# Events for 02/22/2023 from all calendars

## I and T Committee Meeting

**Time: ** 4:00PM - 5:00PM

**Location: ** Bloc 117

## Topology Seminar

**Time: ** 4:00PM - 5:00PM

**Location: ** BLOC 628

**Speaker: **Ruobing Zhang, Princeton University

**Title: ***(Joint with Noncommutative Geometry Seminar) Metric geometry of Einstein 4-manifolds with special holonomy *

**Abstract: ** Studying the geometry of Einstein spaces and their generalizations is a major theme in current areas of differential geometry. This talk will introduce major developments in the metric geometry and global analysis of Einstein 4-manifolds. Recently geometric studies have culminated in a complete understanding of Einstein 4-manifolds with special holonomy.
Among the tremendous progress in this area, an essential chapter is to understand how Einstein moduli spaces can be compactified and how Einstein metrics can degenerate, especially when volume collapse occurs. Understanding collapsing geometry is much more challenging than studying the non-collapsing case so that little progress was made during the past three decades. I will particularly summarize recent breakthrough in this direction on the accurate characterization of singularity formation and the complete classification of degeneration limits on all scales.

## Noncommutative Geometry Seminar

**Time: ** 4:00PM - 5:00PM

**Location: ** BLOC 628

**Speaker: **Ruobing Zhang, Princeton University

**Title: ***(Joint with Topology Seminar) Metric geometry of Einstein 4-manifolds with special holonomy*

**Abstract: **Studying the geometry of Einstein spaces and their generalizations is a major theme in current areas of differential geometry. This talk will introduce major developments in the metric geometry and global analysis of Einstein 4-manifolds. Recently geometric studies have culminated in a complete understanding of Einstein 4-manifolds with special holonomy.

Among the tremendous progress in this area, an essential chapter is to understand how Einstein moduli spaces can be compactified and how Einstein metrics can degenerate, especially when volume collapse occurs. Understanding collapsing geometry is much more challenging than studying the non-collapsing case so that little progress was made during the past three decades. I will particularly summarize recent breakthrough in this direction on the accurate characterization of singularity formation and the complete classification of degeneration limits on all scales.

## AMUSE

**Time: ** 6:00PM - 7:00PM

**Location: ** BLOC 306

**Speaker: **Stephan Wojtowytsch, Texas A&M University

**Title: ***Neural networks and how to train them*

**Abstract: **The most time-consuming part of deep learning is the training of neural networks. We give a gentle introduction to data science, machine learning and deep learning. Our focus will be on training algorithms modeled on a hiker lost in the fog (gradient descent) and a heavy ball rolling down a mountainside (gradient descent with momentum) and their advantages.