College of Arts and Sciences

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.

Date posted: October 5th, 2015

Monday, October 12, 2015 (3:30 p.m. in Yost 102)

**Title:** Elastic Rods

**Speaker:** David Singer (Professor and Interim Chair, Mathematics, Applied Mathematics, & Statistics, Case Western Reserve University)

**Abstract:** We generalize the notion of Euler elastic curve to Kirchhoff elastic rods. …Read more.

Date posted: October 2nd, 2015

Tuesday, October 13, 2015 (3:00 p.m. in Yost 306)

**Title:** K-convexity (Part II)

**Speaker:** Stanislaw Szarek (Professor, Department of Mathematics, Applied Mathematics, & Statistics, Case Western Reserve University)

**Abstract:** Let (gi) be a sequence of independent standard Gaussian random variables on some probability space, and let P be the orthogonal projection on the subspace generated by the gi‘s. …Read more.