NIU Department of Mathematical Sciences

Upcoming Colloquia and Seminars

January 20-23, 2015


Algebra Seminar:   Wednesday, Feb. 18 , 4:15-5:15 p.m. in DU 378
Speaker: Mike Geline
Topic: Introduction to Representation Theory and Brauer's Induction Theorem
Abstract: This seminar series will be aimed at graduate students, and will constitute an informal (but hopefully informative) course on representations of finite dimensional algebras with an emphasis on representations of finite groups. We will begin with a (hopefully brief) review of semisimplicity and the distinction between irreducible (versus absolutely irreducible) modules. We'll define characters early as well. Then we'll define the ubiquitous concept of induced representations (and induced characters) with the aim of proving a fascinating and powerful result known as Brauer's induction theorem (or if time permits one of its stronger variations). Brauer's theorem began life as a conjecture of Emil Artin, who anticipated an application to L-functions attached to representations of Galois groups. But it turned out to have many applications to group theory as well, and also quite surprisingly to certain questions in algebraic topology.

Complex Analysis Seminar:   Tuesday, Feb. 17, 11:00-11:50 p.m. in DuSable 464
Speaker: Weihong Yao, Shanghai Jiao Tong Univ.
Topic: The distribution of normalized zero-sets of random meromorphic functions

Applied Math Seminar:   Tuesday, Feb. 17, 11:30-12:20 p.m. in Watson 110
Speaker: Nathan Krislock
Topic: Semidefinite Optimization and Combinatorial Optimization
Abstract: During the last two decades, semidefinite optimization has grown into a significant field of research with applications in many diverse areas such as graph theory, distance geometry, combinatorial optimization, low-rank matrix completion, and polynomial optimization. In combinatorial optimization, semidefinite optimization is used to compute high-quality bounds to many difficult (in fact, NP-hard) problems, such as Max-Cut and maximum k-cluster. This has led to the development of state-of-the-art branch-and-bound methods for solving such problems to optimality.