Atlantic Graph Theory Seminar: Sandra Kingan (Brooklyn College and Graduate Center, CUNY)
2021-12-08 15:30 - 16:30 UTC | Zoom seminar
I will begin by giving a general overview of what it means to find monarchs for excluded minor classes of graphs and matroids. In a paper that appeared in 2018, I used the Strong Splitter Theorem to give a short proof of Oxley’s result that the class of binary matroids with no 4-wheel minor consists of a few small matroids and an infinite family of maximal 3-connected rank r matroids known as the binary spikes. Such a family is called a monarch for the excluded minor class. This proof essentially comes down to finding the monarchs for non-regular matroids with no minors isomorphic to a 9-element rank 4 matroid known as P9 or its dual P*9. In a paper that appeared this year (Australasian Journal of Combinatorics, 79(3), 302–326), I was able to strengthen the result by characterizing the class of binary non-regular matroids with no minor isomorphic to just P*9. The only members of this class are the rank 3 and 4 binary projective geometries, a 16-element rank 5 matroid, and two monarchs: the rank r binary spikes with 2r+1 elements mentioned earlier and another infinite family with 4r−5 elements. As a consequence, a simple binary matroid of rank at least 6 with no P*9-minor has size at most r(r+1)/2 and this bound is attained by the rank r complete graph. This is one of few excluded minor classes for which the members are so precisely determined.

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AARMS Scientific Machine Learning Seminar: Peter Dueben (ECMWF)
2021-12-07 11:00 - 12:00 UTC | WebEx seminar
This talk provides an overview on the machine learning efforts at the European Centre for Medium-Range Weather Forecasts (ECMWF), and outlines how machine learning, and in particular deep learning, could help to improve weather predictions in the coming years. The talk will name challenges for the use of machine learning and suggest developments (research/software/hardware) that should enable the community of Earth system modelling to make quick progress.
Webex information:
Link: https://mun.webex.com/mun/j.php?MTID=m32a22bd61d05707cefe973ca5bf6ad69
Meeting no: 2631 545 3588
Password: [REDACTED]

Dalhousie-AARMS AAMP Seminar: Jesse Gell-Redman (University of Melbourne)
2021-12-03 16:00 - 17:00 (America/Halifax) | Zoom seminar
Title: A Fredholm approach to scattering
Abstract: We will give a friendly introduction to the scattering theory, specifically to the matrix for Schrodinger operators. We will then discuss how a new functional analytic approach to analysis of non-elliptic equations, due to Vasy, gives a conceptually attractive method for proving detailed regularity results for nonlinear scattering. This is joint work with several groups of authors including Andrew Hassell, Sean Gomes, Jacob Shapiro, and Junyong Zhang.
The Dalhousie-AARMS Analysis-Applied Math-Physics Seminar takes place on Fridays from 4 – 5 pm Atlantic Time over Zoom. If you would like to attend, please email the organizers for connection details.

Atlantic Graph Theory Seminar: James Preen (Cape Breton University)
2021-12-01 15:30 - 16:30 UTC | Zoom seminar
There are many results about triangles in graphs, but the property that every edge in a graph is in at least one triangle seems not to have been studied before. The 4-regular case was quickly solved collaboratively following an internet posting and then written about by one author in their blog, before being published in the Journal of Graph Theory in 2013.
However, the result that was originally wanted was a characterisation for 5-regular graphs, and that did not emerge as smoothly. With no solution published several years later, I started working on it and have submiited my paper resolving it in 2021. In this talk I will outline the background and the ideas used in the proof, which involves cliques, multiple edges and a generalisation of the the line graph construction.
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To view previous slides and talks, click here.

