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Cheers,

===========================
Jiayang Sun
Professor, Chair, and Bernard Dunn Eminent Scholar
Department of Statistics, George Mason University
Nguyen Engineering Building
4400 University Dr.
Fairfax, VA 22030
703-993-9107 (Office Manager and Asst. to Chair)
703-993-4732 (Direct)


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________________________________
From: Carroll Barbour <[log in to unmask]>
Sent: Wednesday, January 19, 2022 9:57 AM
To: [log in to unmask] <[log in to unmask]>
Subject: Statistics Faculty Candidate Seminar: Thursday, January 20, 2022


Faculty Candidate Seminar



Nicholas Rios

Penn State University

Thursday, January 20, 2022

10:00 A.M. – 11:00 A.M. EDT



The talk will be streamed live via Zoom:

https://gmu.zoom.us/j/99104685278?pwd=Y2hmakh4SnR1SGlhSDBrVGY1Y0Jadz09
Meeting ID: 991 0468 5278

Passcode: 753884

Abstract:

In a mixture experiment, several components are mixed to produce a response. This classical experiment has been studied for a long time, but little attention has been given to the addition order of the components. In an Order-of-Addition (OofA) Mixture experiment, the response depends on both the mixture proportions of components and their order of addition. These experiments surface in many fields, such as food science, chemical engineering, and the pharmaceutical sciences. The overall goal of this experiment is to identify the addition order and mixture proportions that produce an optimal response. Methodology for constructing full OofA Mixture designs is discussed. Models that allow for interaction effects between mixture and order are shown. To create more affordable designs, a Threshold Accepting (TA) algorithm is used to find a subset of rows of the full OofA Mixture design that maximize the D-optimality criterion. Time permitting, I will discuss future work alongside other research areas of interest.



Bio:

Nicholas Rios is a PhD candidate and graduate fellow at the Department of Statistics at Penn State University. His current research focus is on experimental design in the presence of real-world constraints. He is also interested in functional data analysis, computational statistics, Gaussian process modeling of multi-fidelity data, and various applications to chemical engineering and the pharmaceutical industry. He is eager to share the results of his research!