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.