Portrait of Taifeng Wang

Taifeng Wang

Lead Researcher


Taifeng Wang (王太峰) is now a lead researcher in Artificial Intelligence group, Microsoft Research Asia. His research interests include machine learning, distributed system, internet advertising, and search engine technique. Currently, he is majorly working on large scale machine learning related topics.

He has been working on internet advertising since Sep, 2010. His research focuses on modeling users’ behavior in ads system to help the search engine to deliver better ads. The research topics include ads click prediction, user behavior targeting, ads optimization etc. Before working on ads, he had developed a large scale graph learning platform (codename: Graphor) which is going to handle learning and mining tasks on graphs with billions of node. He has worked on the Graphor project for three years. He has got several papers published on large scale graph learning, as long as 10+ US patents filed regarding to distributed system.

He joined MSRA in July 2006. He got his Master(2006) degree and BS(2003) degree in Electronic Engineering from University of Science and Technology of China. He has been with MSRA as a research intern from Mar. 2005 to Jan. 2006. During his internship, he worked on news search and text mining related topics.







Our project Distributed Machine Learning Toolkit(DMTK) has been released to Github recently. It provides a  set of good tools for people who want to play with big data machine learning. And more importantly, it creates a new channel for us to advanced the state of the art in distributed machine learning with the research community together. Please check out the website of DMTK: http://www.dmtk.io


  • Bin Gao, Taifeng Wang, and Tie-Yan Liu, Large-Scale Graph Mining and Learning for Information Retrieval. A half-day tutorial in the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2012)
  • Bin Gao, Taifeng Wang, and Tie-Yan Liu, Ranking on Large-Scale Graphs with Rich Metadata. A half-day tutorial in the 20th International World Wide Web Conference (WWW 2011).


  • Organized workshop of Deep Learning for Web Search and Data Mining (WSDM 2015)

Academic Activity:

  • Chair of DL-WSDM 2015
  • Reviewer of IPM
  • PC of IJCAI 2013
  • PC of KDD 2016, 2015, 2012
  • PC of SIGIR 2014, 2013, 2012, 2011, 2010
  • PC of AIRS2011
  • PC of WWW 2014, 2011

Current Interns

  • Shanwei Lin(NTU)
  • Guolin Ke(XMU)
  • Shuxin Zheng(USTC)
  • Wenyi Tang(USTC)
  • Guoqing Liu(USTC)

Previous Interns

  • Pei Li(XMU)
  • Xiaocheng Hu(USTC)
  • Qiwei Ye(PKU)
  • Guihong Ma(SYSU)
  • Yuyu Zhang (WHU->CAS)
  • Liang Pang(CAS)
  • Jingcheng Yu(Fudan)
  • Yunong Wang(USTC)
  • Wuxuan Jiang(SJTU)
  • Lanlan Liu (USTC)
  • Shujia LIu (SYSU)
  • Jun Feng (WHU->Tsinghua)
  • Shaosheng Cao (XDU)
  • SeungKeol Kim (POSTECH)
  • Shusen Liu (SCUT)
  • Huan Gui (PKU->UIUC)
  • Jaeyong Lee (POSTECH)
  • Chenyan Xiong (CAS->CMU)
  • Feichao Ma (PUK)
  • Xin Li (Tsinghua)
  • Jianshan He (PKU)
  • Chenjing Wang (BIT)
  • Shijie Xu (BUAA)
  • Yanliang Cai (PKU)
  • Chao Feng (PKU)
  • Zhicheng Yin (PKU)
  • Shuai Yuan (BUAA->UCL)
  • Diwen Zhu (Fudan->Columbia)
  • Jin Zhou (USTC)
  • Jingrui Chen (USTC)
  • Liang Tang (BIT)
  • Ming Yang (Tsinghua)
  • Minghao Liu (PKU)
  • Zhi Chen (Tsinghua)