AARMS Scientific Machine Learning Seminar: Ben Adcock (Simon Fraser University)
2021-11-23 11:00 - 12:00 UTC | WebEx seminar
Title: Tackling the curse: polynomial and deep neural network methods for function approximation in high dimensions
Abstract: Many problems in computational science and engineering require the accurate approximation of a target function from data. This problem is rendered challenging by the high-dimensionality of the function, the expense of generating function samples, the presence of noise in the measurements, and the fact that the target function may take values in a function space. Developing techniques that tackle these challenges without succumbing to the famous “curse of dimensionality” has been a long-standing problem. In the first part of this talk I will give a brief survey of a decade’s worth of progress on high-dimensional function approximation via sparse polynomial expansions. I will show how the proper use of nonlinear approximation theory and compressed sensing techniques leads to algorithms for high-dimensional approximation which, unlike other approaches, possess provably near-optimal error bounds and moderate sample complexities. In particular, these techniques mitigate the curse of dimensionality to a substantial degree. The second part of the talk will be devoted to emerging approaches based on deep neural networks and deep learning. Such tools are beginning to garner substantial attention in the scientific computing community. Nonetheless, I will present evidence of a key gap between current theory and practice. I will then discuss recent results showing that there exist deep neural networks that match the performance of best-in-class schemes, and furthermore, these can indeed be trained through realizable procedures. This highlights the potential of deep neural networks, and sheds light on achieving robust, reliable and overall improved practical performance.
This talk is based on joint work with Anyi Bao, Simone Brugiapaglia, Juan M. Cardenas, Nick Dexter, Sebastian Moraga, Yi Sui and Clayton G. Webster.
Meeting link:
https://mun.webex.com/mun/j.php?MTID=m38cc6ce370de2b1c234e33feac5bb93a
Meeting number: 2630 760 7617
Password: [REDACTED]

Dalhousie-AARMS AAMP Seminar: Amanda Young (Technical University of Munich)
2021-11-19 16:00 - 17:00 (America/Halifax) | Zoom seminar
Title: A bulk gap in the presence of edge states for a HaldanepseudopotentialAbstract: In this talk, we discuss a recent result on a bulk gap for atruncated Haldane pseudopotential with maximal half filling, whichdescribes a strongly correlated system of spinless bosons in a cylindergeometry. For this Hamiltonian with either open or periodic boundaryconditions, we prove a spectral gap above the highly degenerateground-state space which is uniform in the volume and particle number.Our proofs rely on identifying invariant subspaces to which we applygap-estimate methods previously developed only for quantum spinHamiltonians. In the case of open boundary conditions, the lower boundon the spectral gap accurately reflects the presence of edge states,which do not persist into the bulk. Customizing the gap technique to theinvariant subspace, we avoid the edge states and establish a moreprecise estimate on the bulk gap in the case of periodic boundaryconditions. The same approach can also be applied to prove a bulk gapfor the analogously truncated 1/3-filled Haldane pseudopotential for thefractional quantum Hall effect. Based off joint work with S. Warzel.

The Dalhousie-AARMS Analysis-Applied Math-Physics Seminar takes place on Fridays from 4 – 5 pm Atlantic Time over Zoom. If you would like to attend, please email the organizers for connection details.

University of New Brunswick Data Challenge
2021-11-19 | University of New Brunswick (Fredericton Campus), Fredericton, New Brunswick, Canada
The Data Challenge will bring together three competitive events, the Open Data Visualization (6th annual), Data Analytics (2nd Edition), and Data Sprint (2nd Edition) on November 19, 2021 in a hybrid format – virtually & in-person! Take up the challenge and demonstrate the power of data, with the flexibility to take part remotely. Our previous edition saw 85 data-driven enthusiasts compete from across Canada in 30 teams. The event also saw 35 business experts, mentors, speakers & partners from diverse industries.
Participants and teams will have the chance to showcase their ability to tell a story-driven by data in three unique competitive formats. Teams can participate in all three competitive events. It is an ideal setting for citizens to get engaged, to meet leaders in academia, government, and private organizations, and to explore the world of data science.

