Brittany Duncan represents TEES at Congressional Unmanned Systems Caucus' Science and Technology Fair

Image of Brittany DuncanBrittany Duncan, a Ph.D. student in the Department of Computer Science and Engineering at Texas A&M University, was featured in the press release for the Congressional Unmanned Systems Caucus' Science and Technology Fair in Washington, D.C., Sept. 19.

Pictured: An unmanned aerial vehicle from the AI Robotics Lab (left) and Brittany Duncan speaking with Congressman Henry Cuellar (right).

Brittany represented research in small unmanned aerial vehicles by the Texas A&M Engineering Experiment Station (TEES) as part of the Lone Star Unmanned Aerial System Center led by Texas A&M University-Corpus Christi, which is pursuing funding as a FAA Center of Excellence.

The U.S. House Unmanned Systems Caucus educates members of Congress and the public on the strategic, tactical, and scientific value of unmanned systems. The Caucus also supports the further development and acquisition of unmanned systems, as well as engages the civilian aviation community on unmanned system use and safety.

Brittany's area of study is Rescue Robotics, specifically unmanned aerial vehicles (UAV). She is the team lead for the AI Robotics lab's UAV team working on the use of unmanned aerial vehicles for public safety applications. UAVs for public safety is central to three TEES centers that CSE faculty are engaged in: the Center for Robot-Assisted Search and Rescue, the Center for Emergency Informatics, and the Center for Autonomous Vehicles and Sensor Systems.

"It was an honor to be asked to speak to the Unmanned Systems Caucus to present the hands-on research we conduct at Disaster City," Duncan said.

Brittany is a National Science Foundation Graduate Fellow and a 2009 graduate of the Georgia Institute of Technology with a B.S. in computer science with honors. She is advised by Raytheon Professor of Computer Science and Engineering Robin Murphy. Murphy is recognized as a founder of the fields of rescue robots and human-robot interaction.