Yadong Mu

National Junior 1000-Talent Plan
No. 128, Zhong-Guan-Cun North Street
Institute of Computer Science and Technology
Peking University, Beijing 100080, China
E-mail: myd AT pku.edu.cn; OR muyadong AT gmail DOT com
I am leading the Machine Intelligence Lab at Institute of Computer Science and Technology, Peking Univeristy. Before joining Peking University, I have ever worked as research fellow at National University of Singapore (PI: Prof. Shuicheng Yan), research scientist at the DVMM lab of Columbia University (PI: Prof. Shih-Fu Chang), researcher at the data mining team of Huawei Noah's Ark Lab in Hong Kong, and senior scientist at Multimedia Department of AT&T Labs, New Jersey, U.S.A.. I obtained both the B.S. and Ph.D. degrees from Peking University.

I have interest in broad research topics in large-scale computer vision and machine learning, particularly large-scale image search and compact hashing, video event detection, telecom data mining and distributed / approximate large-scale optimization.

Project Highlight

Event Detection

Compact Hashing
for Visaul Search


Binary Hashing for
Machine Learning

Large Scale


  • Our team won the second place in RACV'2016 Iqiyi Video Annotation Challenge. See http://sist.shanghaitech.edu.cn/racv2016/competition_tag.html for details.
  • Several positions for Ph.D. / master students and research assistants are available! Email me if you are interested. Candidates will work on some research topics on large-scale video analysis / computer vision / machine learning. [Instructions in Chinese] [Link to ICST website] (07/2016)
  • I am the recipient of National Junior 1000-Talent Plan and have joined the Institute of Computer Science and Technology, Peking University as a tenure track faculty and principal investigator. (05/2016)

Recent Publications [all]

  • Yadong Mu, Wei Liu, Cheng Deng, Zongting Lv, Xinbo Gao, Coordinate Discrete Optimization for Efficient Cross-View Image Retrieval, International Joint Conference on Artificial Intelligence (IJCAI) 2016 [PDF]
  • Yadong Mu, Fixed-Rank Supervised Metric Learning on Riemannian Manifold, Thirtieth AAAI Conference (AAAI), 2016 [PDF] (code by request)
  • Yadong Mu, Wei Liu, Xiaobai Liu, Wei Fan, Stochastic Gradient Made Stable: A Manifold Propagation Approach for Large-Scale Optimization , to appear in IEEE Transactions on Knowledge and Data Engineering (TKDE), 2016 [PDF]


Thanks the generous support of all the sponsors.