ABSTRACT: Electronic health records (EHRs) offer great promises in advancing clinical research and transforming learning health systems. However, complex, temporal EHRs are fraught with biases and present daunting analytical challenges that, if not addressed, can exacerbate health inequities. EHRs data, recorded at irregular time intervals with varying frequencies, are multi-modal and multi-scale including structured data […]
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ABSTRACT: How can A.I.-based methods inform social listening applications during public health crises? The COVID-19 pandemic has uprooted the mode and method of human communication and interaction. The magnitude of the pandemic has led to an ‘infodemic’ along with considerable increase in stress and anxiety across communities. At the same time, the use of social […] |
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ABSTRACT: Building robust decision making systems for autonomous systems is challenging. Decisions must be made based on imperfect information about the environment and with uncertainty about how the environment will evolve. In addition, these systems must carefully balance safety with other considerations, such as operational efficiency. Typically, the space of edge cases is vast, placing a large […] |
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ABSTRACT: An important goal of the field sensorimotor robot learning is to do away with cumbersome expertise-intensive task specification, so that general-purpose robots of the future might learn large numbers of new skills. In this talk, I will discuss our recent work on algorithms that exploit goals as a versatile and accessible task specification interface. Goals might […] |
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