Dr. Juan Rojas is an Assistant Professor with the Raymond B. Jones College of Engineering at Lipscomb University in the Electrical and Computer Engineering Department.
My current research interests lie in intelligent robot decision-making in various modalities multi-agent and single-agent scenarios like Human-Robot Interaction; Multi-Robot Interaction; manipulation in service, logistics, and industrial settings. The work starts by helping robots understand (model) human, robot, and environmental behavior. As a robot better understands human actions and intentions as well as its own, and how its interactions change the world, the robot can then intelligently respond to situations. A robot is better able to learn manipulation, predict the world; sense impending anomalies; and gracefully recover from them. Predictive modeling is useful to more efficiently help a robot assist humans or respond to the world. To this end, we develop multimodal time-series-based models and decision-making to aid the robot to interact with the world. I use statistical methods, machine learning, deep learning, and deep reinforcement learning fundamentals across my work.