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CNA/Ki-Net Workshop:
Dynamics and Geometry from High Dimensional Data

Carnegie Mellon University, Department of Mathematical Sciences

March 14–16, 2017

Download poster: PDF (814 KB), JPEG (981 KB)

This workshop focuses on extracting structure from high-dimensional datasets. In particular, it will address how to reliably uncover the laws that govern the dynamics being investigated and how to discover and describe the geometry present in sets of data. The workshop will bring together researchers from a variety of fields, including statistical machine learning, applied analysis, dynamical systems, probability and stochastic processes, and computational mathematics for exchange of ideas.

Confirmed Speakers:

A limited amount of funds is available to support researchers in the early stages of their career who want to attend the program, especially for graduate students and post-doctoral fellows.
Deadline for applications for support is January 31.

Organizers:

Nicolás García-Trillos Brown University
Mauro Maggioni Johns Hopkins University
Hayden Schaeffer Carnegie Mellon University
Dejan Slepčev Carnegie Mellon University
Matthew Thorpe Carnegie Mellon University

Contact Information:

Center for Nonlinear Analysis
Carnegie Mellon University
Department of Mathematical Sciences
Pittsburgh, PA 15213

Telephone: (412) 268-2545
Fax: (412) 268-6380
E-mail: cn0s@math.cmu.edu

Funding provided by the National Science Foundation through the KI-net Grant and the Center for Nonlinear Analysis, CMU.

Ki-Net Center for Nonlinear Analysis CSCAMM University of Maryland Carnegie Mellon University NSF

Background image: Trail formation based on directed pheromone deposition, courtesy Emmanuel Boissard, Pierre Degond and Sebastien Motsch