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DESCRIPTION:Coupled Multiphysics Modeling with Machine Learning Presented B
 y: Mr. Kevin Wandke\, PhD Candidate\, University of Illinois at Urbana-Cham
 paign \n\nAbstract: Improvements in computer hardware have enabled engineer
 s to simulate real world  systems with increasing precision and speed. Howe
 ver\, as the rate of improvements in  computing hardware has slowed\, resea
 rchers have begun exploring alternative ways to improve the capabilities of
  computer modeling technologies. In this research talk\, I will examine one
  such  approach that leverages recent advances in machine learning and para
 llel computing to simulate  coupled multiphysics systems. I will begin with
  a brief overview of existing approaches to  simulating these systems\, as 
 well as the drawbacks of these approaches. Next\, I will discuss how  machi
 ne learning can replace these traditional approaches. After that\, I will e
 xamine a workflow  to utilize machine learning to replace conventional iter
 ative solvers as we solve a real-world  simulation problem. To conclude\, I
  will discuss some additional research directions I hope to  explore\, as w
 ell as ways I would be excited to involve students in this project. \n\nBio
 graphy: Kevin Wandke received his B.S. in Mechanical Science and Engineerin
 g in 2019\, and his M.S. in Electrical Engineering in 2022\, both from the 
 University of Illinois at  Urbana-Champaign. He is currently pursuing his P
 h.D. in Electrical and Computer Engineering at University of Illinois at Ur
 bana-Champaign. He previously worked at Argonne National laboratory as a me
 mber of the SULI program\, and at  General Electric's Global research cente
 r as an intern in the  \nEdison Engineering Program. Additionally\, he is t
 he recipient of the Chancellor's Scholarship\, Olsen award for Excellence i
 n Undergraduate Teaching\, and a Mavis Future Faculty Fellow in the Grainge
 r College of  Engineering. Kevin’s research focuses on two major themes\, c
 omputational modeling\, and  pedagogy. Within the theme of computational mo
 deling\, he has focused on ways to use machine  learning to accelerate the 
 modeling of complex multiphysics processes. Within the area of  pedagogy\, 
 Kevin has focused on ways to provide adaptive instruction\, as well as ways
  to deliver  content through various modalities to improve the learning exp
 eriences of students.
DTEND:20231212T160000Z
DTSTAMP:20260317T032927Z
DTSTART:20231212T150000Z
GEO:42.786861;-86.104963
LOCATION:A. Paul Schaap Science Center\, 1019
SEQUENCE:0
SUMMARY:Engineering Seminar: Mr. Kevin Wandke
UID:tag:localist.com\,2008:EventInstance_44959250499826
URL:https://calendar.hope.edu/event/engineering_seminar_mr_kevin_wandke
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