Research goals

Our research aims to use ideas from artificial intelligence to improve the daily lives of people that are living with Type 1 Diabetes.

At the heart of state-of-the-art artificial intelligence research lies Reinforcement Learning — the study of how to learn from unknown environments. It was listed as one of the top 10 emerging technologies in 2017 by MIT Technology Review.

RL is particularly suited in situations where:

  • decisions are made sequentially along a timeline
  • the actions taken depend on an observed state that is changing over time
  • the effects manifest at later points in time than the actions that induced them, and there is some notion of preferred state(s).

All of these features are certainly present in the T1D controller challenge.

In addition to the T1D controller challenge, our research has fostered several side tracks:

  • Reinforcement learning for Climatology applications
  • Feature representation for reinforcement learning using functional data analysis

 

For recent updates and interesting information, please check out our blog!

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