Focused on developing multimodal time-series-based models for aiding robots' interaction with the world, utilizing statistical methods, machine learning, deep learning, and deep reinforcement learning.
Background
An Assistant Professor in the Electrical and Computer Engineering Department at Lipscomb University, Raymond B. Jones College of Engineering. Research interests include intelligent robot decision-making in multi-agent and single-agent scenarios such as Human-Robot Interaction; Multi-Robot Interaction; and manipulation in service, logistics, and industrial settings. The research focuses on helping robots understand human, robot, and environmental behavior to intelligently respond.