Welcome to the Math Department

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Spring 2017 add/drop begins November 26, 2016. Students who are unable to request or add a Math class should submit the Spring 2017 Math Course Survey.

Advising Information - New Courses (April 2016 update)

Sign ups for Credit by Exam, End of Fall 2016
MONDAY, December 5, 10:00 AM - 11:30 AM an 1:30 PM - 3:00 PM
TUESDAY, December 6, 10:00 AM - 11:30 AM an 1:30 PM - 3:00 PM
WEDNESDAY, December 7, 10:00 AM - 11:30 AM an 1:30 PM - 3:00 PM

Force-Add information for Spring 2017

New Change of Major Policy. Next Open Period: December 19,2016 - January 27, 2017

The Putnam Mathematical Competition with be held 10:00am - 1:00pm and 3:00pm - 6:00pm on Saturday, December 3.

Computational Mathematics Search

Stochastic Analysis Search

Caldwell Postdoc Search

Data and Decision Sciences Collegiate Faculty Search


Featured Research

Serkan Gugercin - Direct numerical simulation of dynamical systems has been one of the few available means when goals include accurate prediction or control of complex physical phenomena of scientific interest or industrial value. However, the ever-increasing need for improved accuracy leads to very large-scale and complex dynamical systems. Simulations in such large-scale settings can be overwhelming and make unmanageably large demands on computational resources, which is the main motivation for model reduction. The goal is to produce a simpler reduced-order model approximating the original one as accurately as possible. The resulting reduced model can then be used as an efficient surrogate to the original, to replace it in a larger simulation or to develop a simpler and faster controller suitable for real time applications. Krylov-based interpolation methods have emerged as the promising candidates for model reduction in realistic large-scale settings. Dr. Gugercin's research focuses on developing optimal, robust and systematic Krylov-based projection methods for efficient construction of high fidelity and optimal reduced-order models in realistic settings with millions of degrees of freedom.

The figure shows the rapid convergence to the optimal reduced model for three different initializations, in a recent method introduced in the paper " An iterative SVD-Krylov based algorithm for model reduction of large-scale dynamical systems", by Gugercin.

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