Atlantic Graph Theory Seminar: Pavol Hell (SFU)
2021-11-17 15:30 - 16:30 UTC | Zoom seminar
I will discuss a few examples where considering loops leads to interesting insights, often allowing unifying existing results. These examples will include cops and robbers games, graph homomorphisms, variants of interval and chordal graphs,
and versions of domination.
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AARMS Scientific Machine Learning Seminar: Hamid Usefi (MUN)
2021-11-09 11:00 - 12:00 UTC | WebEx seminar
Multicollinearity, singular vectors, and dimensionality reduction for high-dimensional datasets
Single nucleotide polymorphisms (SNPs) as building blocks of our DNA, can determine the variations between people. It is believed that SNPs in genes that regulate DNA mismatch repair, cell cycle regulation, metabolism and immunity are associated with genetic susceptibility to cancer. So, SNPs are potential diagnostic and therapeutic biomarkers in many cancer types. This in part has prompted the rapid advancements in DNA sequencing which makes it possible both in terms of cost and time to genetically sequence a single suspect tissue. The number of SNPs in a disease dataset varies from tens of thousands to several million. So, one of the bottlenecks of working with these genome datasets is their large-scale size that makes it difficult to render the data for meaningful analysis. Furthermore, in most diseases, there are at most a couple of hundred SNPs associated with the disease. So, simply put we would be looking for a needle in a haystack.
Machine learning algorithms are gaining increasing attention and believe to have great potential in answering many questions in this respect. A common problem in machine learning and pattern recognition is the process of identifying the most relevant features, specifically in dealing with high-dimensional datasets in bioinformatics. In this talk, I will discuss some of our recent work on a new feature selection method, called Singular-Vectors Feature Selection (SVFS). Part of this work is joint with my recently graduated PhD student Majid Afshar. It is stemmed from identifying linearly dependent columns of a matrix A. This problem can also be viewed as multicollinearity and subset selection in statistical modelling and arises in many contexts, including regression, ecology, and machine learning.
Let D = [A | b] be a labeled dataset, where b is the class label and features (attributes or SNPs) are columns of matrix A; rows of A can be viewed as samples. We show with examples as well as a sketch of proof that the projector matrix P_A onto the null space of A can be used to partition the columns of A into clusters so that columns in a cluster correlate only with the columns in the same cluster. In the first step, SVFS uses the projector P_D to find the cluster that contains b. We reduce the size of A by discarding features in the other clusters as irrelevant features. In the next step, SVFS uses the P_A of reduced A to partition the remaining features into clusters and choose the most important features from each cluster. I will discuss the performance of SVFS on genomic datasets compared to the state-of-the-art feature selection methods.
[ recording ]

Meeting link: https://mun.webex.com/mun/j.php?MTID=m855b1e73549cf668f5b57190a7ef3eae
Meeting number: 2633 483 6250
Meeting password: [REDACTED]

Dalhousie-AARMS AAMP Seminar: Nina Holden (ETH Zürich and the Courant Institute)
2021-11-05 16:00 - 17:00 (America/Halifax) | Zoom seminar
Conformal invariance of percolation on random planar maps
Conformal invariance of critical percolation on the triangular lattice was proved by Smirnov. His proof is hard to extend to critical percolation on other lattices since his proof relies on a combinatorial identity which is only true on the triangular lattice. On random lattices known as random planar maps, however, it turns out that conformal invariance can be established. This was done in joint work with Sun, building on our earlier works with Albenque, Bernardi, Garban, Gwynne, Lawler, Li, and Sepulveda.
The Dalhousie-AARMS Analysis-Applied Math-Physics Seminar takes place on Fridays from 4 – 5 pm Atlantic Time over Zoom. If you would like to attend, please email the organizers for connection details.

Atlantic Graph Theory Seminar: Jo Ellis-Monaghan (University of Amsterdam)
2021-11-03 15:30 - 16:30 UTC | Zoom seminar
2017 saw the centennial of William Tutte, one of the greatest mathematicians of modern times. One of the testimonies to Tutte’s genius is that nearly everything he did proved to be a catalyst, triggering an explosion of further investigations and opening whole new vistas of mathematics. The Tutte polynomial is one of many such examples in his legacy. Here we will explore some of its salient properties and some of the many directions that propagated outward from the original Tutte polynomial. These include several ways in which the Tutte polynomial may be defined and its universality, as well as some of its combinatorial and algebraic properties. We will showcase information encoded in the Tutte polynomial as evaluations and specializations, as these inform nearly every aspect of combinatorics. Furthermore, the scope of the Tutte polynomial is continually broadening through generalizations of either its domain or parameter space, and we will highlight some important examples, and touch on its interrelations with other combinatorial polynomials. We will conclude with its particularly fruitful connections with biology and the Potts model of statistical mechanics, and offer some open questions.

