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Applications of and Challenges Associated With Stochastic Optimization "In the Wild"

Due to recent advances in both mathematics and algorithmics, stochastic	optimization models are	now to the point
where they are starting	to become computationally tractable at reasonable scales. However, significant challenges
remain on both fronts, in terms of both problem classes and application environments that can be addressed. In this
talk, I will discuss key applications of stochastic optimization in two large and related application spaces: critical
infrastructure protection and power systems operations / planning. The talk will focus on both the applications
themselves and mathematical and computational challenges that are inhibiting the broader adoption of stochastic
optimization in these contexts.

Dr. Jean-Paul Watson is a Distinguished Member of Technical Staff in the Discrete Math and Optimization Department
in the Center for Computing Research at Sandia National Laboratories, sited in Albuquerque, New Mexico. Dr. Watson
specializes in the development and analysis of scalable solvers for stochastic optimization, with specific application
to power and related critical infrastructure systems. He also has significant expertise in the development and
deployment of open-source optimization software, including Pyomo (http://www.pyomo.org).

A career Q&A session will follow immediately after the presentation. Graduate students are especially encouraged to attend.