Jun Zhu
Assoc. Prof. @ THU
Adj. Faculty @ CMU
About me

My research focuses on developing statistical machine learning methods to understand complex scientific and engineering data. My current interests are in latent variable models, large-margin learning, Bayesian nonparametrics, and deep learning. Before joining Tsinghua in 2011, I was a post-doc researcher and project scientist at the Machine Learning Department in Carnegie Mellon University.

  • We open-sourced ZhuSuan, a GPU library for Bayesian Deep Learning (a conjoin of Bayesian methods and deep learning) buit on TensorFlow.
  • Looking for highly motivated post-docs to work on large-scale machine learning and/or its applications in image, text, and network analysis. Various types of fellowship are avaiable for outstanding applicants, such as Tsinghua Fellowship [doc, link] , Innovation Fellow, and Exchange Program.
  • I recieved the support from the National Youth Top-notch Talent Support Program, 2015.
  • I recieved the "CVIC SE Talents" Award, 2015.
  • I recieved the Best Collaboration Award by Tsinghua-MSRA Joint Research Lab, 2014.
  • I was selected as one of "AI's 10 to Watch" by IEEE Intelligent Systems, 2013.
  • I recieved the "Excellent Young Scholar" Award by NSF of China (NSFC), 2013.
  • I recieved the "CCF Young Scientist" Award by China Computer Federation (CCF), 2013.
Recent publications (full list)

Last updated on Dec. 4th, 2012.