What is our goal?

       Data is crucial in inverse problems to infer unknown parameters in a PDE model. Traditional inverse problems deploy PDE theory to guide data collection. Big achievement has been made in data science over the past few years, and it is the prime time to reevaluate if, and how data science techniques can feed inverse PDE theory.

       The workshop brings together leading experts from diverse backgrounds to deliver presentations over a span of three days on topics related to interplay between data science and PDE models from the inverse problem perspective. The goal is to create a platform for researchers across different fields to exchange perspectives, discover new research directions and foster collaborative endeavors.

When and where?

       This workshop will be held at University of Wisconsin, scheduled from August 19th to 21st, 2024.

Acknowledgement

      We thank NSF-DMS 1750488 and UW-Madison math department for the generous support.