<div dir="ltr"><div class="gmail_quote"><br><div><div><p><b><font color="#ff0000"><img alt="SDSU_CSRC Logo.jpg" width="534px" height="107px" src="cid:51a615b7-551e-49c3-a78f-d4ad59d4917f"><br></font></b></p><p><b><font color="#ff0000" size="4"><br>**** Registration is required in order to get the link to join the seminar online. Please register at the below web page.<br><br></font></b><b><font size="4" color="#ff0000">**** There Will Be An In Person Viewing Party In GMCS 314.</font></b><b><font color="#ff0000" size="4"><br></font></b></p><p><br></p><p><font size="4">DATE: <br><b>Friday, October 1, 2021</b></font></p><p><br></p><div dir="ltr"><p></p><p></p><p><font size="4">TITLE:<br><b>Informing Missing Physics with Model Form Error and Model Selection </b> </font> <b> </b> <b> </b> </p><div><br></div><p><font size="4">TIME: <br><b>3:30-5:00PM</b></font></p><p> <br></p><p><font size="4">LOCATION:<br><b>Registration is required in advance. Please register at the following site to receive information on how to join the seminar online. </b><a href="https://us06web.zoom.us/meeting/register/tZ0rcu-rpzkuHNwQ_Stp9FX-Sw-X4QQ5YlY0" target="_blank">Meeting Registration - Zoom</a><br><b>or</b><br></font><b><font size="4">Viewing Party - GMCS 314</font></b></p><p><br><font size="4">SPEAKER/BIO: <br><b>Dr. Kathryn A. Maupin, Senior Member of the Technical Staff, Optimization and Uncertainty Quantification, Sandia National Laboratories</b> </font><b> </b> </p><p><br></p><p><font size="4">ABSTRACT:</font></p></div><div dir="ltr"><p><font size="4">Despite continuing advances in statistical inversion and modeling, model inadequacy due to model form error remains a concern in all areas of mathematical modeling. Much like physical models, calibrating a discrepancy model requires careful consideration regarding formulation, parameter estimation, and uncertainty quantification, each of which is often problem-specific. At the intersection of model form error quantification and model selection lies a systematic methodology for identifying and characterizing model form error as a means of identifying missing physics or unknown phenomena, which has the potential to inform model development and experimental design. One such methodology is presented.</font><br><br><font size="4">*Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.</font><br></p><p><font size="4">Bio:
Kathryn Maupin is a Senior Member of the Technical Staff at Sandia National Laboratories. Her research focuses on model form error quantification and multiobjective surrogate modeling. Broader research interests include Bayesian methods, model validation, sensitivity analysis, and uncertainty quantification. Kathryn joined Sandia as a postdoc in 2016 and converted to a staff position in 2018. She received her Ph.D. in Computational Sciences, Engineering and Mathematics and her M.S. in Computational and Applied Mathematics from the University of Texas at Austin after completing her B.A. in Applied Mathematics at the University of California, San Diego. When she is not working, Kathryn spends her time playing with her two girls and three dogs.</font><br><br><br><a href="https://cfwebprod.sandia.gov/cfdocs/CompResearch/templates/insert/dept.cfm?org=01463" target="_blank"><font size="4">Department Website</font></a></p></div><div dir="ltr"><br></div><div dir="ltr"><br></div><font size="4">Host:<br><b>Rodrigo Navarro Perez</b><br></font><div><font size="4"><br><br></font></div><div><p><font size="4"><span style="font-weight:bold">Note:</span><span style="font-weight:bold"> </span>Videos of previous colloquium talks can be seen on the CSRC website in the colloquium archive section or on the <a href="https://www.youtube.com/channel/UCN0ZEztlmyDqG2pm-Rle_Eg/feed" target="_blank">CSRC YouTube page here</a>.</font></p><p><br><br></p></div></div><br></div><div><br></div>
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