June 7, 2026
San Diego, CA, USA
In conjunction with AIAA Aviation Forum 2026
Multifidelity methods are a broad class of computational engineering methods that use both expensive, high-fidelity physics simulations and cheaper, lower-fidelity approximations to support engineering design and decision-making. Multifidelity methods target a broad range of many-query computations — including optimization, uncertainty quantification, control, and modern machine learning — in which simulations must be run many times at different parameters or inputs. The cheaper low-fidelity models are used to reduce the overall computational cost of the computation, often by multiple orders of magnitude, while the high-fidelity model is used to guarantee accuracy. This workshop will present a series of tutorial-style lectures that introduce multifidelity methods to the practitioner while highlighting both successful applications of the methods in aerospace design as well as recent methodological advances, particularly at the intersection of multifidelity methods and machine learning. Participants will also discuss open challenges and opportunities in a panel session with experts in multifidelity design, uncertainty quantification, and machine learning.
Sponsored by the AIAA Multidisciplinary Design Optimization Technical Committee (MDO TC)
Organizing Committee