Future students

Title: On the Strong Nine Dragon Tree Conjecture

Abstract:

Nash-Williams forest covering theorem says that a graph decomposes into $k$ forests if and only if it has fractional arboricity at most $k$. In 2012 Mickeal Montassier, Patrice Ossona de Mendez, Andre Raspaud, and Xuding Zhu  proposed a significant strengthening of Nash-Williams Theorem, called the Strong Nine Dragon Tree Conjecture.

Title: Covers of Complete Bipartite Graphs

Abstract:

I will discuss antipodal distance-regular covers of complete bipartite graphs $K_{n,n}$. The index of such a cover is at most $n$.

Title: The Capacitated Survivable Network Design Problem

Abstract:

The Capacitated Survivable Network Design Problem or Cap-SNDP models a network reinforcement problem where the network designer wants to find a minimum-cost set of reinforcements that protects the network from an adversary.

Title: Electrical networks, random spanning trees, and matroids

Abstract:

This is a reprise of a survey talk I gave at the East Coast Combinatorics Conference in August 2019, and a variation of one I gave in the graphs and matroids seminar last year.

Title: Periodicity in Quantum Walks

Abstract:

Despite the title, quantum walks are, in general, not periodic. However they are, in general, periodic to any desired degree of accuracy.

Title: Beating 3/2 for Approximating TSP in the Half-Integral Case

Abstract:

In 2013, Schalekamp, Williamson, and van Zuylen conjectured that the integrality gap for the Subtour Polytope was attained on its half-integral vertices.

Title: Graph covers with two new eigenvalues

Abstract:

I am going to talk about graph covers. If $Y$ is a cyclic cover of $X$, it turns out that $Y$ has the same spectrum as $X$ plus (possibly) some new eigenvalues. 

Title: OutFn, M_gn and renormalized topological field theory

Abstract:

I will report on recent joint work with Karen Vogtmann on the Euler characteristic of Out(F_n) and the moduli space of graphs.

Title: How can we optimize nonsmooth objectives globally?

Abstract:

In machine learning objective functions that are only piecewise smooth and should be globally minimized abound. The standard method of dealing with them is to apply a stochastic gradient method disregarding the rare points of nonsmoothness and hoping for the best as far as global optimality of the computed solution is concerned.

Title: Biometric security: Design, implementation, and challenges

Abstract:

Biometric based cybersecurity technologies offer significant advantages in authentication, identification, and access control mechanisms.