Simulation methods and multi-scales extrapolation
Sophisticated techniques are required to weave together available data and often incomplete scientific knowledge about the underlying physical processes into models that can be used to forecast risks at scales relevant to practical decision making. Methods are needed to simulate rare events and to evaluate systems and design under uncertainty for all kinds of models from simple arithmetic expressions to complex finite-element or differential-equation codes.
Decision making in complex systems and environments
Although people routinely make many successful decisions every day under various risks and in the face of considerable uncertainties, they can often be misled into extremely poor decisions by their cognitive biases. Methods are needed that engineers can use to ensure they do not make such errors.