Decision-Making Under Risk in Complex Environments

Abstract

Advances in uncertainty quantification enable more nuanced exploration of decision-making under risk in complex environments. Although many such routines are domain-specific, we develop a generic framework leveraging large deviation statistics and probabilistic optimization that makes it possible to evaluate and hedge against both parametric (e.g., extreme weather) and non-parametric (e.g., cyberattacks) events. This framework also enables framing such instances of decision-making under risk in complex environments as a “missing money” problem, which is well known in economics and provides efficient economic signal to mitigate cost of such events.

Brief Biography

Yury Dvorkin is an Associate Professor at the Department of Civil and Systems Engineering and at the Department of Electrical Computer Engineering at Johns Hopkins University (JHU), where he is also part of JHU's Ralph O'Connor Sustainable Energy Institute and the US Director of the NSF Global Climate Center on Electric Power Innovation for a Carbon-free Society (EPICS).