In human-centered computer vision, our research focuses on developing methods to automatically understand non-verbal human behaviors, including various facial and body behaviors, such as eye movements, head movements, facial expressions, body pose, body gestures, body action and activities.
In probabilistic machine learning, our research focues on probabilistic graphical models learning and inference, knowledge-augmented machine learning, Bayesian deep learning, and causal machine learning.
Over the years, we have applied computer vision and machine learning technologies we developed to different applications, including medical imaging, human machine interaction, brain computer Intefrace, intelligent transportation, information fusion for decision making and siutation awarenessnes, etc..