Dalhousie-AARMS AAMP Seminar: Perry Kleinhenz (Michigan State University)
2021-10-29 16:00 - 17:00 (America/Halifax) | Zoom seminar
Title: Stabilization rates for the damped wave equation with polynomial and oscillatory damping

Abstract: In this talk I will discuss energy decay of solutions of the Damped wave equation. After giving an overview of classical results I’ll focus on the torus with damping that does not satisfy the geometric control condition. In this setup properties of the damping at the boundary of its support determine the decay rate, however a general sharp rate is not known.

I will discuss damping which is $0$ on a strip and vanishes either like a polynomial $x^b$ or an oscillating exponential $e^{-1/x} sin^2(1/x)$. Polynomial damping produces decay of the semigroup at exactly $t^{-(b+2)/(b+3)}$, while oscillating damping produces decay at least as fast as $t^{-4/5+delta}$ for any $delta>0$. I will explain how these model cases are proved and how they direct further study of the general sharp rate.

The Dalhousie-AARMS Analysis-Applied Math-Physics Seminar takes place on Fridays from 4 – 5 pm Atlantic Time over Zoom. If you would like to attend, please email the organizers for connection details.

Atlantic Graph Theory Seminar: Guss Regts (University of Amsterdam)
2021-10-27 15:30 - 16:30 UTC | Zoom seminar
Improved bounds for zeros of the chromatic polynomial on bounded degree graphs
About 20 years ago Sokal proved that there exists a constant C so that for any graph G, all of the complex zeros of its chromatic polynomial are contained in the disk of radius C Delta(G) centered at 0. (Here Delta(G) denotes the maximum degree of G.) He showed that C could be taken slightly smaller than 8. This was improved to 6.91 by Fernández and Procacci. In this talk I will present an improvement to 5.02 and explain some of the ideas and ingredients of the proof.
Based on joint work with Maurizio Moreschi, Viresh Patel and Ayla Stam.
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Formulating Success: Industry Research Connector 2021
2021-10-27 13:00 - 15:00 UTC | Zoom seminar
The Formulating Success connector aims to connect Atlantic Canadian companies and not-for-profit organizations with mathematical scientists and statisticians. This is an opportunity for industry and not-for-profits to present data-based challenges; for professors to promote their research with an eye towards establishing partnering opportunities; and for everyone to hear from funding agencies on support mechanisms these collaborations. Rapid-fire 3 minute presentations will enable the understanding of needs, expertise, and funding, and there will be follow-on online networking time to explore future opportunities.
Registration is free at eventbrite.ca

Formulating Success: Industry Research Connector 2021
2021-10-27 13:00 - 15:00 UTC | Zoom seminar
The Formulating Success connector aims to connect Atlantic Canadian companies and not-for-profit organizations with mathematical scientists and statisticians. This is an opportunity for industry and not-for-profits to present data-based challenges; for professors to promote their research with an eye towards establishing partnering opportunities; and for everyone to hear from funding agencies on support mechanisms these collaborations. Rapid-fire 3 minute presentations will enable the understanding of needs, expertise, and funding, and there will be follow-on online networking time to explore future opportunities.
Free registration at eventbrite.ca

