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Research Experiences for Undergraduates:
Integrated
Machine Learning Systems
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The Symbiotic Computing Laboratory is dedicated to the study of
the symbiotic relationships between humans and machines. In particular, we examine:
- machines as models of how biological systems represent and learn motor
and cognitive skills,
- primates as inspiration for new robot control
and learning techniques, and
- the interaction of humans with machines.
Our specific areas of research include:
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Computational Neuroscience and Motor Control:
models of the interaction between muscle and spinal circuitry;
motor skill representation and learning within cortex, cerebellum,
and basal ganglia;
and brain-machine interfaces.
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Human-Machine Interaction:
wearable and ubiquitous computing; sensor networks; pervasive, ambient interfaces;
robot learning through human interaction; interactive art.
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Robot Sensing and Manipulation:
control of reaching, grasping, and manipulation;
visual and haptic sensing for manipulation;
and representing affordances in support of planning, learning, and recognition.
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Machine/Robot Learning:
hybrid models of reinforcement and supervised learning;
learning action-oriented representations; and
learning motor skills through human interaction and through
exploration with the surrounding environment.
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