# 2019 - 2020

# Calendrier / Calendar

# MONTRÉAL

**Date Heure/Time**: Le vendredi 19 juin 2020 - 16:00

**Lieu/Venue**: Zoom meeting : https://umontreal.zoom.us/j/94839201651?pwd=Nm52ZzUzWjdrNWhlMG04Rk1Cb0NZQT09

**Conférencier/Speaker**: Morgan Craig, Université de Montréal - Vidéoconference

**Titre/Title**: Quantitative approaches to understanding the immune response to SARS-CoV-2 infection

**Resume/Abstract**:

COVID-19 is typically characterized by a range of respiratory symptoms that, in severe cases, progress to acute respiratory distress syndrome (ARDS). These symptoms are also frequently accompanied by a range of inflammatory indications, particularly hyper-reactive and dysregulated inflammatory responses in the form of cytokine storms and severe immunopathology. Much remains to be uncovered about the mechanisms that lead to disparate outcomes in COVID-19. Here, quantitative approaches, especially mechanistic mathematical models, can be leveraged to improve our understanding of the immune response to SARS-CoV-2 infection. Building upon our prior work modelling the production of innate immune cell subsets and the viral dynamics of HIV and oncolytic viruses, we are developing a quantitative framework to interrogate open questions about the innate and adaptive immune reaction in COVID-19. In this talk, I will outline our recent work modelling SARS-CoV-2 viral dynamics and the ensuing immune response at both the tissue and systemic levels. A portion of this work is done as part of an international and multidisciplinary coalition working to establish a comprehensive tissue simulator (physicell.org/covid19 [1]), which I will also discuss in more detail.

**Date Heure/Time**: Le vendredi 2 octobre 2020 - 15:30

**Lieu/Venue**: Zoom: pour inscription / to register http://crm.umontreal.ca/colloque-sciences-mathematiques-quebec/#csmq

**Conférencier/Speaker**: Paul McNicholas, McMaster University- Vidéoconference

**Titre/Title**: Data Science, Classification, Clustering and Three-Way Data

**Resume/Abstract**:

Data science is discussed along with some historical perspective. Selected problems in classification are considered, either via specific datasets or general problem types. In each case, the problem is introduced before one or more potential solutions are discussed and applied. The problems discussed include data with outliers, longitudinal data, and three-way data. The proposed approaches are generally mixture model-based.

**Date Heure/Time**: Le vendredi 16 octobre 2020 - 15:00

**Lieu/Venue**: Zoom: pour inscription/ To register: http://crm.umontreal.ca/colloque-sciences-mathematiques-quebec/#csmq

**Conférencier/Speaker**: Nicolas Bergeron, École normale supérieure, France

**Titre/Title**: (Aisenstadt Lecture) Trigonometric functions and modular symbols

**Resume/Abstract**:

In his fantastic book « Elliptic functions according to Eisenstein and Kronecker, » Weil writes: « As Eisenstein shows, his method for constructing elliptic functions applies beautifully to the simpler case of the trigonometric functions. Moreover, this case provides […] the simplest proofs for a series of results, originally discovered by Euler. » The results Weil alludes to are relations between product of trigonometric functions. I will first explain how these relations are quite surprisingly governed by relations between modular symbols (whose elementary theory I will sketch). I will then show how this story fits into a wider picture that relates the topological world of group homology of some linear groups to the algebraic world of trigonometric and elliptic functions. To conclude I will briefly describe a number theoretical application. This is based on a work-in-progress with Pierre Charollois, Luis Garcia and Akshay Venkatesh.

**Date Heure/Time**: Le vendredi 13 novembre 2020 - 15:30

**Lieu/Venue**: Zoom: pour inscription/ To register: http://crm.umontreal.ca/colloque-sciences-mathematiques-quebec/#csmq

**Conférencier/Speaker**: Tamara Broderick, Massachusetts Institute of Technology, USA

**Titre/Title**: Approximate Cross-Validation for Large Data and High Dimensions

**Resume/Abstract**:

The error or variability of statistical and machine learning algorithms is often assessed by repeatedly re-fitting a model with different weighted versions of the observed data. The ubiquitous tools of cross-validation (CV) and the bootstrap are examples of this technique. These methods are powerful in large part due to their model agnosticism but can be slow to run on modern, large data sets due to the need to repeatedly re-fit the model. We use a linear approximation to the dependence of the fitting procedure on the weights, producing results that can be faster than repeated re-fitting by orders of magnitude. This linear approximation is sometimes known as the "infinitesimal jackknife" (IJ) in the statistics literature, where it has mostly been used as a theoretical tool to prove asymptotic results. We provide explicit finite-sample error bounds for the infinitesimal jackknife in terms of a small number of simple, verifiable assumptions. Without further modification, though, we note that the IJ deteriorates in accuracy in high dimensions and incurs a running time roughly cubic in dimension. We additionally show, then, how dimensionality reduction can be used to successfully run the IJ in high dimensions when data is sparse or low rank. Simulated and real-data experiments support our theory.

**Date Heure/Time**: Le vendredi 20 novembre 2020 - 15:00

**Lieu/Venue**: Zoom: pour inscription/ To register: http://crm.umontreal.ca/colloque-sciences-mathematiques-quebec/#csmq

**Conférencier/Speaker**: Wieslawa Niziol, Sorbonne Université

**Titre/Title**: Hodge Theory of p-adic varieties

**Resume/Abstract**:

p-adic Hodge Theory is one of the most powerful tools in modern Arithmetic Geometry. In this talk, I will review p-adic Hodge Theory of algebraic varieties, present current developments in p-adic Hodge Theory of analytic varieties, and discuss some of its applications to problems in Number Theory.

**Date Heure/Time**: Le vendredi 27 novembre 2020 - 15:00

**Lieu/Venue**: Zoom: pour inscription/ To register: http://crm.umontreal.ca/colloque-sciences-mathematiques-quebec/#csmq

**Conférencier/Speaker**: Frances Kirwan, University of Oxford

**Titre/Title**: Moduli of unstable objects in algebraic geometry

**Resume/Abstract**:

Moduli spaces arise naturally in classification problems in geometry. The study of the moduli spaces of nonsingular complex projective curves (or equivalently of compact Riemann surfaces) goes back to Riemann himself in the nineteenth century. The construction of the moduli spaces of stable curves of fixed genus is one of the classical applications of Mumford's geometric invariant theory (GIT), developed in the 1960s; many other moduli spaces of 'stable' objects can be constructed using GIT and in other ways. A projective curve is stable if it has only very mild singularities (nodes) and its automorphism group is finite; similarly in other contexts stable objects are usually better behaved than unstable ones. The aim of this talk is to explain how recent methods from a version of GIT for non-reductive group actions can help us to classify singular curves in such a way that we can construct moduli spaces of unstable curves (of fixed type). More generally our aim is to use suitable 'stability conditions' to stratify other moduli stacks into locally closed strata with coarse moduli spaces. The talk is based on joint work with Gergely Berczi, Vicky Hoskins and Joshua Jackson.