Applied/ACMS: Difference between revisions
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*'''When:''' Fridays at 2:25pm | __NOTOC__ | ||
= Applied and Computational Mathematics Seminar = | |||
*'''When:''' Fridays at 2:25pm (except as otherwise indicated) | |||
*'''Where:''' 901 Van Vleck Hall | *'''Where:''' 901 Van Vleck Hall | ||
*'''Organizers:''' [https://www.math.wisc.edu/~spagnolie/ Saverio Spagnolie], [https://people.math.wisc.edu/~rycroft/ Chris Rycroft], and [https://sites.google.com/view/laurel-ohm-math Laurel Ohm] | |||
*'''To join the ACMS mailing list:''' Send mail to [mailto:acms+join@g-groups.wisc.edu acms+subscribe@g-groups.wisc.edu]. | |||
<br> | <br> | ||
{| | == '''Fall 2025''' == | ||
{| cellpadding="8" | |||
! align="left" |Date | |||
! align="left" |Speaker | |||
! align="left" |Title | |||
! align="left" |Host(s) | |||
|- | |- | ||
| | |Sep 19* | ||
| | |[https://www.anl.gov/profile/zichao-di Zichao (Wendy) Di] (Argonne National Laboratory) | ||
|Multimodal Inverse Problems and Multilevel Optimization for X-ray Imaging Science | |||
| | |Rycroft/Li | ||
|- | |- | ||
| | |Sep 26 | ||
|[https://scholar.google.com/citations?user=Imuw5CMAAAAJ&hl=en&oi=ao Pouria Behnoudfar] (UW) | |||
|TBD | |||
| | |Spagnolie | ||
|- | |- | ||
| | |Oct 3 | ||
| | | | ||
| | | | ||
| | | | ||
|- | |- | ||
| | |Oct 10* | ||
|[https://www.alexandriavolkening.com Alexandria Volkening] (Purdue) | |||
| | |TBD | ||
|Rycroft | |||
| | |||
|- | |- | ||
| | |Oct 17* | ||
|[https://www.nickderr.me/ Nick Derr] (UW) | |||
| | |TBD | ||
| | |Spagnolie | ||
|- | |- | ||
| | |Oct 24 | ||
|[https://cims.nyu.edu/~oneil/ Mike O'Neil] (Courant) | |||
| | |TBD | ||
| | |Spagnolie | ||
|- | |- | ||
| | |Oct 31 | ||
|[https://people.math.wisc.edu/~hhong78/ Hyukpyo Hong] (UW) | |||
| | |TBD | ||
|Spagnolie | |||
| | |||
|- | |- | ||
| | |Nov 7* | ||
|[https://thales.mit.edu/bush/ John Bush] (MIT) | |||
| | |TBD | ||
| | |Spagnolie | ||
|- | |- | ||
| | |Nov 14 | ||
|[https://sites.google.com/andrew.cmu.edu/yukunyue/home Yukun Yue] (UW) | |||
| | |TBD | ||
| | |Spagnolie | ||
|- | |- | ||
| | |Nov 21* | ||
|[https://jesnial.github.io/ Jessie Levillain] (CNES/INSA Toulouse) | |||
| | |TBD | ||
| | |Ohm | ||
|- | |- | ||
| | |Nov 28 | ||
| | |Thanksgiving | ||
| | | | ||
| | | | ||
|- | |- | ||
| | |Dec 5 | ||
|[https://mesomod.weebly.com/ Jiamian Hu] (UW; Engineering) | |||
| | |TBD | ||
| | |Chen | ||
|- | |- | ||
| | |Dec 12 | ||
|[https://sites.google.com/a/brandeis.edu/tfai/home Thomas Fai] (Brandeis) | |||
|TBD | |||
|Rycroft | |||
| | |||
| | |||
|} | |} | ||
''[Dates marked with an asterisk are close to weekends with a home game for the [https://uwbadgers.com/sports/football/schedule UW Badgers football team]. Hotel availability around these dates is often limited if booked on short notice.]'' | |||
==Abstract== | |||
<div id="Chandler"> | |||
'''Zichao (Wendy) Di (Argonne National Laboratory)''' | |||
Title: Multimodal Inverse Problems and Multilevel Optimization for X-ray Imaging Science | |||
X-ray imaging experiments generate vast datasets that are often incomplete or ill-posed when considered in isolation. One way forward is multimodal data analysis, where complementary measurement modalities are fused to reduce ambiguity and improve reconstructions. A key question, both mathematically and practically, is how to identify which modalities to combine and how best to integrate them within an inverse problem framework. | |||
