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Optimal transport and mean-field control problems are widely used in many practical problems in engineering, physics, financial mathematics, and machine learning. The elegant theory of transporting measures has deep connections with analysis and probability, while it also relates to the mean-field control, large deviations, and generative models which explore the macroscopic behaviors of a large number of agents/samples. The associated computational methods for optimal transport, mean-field control and related applications in data science are developed at dramatic speed, which also in turn stimulate theoretical foundations. This workshop brings junior and senior researchers together to exchange fundamental mathematical ideas and recent developments in the field.
Organizers: Yuan Gao and Rongjie Lai, Purdue University
This workshop is supported by Center for Computational and Applied Mathematics at Purdue University.
Please register before August 1, 2024 if you will be attending. There is no charge for registration, but registration is required for an accurate lunch count.
We will also have a poster session or lightning talks for students or junior researchers who are interested in sharing their work. Please submit your title, abstract and the presentation format HERE before July 19, 2024.
Confirmed Speakers
Confirmed Speakers
University of Maryland
University of California, Irvine
Purdue University
University of Chicago
Duke University
University of Minnesota
University of Wisconsin–Madison
University of California, Los Angeles
University of Wisconsin–Madison
University of Minnesota
Duke University
Georgia Institute of Technology
The Venue: All the presentations will be in WALC B091, 340 Centennial Mall Dr., West Lafayette, IN
The Venue: All the presentations will be in WALC B091, 340 Centennial Mall Dr., West Lafayette, IN
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