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. 对照阅读

News

• Looking for highly motivated post-docs to work on large-scale machine learning, deep learning, and/or applications in image, text, and network analysis.
• 2015/12: Tian Tian was awarded the Tsinghua Special Grade Scholarship for Graduate Students (亚洲威廉官网规则须知特等奖学金）
• 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.