A second line of work focuses on the computational challenge: even for single-modality inverse problems, the resulting optimization problems are large-scale, nonlinear, and nonconvex. Here, I will discuss multilevel optimization and stochastic sampling strategies that accelerate convergence by exploiting hierarchical structure in both parameter and data spaces. | |||
Although developed separately, these two directions point toward a common goal: building scalable, optimization-based frameworks that make the best use of diverse data to enable new discoveries in X-ray imaging science.<div id="Fraser"><div id="Luedtke"><div id="Zhdankin"><div id="Boffi"><div id="Shankar"><div id="Loevbak"> | |||
<div id="Lu"><div id="Vogman"><div id="Cockburn"> | |||
== Archived semesters == | == Archived semesters == | ||
*[[Applied/ACMS/Spring2025|Spring 2025]] | |||
*[[Applied/ACMS/Fall2024|Fall 2024]] | |||
*[[Applied/ACMS/Spring2024|Spring 2024]] | |||
*[[Applied/ACMS/Fall2023|Fall 2023]] | |||
*[[Applied/ACMS/Spring2023|Spring 2023]] | |||
*[[Applied/ACMS/Fall2022|Fall 2022]] | |||
*[[Applied/ACMS/Spring2022|Spring 2022]] | |||
*[[Applied/ACMS/Fall2021|Fall 2021]] | |||
*[[Applied/ACMS/Spring2021|Spring 2021]] | |||
*[[Applied/ACMS/Fall2020|Fall 2020]] | |||
*[[Applied/ACMS/Spring2020|Spring 2020]] | |||
*[[Applied/ACMS/Fall2019|Fall 2019]] | |||
*[[Applied/ACMS/Spring2019|Spring 2019]] | |||
*[[Applied/ACMS/Fall2018|Fall 2018]] | |||
*[[Applied/ACMS/Spring2018|Spring 2018]] | |||
*[[Applied/ACMS/Fall2017|Fall 2017]] | |||
*[[Applied/ACMS/Spring2017|Spring 2017]] | |||
*[[Applied/ACMS/Fall2016|Fall 2016]] | |||
*[[Applied/ACMS/Spring2016|Spring 2016]] | |||
*[[Applied/ACMS/Fall2015|Fall 2015]] | |||
*[[Applied/ACMS/Spring2015|Spring 2015]] | |||
*[[Applied/ACMS/Fall2014|Fall 2014]] | |||
*[[Applied/ACMS/Spring2014|Spring 2014]] | |||
*[[Applied/ACMS/Fall2013|Fall 2013]] | |||
*[[Applied/ACMS/Spring2013|Spring 2013]] | |||
*[[Applied/ACMS/Fall2012|Fall 2012]] | |||
*[[Applied/ACMS/Spring2012|Spring 2012]] | |||
*[[Applied/ACMS/Fall2011|Fall 2011]] | |||
*[[Applied/ACMS/Spring2011|Spring 2011]] | |||
*[[Applied/ACMS/Fall2010|Fall 2010]] | *[[Applied/ACMS/Fall2010|Fall 2010]] | ||
*[http://www.math.wisc.edu/~ | <!-- | ||
*[http://www.math.wisc.edu/~ | *[http://www.math.wisc.edu/~jeanluc/ACMS/archive/Spring10.html Spring 2010] | ||
*[http://www.math.wisc.edu/~ | *[http://www.math.wisc.edu/~jeanluc/ACMS/archive/Fall09.html Fall 2009] | ||
*[http://www.math.wisc.edu/~ | *[http://www.math.wisc.edu/~jeanluc/ACMS/archive/Spring09.html Spring 2009] | ||
*[http://www.math.wisc.edu/~ | *[http://www.math.wisc.edu/~jeanluc/ACMS/archive/Fall08.html Fall 2008] | ||
*[http://www.math.wisc.edu/~ | *[http://www.math.wisc.edu/~jeanluc/ACMS/archive/Spring08.html Spring 2008] | ||
*[http://www.math.wisc.edu/~ | *[http://www.math.wisc.edu/~jeanluc/ACMS/archive/Fall07.html Fall 2007] | ||
*[http://www.math.wisc.edu/~ | *[http://www.math.wisc.edu/~jeanluc/ACMS/archive/Spring07.html Spring 2007] | ||
*[http://www.math.wisc.edu/~jeanluc/ACMS/archive/Fall06.html Fall 2006] | |||
--> | |||
<br> | <br> |
Latest revision as of 02:58, 5 September 2025
Applied and Computational Mathematics Seminar
- When: Fridays at 2:25pm (except as otherwise indicated)
- Where: 901 Van Vleck Hall
- Organizers: Saverio Spagnolie, Chris Rycroft, and Laurel Ohm
- To join the ACMS mailing list: Send mail to acms+subscribe@g-groups.wisc.edu.
