How can we make computers interact more intelligently with us? Does the field of Human/Computer Interface (HCI) suggest challenging new problems for machine learning? This workshop will address these and other related questions. We will focus discussion on five topics in HCI which have the greatest connection to machine learning (shown below). The goal of the workshop is to cross-fertilize HCI with machine learning by fostering discussion between researchers in the two fields.
- User modeling and personalization --- making predictive models of human state and preferences, in order to serve them better.
- Multimodal and perceptual user interfaces --- giving computers one or more senses, to make interaction with people more natural.
- Computerized support for meetings --- meeting capture and retrieval, to make meetings more effective.
- Direct brain-computer interface ---- input to computers directly from the brain.
- Intelligent dialog systems --- systems that can engage in conversations with people.
- Corey Anderson, Google
- Trevor Darrell, MIT AI Lab
- Eric Horvitz, Microsoft Research
- Satinder Singh Baveja, Computer Science and Engineering, University of Michigan