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UID:0-8199@eng.ufl.edu
DTSTART;TZID=America/New_York:20260210T114000
DTEND;TZID=America/New_York:20260210T123000
DTSTAMP:20260209T164955Z
URL:https://www.eng.ufl.edu/news-events/events/ise-special-seminar-russell
 -barton/
SUMMARY:ISE Special Seminar: Russell Barton
DESCRIPTION:"Response Grid Plots for Model-Agnostic Machine Learning Insigh
 t"\nRussell R. Barton\, Penn State\nAbstract\nMachine learning (ML) models
  are used to provide predictive characterization of response functions bas
 ed on observed or simulated data. Insight on the nature of the approximati
 on to the underlying response function is essential for the model output t
 o be trusted and used by decision makers. When a response function is well
 -behaved\, methods that identify marginal effects and interactions for imp
 ortant input variables can provide adequate insight on its nature. Alterna
 tively\, interpretable ML models can provide an ensemble of simple models 
 to decompose a complex response into interpretable elements. This talk int
 roduces a model-generated but model-independent visual display of function
 al information that provides direct insight\, not interpreted through mode
 l form\, model coefficients\, or numerical characterizations such as those
  produced by sensitivity analysis. Further\, the method can be applied dir
 ectly to system response data if the data are collected from a factorial (
 grid) design. The value of response grid plots (RGPs) is shown through sev
 eral examples.\nBrief Biography for Russell Barton\nRussell Barton is Dist
 inguished Professor Emeritus of Supply Chain and Information Systems and D
 istinguished Professor Emeritus of Industrial Engineering at Penn State. H
 e holds a B.S. in electrical engineering from Princeton University\, and M
 .S. and Ph.D. degrees in operations research from Cornell University. Dr. 
 Barton's research focuses on the interface between applied statistics\, si
 mulation\, and product design and manufacturing. He is the author of two b
 ooks: Graphical Methods for the Design of Experiments and Predictive Analy
 tics for Business Using R. He served as Associate Editor for the INFORMS J
 ournal on Computing\, IIE Transactions\, Operations Research\, Naval Resea
 rch Logistics\, Management Science\, and the Institute of Mathematics and 
 Its Applications IMA Journal of Management Mathematics. He served as Chair
  of the INFORMS Subdivisions Council\, and on the INFORMS Board of Directo
 rs as Vice President of INFORMS Sections and Societies. He is a Fellow of 
 IISE and INFORMS\, and a Senior Life Member of IEEE. His is a Certified An
 alytics Professional – Expert (CAP-X®) and has served on the Analytics 
 Certification Board.
CATEGORIES:Seminars
LOCATION:406 Weil Hall &amp\; Zoom\, 1949 Stadium Dr\, Gainesville\, FL\, 3
 2611\, United States
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1949 Stadium Dr\, Gainesvil
 le\, FL\, 32611\, United States;X-APPLE-RADIUS=100;X-TITLE=406 Weil Hall &
  Zoom:geo:0,0
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