Welcome to CAMS
The Center for Applied Mathematical Sciences is an organized research unit
based in the Department of Mathematics
at USC.
The purpose of CAMS is to foster research and graduate education in
Mathematics in a broad sense and in an interdisciplinary mode. One goal
of the center's participants is to facilitate and encourage the development of
applicable mathematics and its utilization in problems in engineering and the
sciences.
The mission of the Center is threefold.
 To maintain USC's position as an internationallyrecognized center in
several important and well defined areas of mathematics and its applications
 To be a muchneeded interface between the Department of Mathematics and
other USC departments and institutions outside USC.
 To serve as a catalyst in the development of stateoftheart
activities in applicable mathematics at USC.
CAMS Prize Winners
Winners of the CAMS Graduate Student Prize for Excellence in Research with a Substantial Mathematical Component.
Anand Kumar Narayanan 
Ibrahim Ekren 
Sushmita Allam 
WanJung Kuo 
Yang Huang 





Computer Science 
Mathematics 
Biomedical Engineering 
Physics 
Mathematics 





Upcoming Colloquium
3:30 PMKAP 414

Tristan Buckmaster
Courant Institute
Monday, October 27

Onsager's Conjecture
In 1949, Lars Onsager in his famous note on statistical hydrodynamics conjectured that weak solutions to the Euler equation belonging to Hölder spaces with Hölder exponent greater than 1/3 conserve energy; conversely, he conjectured the existence of solutions belonging to any Hölder space with exponent less than 1/3 which dissipate energy. The first part of this conjecture has since been confirmed (cf. Eyink 1994, Constantin, E and...


Upcoming Colloquium
3:30 PMKAP 414

Michael Wolf
University of Zurich
Monday, November 03

Spectrum Estimation: A Unified Framework for Covariance Matrix Estimation and PCA in Large Dimensions
Covariance matrix estimation and principal component analysis (PCA) are two cornerstones of multivariate analysis. Classic textbook solutions perform poorly when the dimension of the data is of a magnitude similar to the sample size, or even larger. In such settings, there is a common remedy for both statistical problems: nonlinear shrinkage of the eigenvalues of the sample covariance matrix. The optimal nonlinear shrinkage formula...


Upcoming Colloquium
3:30 PMKAP 414

David Levermore
University of Maryland
Monday, November 10

Scattering Theory for the Boltzmann Equation and the Arrow of Time (joint work with Claude Bardos, Irene Gamba, and Francois Golse)
We develop a scattering theory for a class of eternal solutions of the Boltzmann equation posed over all space. In three spatial dimensions each of these solutions has thirteen conserved quantities. The Boltzmann entropy has a unique minimizer with the same thirteen conserved values. This minimizer is a local Maxwellian that is also a global solution of the Boltzmann equation  a socalled global Maxwellian. We show that each...


Upcoming Colloquium
3:30 PMKAP 414

Inwon Kim
UCLA
Monday, November 17

To be Announced



