# PACM Colloquium

## PACM Colloquium: Stefan Steinerberger, Yale University

# Orthogonality and Oscillation, Sines and Cosines, Sturm and Liouville, Wasserstein and Optimal Transport

## PACM Colloquium: Cynthia Vinzant, North Carolina State University

# Log-concave polynomials, matroids, and expanders

## PACM Colloquium: Percy Deift, New York University, Courant Institute of Mathematical Sciences

# Universality in numerical computation

The speaker will discuss a variety of universality results in numerical computation with random data. It turns out that for many standard algorithms the fluctuations in the time it takes to achieve a given accuracy are universal, independent of the statistical assumptions on the data. Some of the results presented are numerical, and some are analytical.

This is joint work with a number of authors over the last 6 or 7 years, but mostly with Tom Trogdon.

## PACM Colloquium: Charles Gammie, University of Illinois, Urbana-Champaign

# Modeling the Black Hole Image

## PACM Colloquium: Alexander Barvinok, University of Michigan, Ann Arbor

# Computational complexity of approximation and complex zeros

## PACM Colloquium: Yuxin Chen, Princeton University

# Bridging convex and nonconvex optimization in noisy matrix completion: Stability and uncertainty quantification

## PACM Colloquium: Subhash Khot, Courant Institute of Mathematical Sciences - New York University

# Hardness of Approximation

Hardness of Approximation studies the phenomenon that for several fundamental NP-hard problems, even computing approximate solutions to them remains an NP-hard problem. The talk will give an overview of this study along with its connections to algorithms, analysis, and geometry.

## PACM Colloquium: Oded Regev, Courant Institute of Mathematical Sciences, New York University

# Lattice-Based Cryptography and the Learning with Errors Problem

## PACM Colloquium: Avi Wigderson, Institute for Advanced Study

**PLEASE NOTE UPDATED LOCATION: JADWIN HALL, ROOM A10**

# Optimization, Complexity and Math (through the lens of one problem and one algorithm)

I will first introduce and motivate the main characters in this plot: