Minh Hoai Nguyen's research interests are in computer vision, machine learning, and time series analysis. His recent research focuses on creating algorithms that recognize human actions, gestures, and expressions in video. Such successful algorithms will be widely useful, e.g., to improve video surveillance systems, to advance human-computer interaction, and to assist medical diagnosis of behavioral disorders. Minh Hoai Nguyen's research extends to three areas that support it: computer vision, time series analysis, and machine learning. His work studies video data, and computer vision addresses video representation and processing. Time series analysis studies how human actions, gestures, and expression can be modeled, which is the critical foundation to detect and recognize them. Machine learning is a core component of his research because visual interpretation algorithms are so complex that they need to be trained rather than hand-designed.