AARMS Scientific Machine Learning Seminar: Nicholas Touikan (University of New Brunswick)
2021-10-26 11:00 - 12:00 UTC | WebEx seminar
Group equivariant neural networks seen by a mathematician
Artificial neural networks (ANNs) are incredibly successful at performing certain machine learning tasks, such as classification. In applications such as computer vision or quantum chemistry, we will often seek machine learning algorithms that can handle inputs that are transformed. For example, a cat detector should be able to detect a rotated cat.
Group theory provides the natural formalization of what we mean by transformations and group equivariance is the property we seek in artificial neural networks (ANN) and there is currently a flurry of research activity in group equivariant neural networks. In this talk, I will present the M.Sc. work of my former student Max Hennick, which gives a characterization of (approximate) G-equivariant linear mappings. What is most striking is how effective a bit of functional analysis and algebra can be at answering this question.
I will provide as many examples as possible and conclude with some hopefully interesting questions.
[ recording ]
The AARMS Scientific Machine Learning Seminar takes virtually via WebEx. If you would like to attend, please email the organizers for connection details.

Atlantic Graph Theory Seminar: Viresh Patel (University of Amsterdam)
2021-10-20 15:30 - 16:30 UTC | Zoom seminar
Title: Path decompositions of random directed graphs
In this talk we consider the problem of partitioning the edges of a digraph into as few paths as possible. The minimum number of paths needed in such an edge decomposition is called the path number of the digraph.
The problem of determining the path number is generally NP-hard. However, there is a simple (easy to compute) lower bound for the path number of a digraph in terms of its degree sequence, and a conjecture of Alspach, Pullman, and Mason from 1976 states that this lower bound gives the correct value of the path number for any even tournament. The conjecture was recently resolved, and in this talk I will discuss to what extent the conjecture holds for other digraphs. In particular I will discuss some of the ingredients of a recent result showing that the conjecture holds for almost all digraphs.
More generally we will see the conjecture holds with high probability for the random directed graph D_{n,p} for a large range of p. In fact the proof does not use randomness in a significant way.

This is joint work with Alberto Espuny Díaz and Fabian Stroh.
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Dalhousie-AARMS AAMP Seminar: Ben Landon (University of Toronto)
2021-10-15 16:00 - 17:00 (America/Halifax) | Zoom seminar
Title: Local eigenvalue statistics of random matrices and Dyson Brownian motion
Abstract: Dyson Brownian motion is a stochastic process describing eigenvalue dynamics under a matrix-valued Brownian motion. We will review this process and its role in the study of universality of the local
spectral statistics of random matrices. We discuss results on the local ergodicity of Dyson Brownian motion and applications, including local eigenvalue universality of the adjacency matrices of sparse random graphs
and an additive model related to free probability. Time permitting, we also review results on the universality of extremal spectral statistics and the fluctuations of a single eigenvalue in the spectral bulk.
The Dalhousie-AARMS Analysis-Applied Math-Physics Seminar takes place on Fridays from 4 – 5 pm Atlantic Time in Chase 319 on the Dalhousie University campus with some being broadcasted over Zoom. If you would like to attend, please email the organizers for connection details.

Atlantic Graph Theory Seminar: Danny Dyer (Memorial University)
2021-10-13 15:30 - 16:30 UTC | Zoom seminar
Title: The basics of the deduction game
Abstract:
The deduction game is a new variant of the classical chasers and runners game where the chasers are trying to catch an invisible runner quickly, but with no communication possible between chasers on different vertices. Instead, chasers may deduce where their fellow chasers *must* move, and make corresponding adjustments to their own movements. The goal is to use as few chasers as possible, and in some cases that number is quite high. We will examine some bounds on the deduction number, determine the deduction number of several classes of graphs, and pose some open problems. This is joint work with Andrea Burgess and Mozhgan Farahani.
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Atlantic Graph Theory Seminar: Anthony Bonato (Ryerson University)
2021-10-06 15:30 - 16:30 UTC | Zoom seminar
In pursuit-evasion games, a set of pursuers attempts to locate, eliminate, or contain an evader in a network. The rules, specified from the outset, greatly determine the difficulty of the questions posed above. For example, the evader may be visible, but the pursuers may have limited movement speed, only moving to nearby vertices adjacent to them.
Central to pursuit-evasion games is the idea of optimizing certain parameters, whether they are the search number, burning number, or localization number, for example. We report on progress in several pursuit-evasion games on graphs and conjectures arising from their analysis. Finding the values, bounds, and algorithms to compute these graph parameters leads to topics intersecting graph theory, the probabilistic method, and geometry.

