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.