Yonghong Tian is currently a Boya Distinguished Professor with the School of EECS, Peking University, China, and is also the deputy director of Artificial Intelligence Research Center, PengCheng Laboratory, Shenzhen, China. His research interests include computer vision, multimedia big data, and brain-inspired visual intelligence. Prof. Tian was/is an Associate Editor of IEEE TCSVT (2018.1-), IEEE TMM (2014.8-2018.8), IEEE Multimedia Mag. (2018.1-), and IEEE Access (2017.1-). He co-initiated IEEE Int’l Conf. on Multimedia Big Data (BigMM) and served as the TPC Co-chair of BigMM 2015, and aslo served as the Technical Program Co-chair of IEEE ICME 2015, IEEE ISM 2015 and IEEE MIPR 2018/2019, and General Co-chair of IEEE MIPR 2020. He is the steering member of IEEE ICME (2018-) and IEEE BigMM (2015-), and is a TPC Member of more than ten conferences such as CVPR, ICCV, ACM KDD, AAAI, ACM MM and ECCV. He was the recipient of the Chinese National Science Foundation for Distinguished Young Scholars in 2018, two National Science and Technology Awards and three ministerial-level awards in China, and obtained the 2015 EURASIP Best Paper Award for Journal on Image and Video Processing, and the best paper award of IEEE BigMM 2018. He is a senior member of IEEE, CIE and CCF, a member of ACM.
He is the author or coauthor of over 180 technical articles in refereed journals such as IEEE TPAMI/TNNLS/TIP/TMM/TCSVT/TKDE/TPDS, ACM CSUR/TOIS/TOMM and conferences such as NeurIPS/CVPR/ICCV/AAAI/ ACMMM/WWW. Five representative papers are listed as follows:
 Siwei Dong, Zhichao Bi, Yonghong Tian* and Tiejun Huang, Spike Coding for Dynamic Vision Sensor in Intelligent Driving, IEEE Internet of Things Journal, 6(1), Feb 2019, 60-71.
 Peixi Peng, Yonghong Tian*, Tao Xiang, Yaowei Wang, Massimiliano Pontil, Tiejun Huang, Joint Semantic and Latent Attribute Modelling for Cross-Class Transfer Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(7), 2018, Jul 2018, 1625-1638.
 Lin Ding, Yonghong Tian*, Hongfei Fan, Yaowei Wang, and Tiejun Huang, Rate-Performance-Loss Optimization for Inter-frame Deep Feature Coding from Videos, IEEE Transactions on Image Processing, 26(12), Dec. 2017, 5743-5757.
 Jia Li, Lingyu Duan, Xiaowu Chen, Tiejun Huang, and Yonghong Tian, Finding the Secret of Image Saliency in the Frequency Domain, IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(12), Dec 2015, pp. 2428-2440.
 Yonghong Tian*, Jia Li*, Shui Yu, Tiejun Huang, Learning Complementary Saliency Priors for Foreground Object Segmentation in Complex Scenes, Int’l Journal of Computer Vision, 111(2), Jan 2015, 153-170.