Atlantic Algebra Centre Minicourse: Introduction to Schubert calculus via (nil-)Hecke algebras
2021-09-21 - 2021-09-23 | Zoom seminar
Professor Kirill Zaynullin (University of Ottawa)
From September 20 to September 23, 2021, Professor Kirill Zaynullin from the University of Ottawa will give an introductory mini- course on nil-Hecke algebras and their applications in cohomology.
The mini-course will consist of four lectures and will give a self-contained exposition on the use of the techniques of nil-Hecke algebras in the equivariant Schubert calculus for cohomology of flag varieties.
The first part will discuss root datum and Coxeter groups (Lectures 1-2): definition of a root datum, simple roots, fundamental weights and the Cartan matrix, the Dynkin diagram, the Weyl group, geometric realization, finite real root systems, coefficient ring of a root system, non-crystallographic root datum.
The second part will introduce nil-Hecke rings and twisted group algebras (Lectures 2-3): definition of nil-Coxeter and nil-Hecke rings, twisted group algebras and their localizations, coproducts, Hecke and Weyl actions, characteristic and the Borel maps.
The third part (Lectures 3-4) will relate nil-Hecke rings and the Schubert calculus techniques: push-pull elements and divided- difference operators, the coproduct and the actions, faithful representation, the augmented coproduct and the formula for the coproduct, the dual of the nil-Hecke ring and equivariant cohomology.
The lectures will take place at the St. John’s campus of Memorial University and will be broadcast via Zoom. The schedule is tentatively:

Tuesday, Sep. 21: 9-9:50 am and 3-3:50 pm (Atlantic time)
Wednesday, Sep. 22: 9-9:50 am (Atlantic time)
Thursday, Sep. 23: 9-9:50 am (Atlantic time)

For Zoom connection details and last minute schedule changes, see the event website.

AARMS COVID-19 Seminar: Theodore Kolokolnikov (Dalhousie)
2021-09-20 15:00 - 16:30 (America/Halifax) | Zoom seminar
Modelling of disease spread through heterogeneous population
We present a simple model of disease spread that incorporates spatial variability in population density. Starting from first principles, we derive a novel PDE with state-dependent diffusion. Consistent with observations, this model exhibits higher infection rates in the areas of higher population density. The model also exhibits an infection wave whose speed varies with population density. In addition, we demonstrate the possibility of super-diffusive propagation of infection, whereby an infection can “jump” across areas of low population density towards the areas of high population density. Finally, a case study of coronavirus spread in the Canadian province of Nova Scotia is presented with qualitatively similar features as our model, including density-dependent infection rates and infection that jumps across main population centers.
[ recording ]
More information about this seminar series. This is a virtual zoom seminar. If you would like to attend, please email the organizers for connection details. All times are given in the Atlantic timezone.

AARMS COVID-19 Seminar: Jane Heffernan (York)
2021-08-23 15:00 - 16:30 (America/Halifax) | Zoom seminar
Modelling immunity against SARS-CoV-2 from infection and vaccination: The Atlantic Bubble
We have developed a mathematical model model of COVID-19 in the population. The model is stratified over 5-year age groups, and by immunity status. We track mild, moderate, and severe infections by age, as well as vaccination uptake. The model is fit to COVID-19 case data, and produces estimates of immunity distributions for each age group, from infection and vaccination. In this talk I will provide a overview of the model, and we will discuss results specific to the Atlantic Bubble region.
More information about this seminar series. This is a virtual zoom seminar. If you would like to attend, please email the organizers for connection details. All times are given in the Atlantic timezone.

