than 30 academic papers, including many top-tier international journals. He is serving as a reviewer for IEEE Transactions on cybernetics, pattern recognition, IEEE transaction on intelligent transportation systems and IEEE transaction on vehicular technology, etc.
Education
2008.09—2012.11 Ph.D. in Pattern Recognition and Intelligent System, Southeast University, China, Supervisor Prof. Changyin Sun
2003.09—2006.04 M.S. in Computer Science, Jiangsu University of Science and Technology, China,
Supervisor Prof. Tongming Liu
1999.09—2003.07 B.S. in Computer Science, East China Shipbuilding Institute, China,
Supervisor Prof. Tongming Liu
Work Experience
2006.04—2008.08 Software Engineer, ZTEsoft, Nanjing, Jiangsu Province, China.
2013.01—2017.5 Lecturer, JiangSu university, Zhenjiang, Jiangsu Province, China.
2013.11—2017.12 Postdoctor, JiangSu university, Zhenjiang, Jiangsu Province, China.
2016.10—2017.11 Visiting Scholar of CSC, Temple University, PA, USA
2017.05—now Associate Professor, JiangSu university, Zhenjiang, Jiangsu Province, China.
Research Grants
Young Scientist Foundation of Jiangsu Province (BK20140566, BK20150470, BK20191427), PI
Chinese Postdoctoral Science Foundation(2014M561586), PI
NSF of China(31971788, 61773184), co-PI
Selected Publications in recent years
[1]Jifeng Shen*, Xin Zuo, Wankou Yang, Danil Prokhorov, Xue Mei and Haibin Ling, Differential Features for Pedestrian Detection: A Taylor Series Perspective,IEEE Transactions on Intelligent Transportation Systems, 20(8):2913-2922, 2019.(IF 6.319)
[2]Jifeng Shen*,Xin Zuo, Lei Zhu, Jun Li, Wankou Yang, and Haibin Ling, Pedestrian Proposal and Refining Based on the Shared Pixel Differential Feature,IEEE Transactions on Intelligent Transportation Systems, 20(6):2085-2095, 2019.(IF 6.319)
[3]Jifeng Shen*, Xin Zuo, Wankou Yang,A Novel Pixel Neighborhood Differential Statistic Feature for Pedestrian and Face Detection,Pattern recognition, 63 (2017) 127–138,2017.(IF 7.196)
[4]Jifeng Shen*, Xin Zuo, Wankou Yang, Hualong Yu, Guohai Liu,Learning Discriminative Features Based on Data Distribution and Shape Statistics for Pedestrian Detection,Neurocomputing, 184(2016)66–77, 2016.(IF 4.438)
[5]Jifeng Shen*, Xin Zuo, Haoran Wang, Wankou Yang,Supervised Local High-order differential Channel feature learning for pedestrian detection,Neural Processing Letters, 45(3):1025–1037 ,2017.(IF 2.891)
[6]Xin Zuo, Bin Dai,Yongwei Shan*,Jifeng Shen*, Chunlong Hu, Shucheng Huang, Classifying cracks at sub-class level in closed circuit television sewer inspection videos,Automation in Construction, 118,(2020):103289,2020. (IF5.669)
[7]Haoran Wang, Chunfeng Yuan,Jifeng Shen, Wankou Yang, and Haibin Ling, Action Unit Detection and Key Frame Selection for Human Activity Prediction,Neurocomputing, 318(2018):109-119, 2018.(IF 4.438).
[8]Hualong Yu, Changyin Sun, Xibei Yang, Wankou Yang andJifeng Shen,ODOC-ELM: Optimal decision outputs compensation-based extreme learning machine for classifying imbalanced data,Knowledge-Based Systems, 92:55-70, 2016. (IF5.921)
