Justin Hart

Justin Hart is an Assistant Professor of Practice at the University of Texas at Austin's College of Natural Sciences, Department of Computer Science. He is also a postdoctoral fellow affiliated with the Building-Wide Intelligence Project and the Learning Agents Research Group under Professor Peter Stone. His research focuses on semantic mapping, autonomous human-robot interaction, and AI representations for service robots.

• Education: M.S., M.Phil, Ph.D. in Computer Science from Yale University; M.Eng from Cornell University; B.S. from West Virginia University.

Hart's research spans Artificial Intelligence, Human-Computer Interaction, and Intelligent Robotics, with a focus on enabling technologies for general-purpose service robots. His work explores comprehensive systems for autonomous interaction, semantic mapping, and interpretable AI. Recent publications emphasize human-robot communication, natural language grounding, and ecological modeling in robotics.

Notable research trends include:

• Human-robot interaction using light-based signals
• Active learning for language grounding
• Self-modeling and ecological cognition in humanoid robots
• Novel AI architectures for service robotics applications

Scientific accolades include the 2013 Society of Manufacturing Engineers Innovation Watch List. Hart collaborates with the Learning Agents Research Group and has contributed to advancements in robot self-modeling and perspective-taking.

His work bridges theoretical cognitive science and practical robotics, developing systems that combine sensorimotor integration, grounded language understanding, and interpretable human-robot communication frameworks.