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Guidance and Control Seminar - Robots Learning from Human Teachers

Tuesday, January 27, 2015
3:30 pm

WRW 113

Abstract: In this talk I present recent work from the Socially Intelligent Machines Lab at Georgia Tech.  

Our research aims to computationally model mechanisms of human social learning in order to build robots and other machines that are intuitive for people to teach.  We take Machine Learning interactions and redesign interfaces and algorithms to support the collection of learning input from naive humans.  This talk covers results on building computational models of reciprocal interactions, high-level task goal learning, low-level skill learning, and active learning interactions using several humanoid robot platforms.  

Bio: Andrea L. Thomaz is an Associate Professor of Interactive Computing at the Georgia Institute of Technology. She directs the Socially Intelligent Machines lab, which is affiliated with the Robotics and Intelligent Machines (RIM) Center and with the Graphics Visualization and Usability (GVU) Center. She earned a B.S. in Electrical and Computer Engineering from the University of Texas at Austin in 1999, and Sc.M. and Ph.D. degrees from MIT in 2002 and 2006. Dr. Thomaz has published in the areas of Artificial Intelligence, Robotics, and Human-Robot Interaction. She received an ONR Young Investigator Award in 2008, and an NSF CAREER award in 2010. Her work has been featured on the front page of the New York Times, on NOVA Science Now, she was named one of MIT Technology Review’s Top 35 under 35 in 2009, and on Popular Science Magazine’s Brilliant 10 list in 2012.​

Contact  Maruthi Akella at 512-471-9493 or makella@mail.utexas.edu