The increase in computational resources in the past decades has resulted in computationally expensive numerical simulations appearing in nearly all scientific domains. Often times, domain scientists wish to identify inputs to the simulation that produce some form of optimal behavior. In this talk, we focus on algorithmic approaches for optimizing such computationally expensive functions, and highlight motivating problems from Argonne National Laboratory. No foreknowledge of numerical optimization is assumed; pictures will be used throughout the presentation.
Jeffrey Larson is an assistant computational mathematician at Argonne. His research centers on optimization algorithms and their implementation in software. Jeff joined Argonne in 2014 as a postdoctoral appointee. He was previously a postdoctoral researcher with the Royal Institute of Technology KTH in Sweden. He earned his Ph.D. in applied mathematics from the University of Colorado, Denver in 2012.
Lunch will be provided for those that RSVP at least 24 hours prior to the seminar.