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Ki-Net–CNA Workshop:
Groups and interactions in data, networks and biology

Carnegie Mellon University, Department of Mathematical Sciences

May 27–29, 2015

Download poster: PDF (500 KB), JPEG (663 KB)

Individuals and agents in many systems spontaneously organize to form structures such as flocks, swarms, and clusters. Investigating the principles that govern the formation and behavior of large groups in natural systems requires understanding the structure of clusters, their connectivity, how their identities develop, and how information propagates. Similar goals are also important in statistics and machine learning for understanding massive clouds of high-dimensional data, where one relies on properties of graphs encoding data similarity. Likewise connectivity and structure play an important role in studies of network dynamics.


Lectures are in Wean Hall 7218.



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

Registration and application for aid are at the Ki-Net Conference site


Robert Pego, Carnegie Mellon University,
Dejan Slepčev, Carnegie Mellon University,
Eitan Tadmor, University of Maryland,

Contact Information:

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

Telephone: (412) 268-2545
Fax: (412) 268-6380

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

Image courtesy of Jeub, Balachandran, Porter, Mucha, and Mahoney.

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