Speakers & Sessions

Plenary Speakers

Our plenary speakers will include:

• Michael Bronstein (Oxford)
• Dan Spielman (Yale)
• Soledad Villar (Johns Hopkins)
• Laura Balzano (University of Michigan)
• Samory Kpotufe (Columbia University)
• Mark Iwen (Michigan State University)
• Holger Rauhut (Aachen University)
• Coralia Cartis (Oxford)
• Rebecca Willett (University of Chicago)

Special Sessions

Our special sessions will bring together domain experts to present on topics including Manifold Learning from Data, Graph Signal Processing, Topological Data Analysis, and Sampling Theory for Neural Activity Data, among others. Each session will feature 3-4 speakers, and run for 2 hours. The following is a preliminary listing of session topics, organizers, and speakers.

Manifold Learning from Data

Hosted by Kevin Moon (Utah State).

Signal and Image Processing

Hosted by Longxiu Huang (Michigan State University).

Methods for Low Rank Matrices and Tensors

Hosted by Dominik Stöger (KU Eichstätt-Ingolstadt) and Anna Ma (University of California Irvine),

Data Geometry and Optimization

Hosted by Rishi Sonthalia (UCLA) and Michael Perlmutter (UCLA).

Randomized Algorithms for Complex Data

Hosted by Elizaveta Rebrova (Princeton).

Machine Learning and Signal Processing on Graphs and Manifolds

Hosted by Michael Perlmutter (UCLA).

Sampling Theory in Neuroscience

Hosted by Bastian Rieck (Helmholtz Munich, Germany) and Guillaume Lajoie (University of Montreal).

Quantization in Signal Processing and Data Science

Hosted by Johannes Maly (LMU Munich).