on interdependence for teams (human-machine teams).
He advised the Naval Research and Development Enterprise’s Applied Artificial Intelligence Summit in 2018; coedited four books; published widely; and co-organized eight
AAAI symposia at Stanford with a ninth in 2019 on shared
context.
Ranjeev Mittu is the Branch Head for the Information
Management and Decision Architectures Branch within
the Information Technology Division, US Naval Research
Laboratory. His research expertise is in multi-agent systems,
artificial intelligence, machine learning, data mining, pattern recognition and anomaly detection. He has won an
award for transitioning technology solutions to the operational community, and has coauthored one book, coedited
four books, and written numerous book chapters, articles,
and conference publications. He has served on scientific
exchanges, as a subject matter expert and Technology Evaluation Boards. He has an MS in Electrical Engineering from
The Johns Hopkins University.
Donald Sofge is a computer scientist and roboticist at
the U.S. Naval Research Laboratory (NRL) with more than
30 years of experience in AI and Control Systems R&D.
He has served as PI or Co-PI on dozens of federally funded
R&D programs, and has numerous publications on autonomy, intelligent control, quantum computing, including
5 books and one patent. He leads the Distributed Autonomous Systems Group at NRL where he develops nature-inspired computing solutions to problems in sensing,
AI, and autonomous robotic systems control, including
autonomous teams or swarms of robotic systems for Navy
missions.
Laura Hiatt is a research scientist at the U.S. Naval Research Laboratory. She received her BS in symbolic systems from Stanford University and her PhD in computer
science from Carnegie Mellon University. Hiatt’s work has
primarily focused on ways in which humans and robots
can effectively work together as teammates. The research
involves issues of planning and reasoning, human situational awareness, and team-based task communication
strategies. Much of her work has also involved developing
computational cognitive models of human cognition, and
leveraging them to improve the ability of robots to team
with humans and accomplish their tasks.
