Seminars feedhttps://www.math.umanitoba.ca/seminars/en-usTue, 19 Feb 2019 21:39:30 +0000- Dinamo Djounvouna - TBAhttps://www.math.umanitoba.ca/seminars/2019/2/28/dinamo-djounvouna/Graduate Student seminar:<br>
Dinamo Djounvouna (Department of Mathematics, University of Manitoba)<br>
<i>TBA</i><br>
Thursday, February 28, 2019 at 14:30<br>
115 Armes<br>
<br>
Thu, 07 Feb 2019 21:51:34 +0000https://www.math.umanitoba.ca/seminars/2019/2/28/dinamo-djounvouna/
- Gurjyot Kaur - TBAhttps://www.math.umanitoba.ca/seminars/2019/2/28/gurjyot-kaur/Graduate Student seminar:<br>
Gurjyot Kaur (Department of Mathematics, University of Manitoba)<br>
<i>TBA</i><br>
Thursday, February 28, 2019 at 15:00<br>
115 Armes<br>
<br>
Thu, 07 Feb 2019 21:51:52 +0000https://www.math.umanitoba.ca/seminars/2019/2/28/gurjyot-kaur/
- Dave Morris - Quasi-isometric bounded generationhttps://www.math.umanitoba.ca/seminars/2019/3/1/dave-morris/Colloquium talk:<br>
Dave Morris (University of Lethbridge)<br>
<i>Quasi-isometric bounded generation</i><br>
Friday, March 1, 2019 at 14:30<br>
111 Armes<br>
<br>
<p>A subset \(X\) "boundedly generates" a group \(G\) if every element of \(G\) is the product of a bounded number of elements of \(X\). This is a very powerful notion in abstract group theory, but geometric group theorists (and others) may also need a good bound on the sizes of the elements of \(X\) that are used. (We do not want to have to use large elements of \(X\) to represent a small element of \(G\).) Twenty-five years ago, Lubotzky, Mozes, and Raghunathan proved an excellent result of this type for the case where \(G\) is the group \(SL(n,\mathbb{Z})\) of \(n\times n\) matrices with integer entries and determinant one, and \(X\) consists of the elements of the natural copies of \(SL(2,\mathbb{Z})\) in \(G\). We will explain the proof of this result, and discuss a recent generalization to other arithmetic groups.</p>
Sun, 10 Feb 2019 23:52:08 +0000https://www.math.umanitoba.ca/seminars/2019/3/1/dave-morris/
- Rob Craigen - Orthogonal matrices with zero diagonalhttps://www.math.umanitoba.ca/seminars/2019/3/1/rob-craigen/Combinatorics seminar:<br>
Rob Craigen (Department of Mathematics, University of Manitoba)<br>
<i>Orthogonal matrices with zero diagonal</i><br>
Friday, March 1, 2019 at 15:30<br>
418 Machray Hall<br>
<br>
<p>TBA</p>
Sat, 02 Feb 2019 20:41:16 +0000https://www.math.umanitoba.ca/seminars/2019/3/1/rob-craigen/
- Deokro Lee - TBAhttps://www.math.umanitoba.ca/seminars/2019/3/7/deokro-lee/Graduate Student seminar:<br>
Deokro Lee (Department of Mathematics, University of Manitoba)<br>
<i>TBA</i><br>
Thursday, March 7, 2019 at 14:30<br>
115 Armes<br>
<br>
Thu, 07 Feb 2019 21:52:11 +0000https://www.math.umanitoba.ca/seminars/2019/3/7/deokro-lee/
- Yu Li - TBAhttps://www.math.umanitoba.ca/seminars/2019/3/7/yu-li/Graduate Student seminar:<br>
Yu Li (Department of Mathematics, University of Manitoba)<br>
<i>TBA</i><br>
Thursday, March 7, 2019 at 15:00<br>
115 Armes<br>
<br>
Thu, 07 Feb 2019 21:52:30 +0000https://www.math.umanitoba.ca/seminars/2019/3/7/yu-li/
- Morgan Craig - Optimal combination immunotherapy/oncolytic virotherapy determined through in silico clinical trials improves late stage melanoma patient outcomeshttps://www.math.umanitoba.ca/seminars/2019/3/8/morgan-craig/Colloquium talk:<br>
Morgan Craig (UniversitÃ© de MontrÃ©al)<br>
<i>Optimal combination immunotherapy/oncolytic virotherapy determined through in silico clinical trials improves late stage melanoma patient outcomes</i><br>
Friday, March 8, 2019 at 14:30<br>
111 Armes<br>
<br>
