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Generally, I am interested in building machine learning algorithms that can transfer knowledge across very wide task distributions, which humans can do to a great extent. When a human toddler is learning basic motor control from scratch, they are able to learn tasks - such as twisting a door knob and grasping a bottle in hand - in a way that allows them to distill fundamental skills from these tasks. These skills can be transferred to quickly perform new but related tasks, such as simultaneously grasping a bottle and twisting that bottle's cap open. Current machine learning methods aren't able to perform such general transfer of knowledge across tasks in motor control or any other domain, and my goal is to build systems that can.
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