Fall 2025
Date | Speaker | Title | Host(s) |
---|---|---|---|
Sep 19* | Zichao (Wendy) Di (Argonne National Laboratory) | Multimodal Inverse Problems and Multilevel Optimization for X-ray Imaging Science | Rycroft/Li |
Sep 26 | Pouria Behnoudfar (UW) | TBD | Spagnolie |
Oct 3 | |||
Oct 10* | Alexandria Volkening (Purdue) | TBD | Rycroft |
Oct 17* | Nick Derr (UW) | TBD | Spagnolie |
Oct 24 | Mike O'Neil (Courant) | TBD | Spagnolie |
Oct 31 | Hyukpyo Hong (UW) | TBD | Spagnolie |
Nov 7* | John Bush (MIT) | TBD | Spagnolie |
Nov 14 | Yukun Yue (UW) | TBD | Spagnolie |
Nov 21* | Jessie Levillain (CNES/INSA Toulouse) | TBD | Ohm |
Nov 28 | Thanksgiving | ||
Dec 5 | Jiamian Hu (UW; Engineering) | TBD | Chen |
Dec 12 | Thomas Fai (Brandeis) | TBD | Rycroft |
[Dates marked with an asterisk are close to weekends with a home game for the UW Badgers football team. Hotel availability around these dates is often limited if booked on short notice.]
Abstract
Zichao (Wendy) Di (Argonne National Laboratory)
Title: Multimodal Inverse Problems and Multilevel Optimization for X-ray Imaging Science
X-ray imaging experiments generate vast datasets that are often incomplete or ill-posed when considered in isolation. One way forward is multimodal data analysis, where complementary measurement modalities are fused to reduce ambiguity and improve reconstructions. A key question, both mathematically and practically, is how to identify which modalities to combine and how best to integrate them within an inverse problem framework.
A second line of work focuses on the computational challenge: even for single-modality inverse problems, the resulting optimization problems are large-scale, nonlinear, and nonconvex. Here, I will discuss multilevel optimization and stochastic sampling strategies that accelerate convergence by exploiting hierarchical structure in both parameter and data spaces.
Although developed separately, these two directions point toward a common goal: building scalable, optimization-based frameworks that make the best use of diverse data to enable new discoveries in X-ray imaging science.Archived semesters
- Spring 2025
- Fall 2024
- Spring 2024
- Fall 2023
- Spring 2023
- Fall 2022
- Spring 2022
- Fall 2021
- Spring 2021
- Fall 2020
- Spring 2020
- Fall 2019
- Spring 2019
- Fall 2018
- Spring 2018
- Fall 2017
- Spring 2017
- Fall 2016
- Spring 2016
- Fall 2015
- Spring 2015
- Fall 2014
- Spring 2014
- Fall 2013
- Spring 2013
- Fall 2012
- Spring 2012
- Fall 2011
- Spring 2011
- Fall 2010
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