Department of Mathematics, Applied Mathematics and Statistics

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The Department of Mathematics, Applied Mathematics and Statistics at Case Western Reserve University is an active center for mathematical research. Faculty members conduct research in algebra, analysis, applied mathematics, convexity, dynamical systems, geometry, imaging, inverse problems, life sciences applications, mathematical biology, modeling, numerical analysis, probability, scientific computing, stochastic systems and other areas.

The department offers a variety of programs leading to both undergraduate and graduate degrees in traditional and applied mathematics, and statistics. Undergraduate degrees are Bachelor of Arts or Bachelor of Science in mathematics, Bachelor of Science in applied mathematics, and Bachelor of Arts or Bachelor of Science in statistics. Graduate degrees are Master of Science and Doctor of Philosophy. The Integrated BS/MS program allows a student to earn a Bachelor of Science in either mathematics or applied mathematics and a master’s degree from the mathematics department or another department in five years. The department, in cooperation with the college’s teacher licensure program and John Carroll University, offers a program for individuals interested in pre-college teaching. Together with the Department of Physics, it offers a specialized joint Bachelor of Science in Mathematics and Physics.

 

Analysis and Probability Seminar- April 11, 2017

Date posted: March 27th, 2017

Tuesday, April 11, 2017 (3:00 p.m. in Yost 306)
Title: Random polytopes: An introduction and recent developments
Speaker: Julian Grote (PhD Student, University of Bochum and Case Western Reserve University)
Abstract: Random polytopes are among the most classical and popular models considered in stochastic geometry, and their study has become a rapidly developing branch of mathematics at the borderline between geometry and probability. …Read more.

Colloquium-March 31, 2017

Date posted: March 23rd, 2017

Friday, March 31, 2017 (3:15 p.m. in Yost 306)
Title: Solution uncertainty quantification for differential equations
Speaker: Oksana Chkrebtii (Assistant Professor, The Ohio State University)
Abstract: When models are defined implicitly by systems of differential equations without a closed form solution, small local errors in finite-dimensional solution approximations can propagate into large deviations from the true underlying state trajectory. …Read more.

Page last modified: March 23, 2017