I seek effective means for engineering software for complex embedded systems, equipped with sensors and actuators. My group and I have developed statistical algorithms for perception, learning and decision making in robotics (see introductory report). We have applied these algorithms to various problems in mobile robotics, such as exploration, map learning, human robot interaction, and multi-robot team coordination (see 3D maps). Two of our mobile robots were deployed as
I am equally interested in machine learning. I believe learning and teaching should be seamlessly integrated into mainstream software development. My current research focuses on programming languages that support learning from experience and probabilistic computation (see preliminary report). In the past, I also worked on lifelong learning algorithms, which enable agents to transfer knowledge among families of related learning tasks (see book and thesis).
For complete current information on my research, please see my SCS homepage.
|Research Interest Keywords|
|artificial intelligence, computer vision, gesture recognition, human-computer interaction, machine learning, mobile robots, multi-agent systems, sensor fusion, statistics|
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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