Risk Management Collaboratory - overview

Making rigorous decision making under uncertainty scalable within a business environment

Our project investigates methods and algorithms to improve the effectiveness in the use of risk models in decision making.

A team of researchers from IBM is collaborating with faculty and students from Irish universities (University College Cork, Dublin City University and University College Dublin) along four research axes:

  • Natural Language Processing: Simplify the creation of risk models by extracting risk information from structured and unstructured data, with a focus on text.
  • Imprecise Probability: Lessen the input requirements for risk models by develop efficient decision theoretic algorithms to work with imprecise probabilistic information such as ranges or orders of magnitude.
  • Constraint Programming applied to Stochastic Optimization: Find effective way of solving complex stochastic problems by combining constraint programming with stochastic programming and address fundamental challenges in risk-based optimization.
  • Risk Communication Experiment with novel ways for users to communicate about and interact with risk information through the development of novel risk visualization support and the refactoring of a web-based expert elicitation tool.

    • Curious? Take our survey about the communication of side effects of prescription medicine.

      We describe the research objectives and activities for each sub-project in a separate section (see left).