I am a Masters student in the College of Computing at the Georgia Institute of Technology. I am working as a graduate research assistant to Dr. Andrea Thomaz at Socially Intelligent Machine Lab.

My research goals are to make robotic technology accessible to ordinary people and to leverage social robots as therapeutic devices for social deficits, assistants for elders and disabled people, and educational partners for children. This goal shapes my research interests into three main streams: artificial intelligence that explores how robots represent and reason upon the dynamic world, machine learning that studies how robots effectively learn from past experience and human partners, and human-robot interaction that probes into with what modalities and mechanism people better interact with robots in their everyday lives.

My current research work, developing a computational model of joint attention and implementing affective components on a humanoid robot, is leading me toward my research goal. Joint attention is an important stage in infant development and a crucial component for establishing common ground between agents in interaction. In addition, affective robots can induce preferred behaviors from people, and people are inclined to apply social understanding to affective robots. All these efforts are providing better ways for natural human-robot interaction.

Before graduate study at Georgia Tech, I was a research assistant to Dr. Chun-Nan Hsu at Insititute of Information Science at Academia Sinica. There I was focusing on clustering and classification of scientific data.

-Sociable Robots
-Human-Robot Interaction
-Learning by Demonstration
-Multi-Robot system, Self-* Systems
-Machine Learning
-Biologically-Inspired Computing
-Cognitive Computing

cmhuang[at]gatech[dot]edu