Comet Calendar

Statistics Seminar by Ying Hung (Rutgers)

Friday, April 28 at 11:00am to 12:00pm

Sciences Building (SCI), 2.210
800 W. Campbell Road, Richardson, Texas 75080-3021

Functional-Input Gaussian Processes with Applications to Inverse Scattering Problems.

Surrogate modeling based on Gaussian processes (GPs) has received increasing attention in the analysis of complex problems in science and engineering. Despite extensive studies on GP modeling, the developments for functional inputs are scarce. Motivated by an inverse scattering problem in which functional inputs representing the support and material properties of the scatterer are involved in the partial differential equations, a new class of kernel functions for functional inputs is introduced for GPs. Based on the proposed GP models, the asymptotic convergence properties of the resulting mean squared prediction errors are derived and the finite sample performance is demonstrated by numerical examples. In the application to inverse scattering, a surrogate model is constructed with functional inputs, which is crucial to recover the reflective index of an inhomogeneous isotropic scattering region of interest for a given far-field pattern.

UTD strives to create inclusive and accessible events in accordance with the Americans with Disabilities Act (ADA). If you require an accommodation to fully participate in this event, please contact the event coordinator (listed below) at least 10 business days prior to the event. If you have any additional questions, please email and the AccessAbility Resource Center at

Event Type

Lectures & Workshops

Target Audience

Undergraduate Students, Faculty & Staff, Graduate Students




math, statistics, data science, stat.spring2023


Natural Sciences & Mathematics
Contact Information
Chuan-Fa Tang
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