<p>Modern cancer treatments increasingly incorporate a broad class of biological therapies known as immunotherapies that seek to activate the immune system against cancer cells in a generalized or targeted way. For example, one general approach is the exogenous administration of certain small proteins known as cytokines to stimulate hematopoietic and immune cell production and recruitment. An older idea is to use viruses or bacteria to trigger a targeted anti-cancer immune reaction. Contemporary oncolytic virotherapy uses genetically modified viruses that preferentially attack and infect cancer cells, forcing infected cells to undergo lysis and release tumour specific antigens that signal the immune system to mount a response. It is natural to expect that immunotherapy and oncolytic virotherapy act synergistically against tumour cells, but proposed combination treatments must be shown to be both effective and non-toxic in clinical trials before they can be used in a clinical setting. However, running trials for all possible (dose,time)-pairs to determine efficient and safe scheduling is both time and cost prohibitive. As a consequence, determining the ideal regimen of immuno-/oncolytic virotherapy remains an open problem.</p>
<p>Here I will discuss our recent work using a quantitative approach to schedule and optimize combination granulocyte-macrophage colony-stimulating factor and T-VEC (the first FDA approved oncolytic virus) therapy for patients with late stage melanoma. By running an in silico clinical trial, we identified optimized treatment schedules that significantly improved 5-year survival while reducing the overall drug burden to patients. Our results highlight the potency of rational regimen prediction using a computational biology approach.</p>
Tue, 19 Feb 2019 21:39:30 +0000https://www.math.umanitoba.ca/seminars/2019/3/8/morgan-craig/
- Suraj Srinivasan - TBAhttps://www.math.umanitoba.ca/seminars/2019/3/14/suraj-srinivasan/Graduate Student seminar:<br>
Suraj Srinivasan (Department of Mathematics, University of Manitoba)<br>
<i>TBA</i><br>
Thursday, March 14, 2019 at 14:30<br>
115 Armes<br>
<br>
Thu, 07 Feb 2019 21:52:45 +0000https://www.math.umanitoba.ca/seminars/2019/3/14/suraj-srinivasan/
- Ruoxin Zhao - TBAhttps://www.math.umanitoba.ca/seminars/2019/3/14/ruoxin-zhao/Graduate Student seminar:<br>
Ruoxin Zhao (Department of Mathematics, University of Manitoba)<br>
<i>TBA</i><br>
Thursday, March 14, 2019 at 15:00<br>
115 Armes<br>
<br>
Thu, 07 Feb 2019 21:53:00 +0000https://www.math.umanitoba.ca/seminars/2019/3/14/ruoxin-zhao/
- Ilse C.F. Ipsen - An Introduction to Randomized Algorithms for Matrix Computationshttps://www.math.umanitoba.ca/seminars/2019/3/14/ilse-cf-ipsen/PIMS lecture:<br>
Ilse C.F. Ipsen (North Carolina State University)<br>
<i>An Introduction to Randomized Algorithms for Matrix Computations</i><br>
Thursday, March 14, 2019 at 16:00<br>
Robert Schultz Lecture Theatre<br>
<br>
<p>The emergence of massive data sets, over the past twenty or so years, has led to the development of Randomized Numerical Linear Algebra. Fast and accurate randomized matrix algorithms are being designed for applications like machine learning, population genomics, astronomy, nuclear engineering, and optimal experimental design.</p>
<p>We give a flavour of randomized algorithms for the solution of least squares/regression problems. Along the way, we illustrate important concepts from numerical analysis (conditioning and pre-conditioning), probability (concentration inequalities), and statistics (sampling and leverage scores).</p>
<p>See the <a class="reference external" href="/media/seminars/2018/11/Ilse_C.F._Ipsen_2018_gen.pdf">poster</a> for this talk.</p>
Tue, 27 Nov 2018 21:54:38 +0000https://www.math.umanitoba.ca/seminars/2019/3/14/ilse-cf-ipsen/