Tsinghua SAIL Group

Statistical Artificial Intelligence & Learning

Research Overview

We are interested in developing machine learning theories, algorithms, and applications to problems in science, engineering and computing. We use the tools of statistical inference and large-scale computing to deal with uncertainty and information in various domains, including text mining, image & video processing, network analysis, and neuroscience.
Our recent projects include Probabilistic Modeling, Inference and Programming / Interaction between Deep Learning and Neuroscience / Reinforcement Learning and Algorithmic Game Theory / Adversarial Attacks and Defenses (for Deep Learning) / Interpretable Machine Learning Techniques and Visualization / Intelligent Multimedia Applications.
We actively seek to collaborate with other groups around the world. If you are interested in finding out more about our research, please visit our publication page.


  • Looking for highly motivated post-docs to work on large-scale machine learning, deep learning, and/or applications in image, text, and network analysis.
  • 2016/1: Jun Zhu got support from "National High-Level Talents Special Support Plan" ("万人计划"青年拔尖人才)
  • 2015/12: Tian Tian was awarded the Tsinghua Special Grade Scholarship for Graduate Students (研究生特等奖学金)
  • 2015/12: Ming Liang was awarded the Baidu Scholarship.
  • 2015/11: Jun Zhu received the CVIC SE Talents Award (中创软件人才奖).
  • 2015/09: Our group has 3 NIPS papers. Congratulations to the authors.
  • 2015/08: Tian Tian was awarded the Siebel Scholarship.