17th Algorithms and Data Structures Symposium & 33rd Canadian Conference on Computational Geometry
2021-08-09 - 2021-08-12 | Dalhousie University, Halifax, Nova Scotia, Canada
This event consists of two co-located conferences over a four-day period. These two conferences are the 17th Algorithms and Data Structures Symposium (WADS) and the 33rd Canadian Conference on Computational Geometry (CCCG).
WADS is intended as a forum for researchers in the area of design and analysis of algorithms and data structures. We invite submissions of papers presenting original research on the theory and application of algorithms and data structures in all areas, including combinatorics, computational geometry, databases, graphics, and parallel and distributed computing.
CCCG is a forum to disseminate and discuss new theoretical and applied results in discrete and computational geometry. It focuses on the design of efficient algorithms, the development of software, and the study of the mathematical foundations of computational problems whose formulations involve geometric constraints. The field of computational geometry is motivated by problems from a broad range of application areas.

AARMS CRG Online Workshop on Financial Mathematics and Actuarial Science
2021-08-06 | Online via Zoom
The AARMS CRG Online Workshop on Financial Mathematics and Actuarial Science will be held August 6th, 2020 in PEI, Canada. This workshop is mainly hosted by the Atlantic Association for Research in Mathematical Sciences (AARMS) collaborative research group (CRG) and the School of Mathematical and Computational Sciences (SMCS) at University of Prince Edward Island (UPEI), Canada.

AARMS COVID-19 Seminar: Lam Ho (Dalhousie)
2021-07-26 15:00 - 16:30 (America/Halifax) | Zoom seminar
Modelling the dynamics of COVID-19 epidemic
Managing the COVID-19 pandemic has become the top priority since its inception in late 2019. Modelling the development of the epidemic is a crucial step for governments to make effective public health policies. In this talk, we will discuss some challenges of studying the dynamics of the COVID-19 epidemic as well as our recent ideas that cut directly to the heart of these challenges.
More information about this seminar series. This is a virtual zoom seminar. If you would like to attend, please email the organizers for connection details. All times are given in the Atlantic timezone.

AARMS Industrial Problem Solving Workshop 2021
2021-07-26 - 2021-08-06
The Atlantic Association for Research in the Mathematical Sciences (AARMS) will host its third Industrial Problem Solving Workshop (IPSW) in a purely online format from from July 26 to August 6
About IPSWs

The main goals of an IPSW are to build connections between researchers in industry, non-profit organizations, and academia. Organizations based in Atlantic Canada and elsewhere present problems related to their interests, and participants will break into teams to explore solutions to these problems. The problems come from a variety of subject areas, but all are designed to be approachable by students and postdocs with backgrounds in pure mathematics, modelling, scientific computing, computer science, or data analysis. Each problem group will be led by one or more university faculty members with expertise relevant to the technical challenge at hand, but participants with a wide range of interests and expertise are welcome. Over the course of the workshop, problem groups will work collaboratively to explore possible solution strategies to the technical challenges and propose longer-term research directions, as well as make connections to a larger group of companies and academic researchers with similar interests.

Event format

This year’s IPSW will be a little bit different from previous versions: it is two weeks in duration and convened exclusively online. Problem solving teams are invited to use AARMS video-conferencing resources to schedule their own problem solving sessions during the course of the workshop. It is expected that many people will participate on a part-time basis. We will plan to organize several optional live events during the course of the workshop aimed at networking and career-oriented skills training.

Prizes

NBIF Award for best problem solving pitch ($500 shared amongst student/postdoc presenters)
Springboard Atlantic Award for most valuable student/postdoc problem solver ($500 for one student)
AARMS Award for best solution ($2000 shared amongst student/postdoc members of the winning team)
CANSSI Atlantic prize for the most effective use of statistics in problem solving ($200 for one student)

Important dates

July 21, 2021: Registration deadline
July 23, 2021: Prerecorded problem presentations from industry and non-academic partners available online
July 26, 2021: Live Q&A panel from industrial and non-academic representatives
July 26-30, 2021: Groups meet online to discuss problem solving strategies
July 30, 2021: Mid-workshop progress presentations
August 3-6, 2021: Groups meet online to discuss problem solving strategies
August 6, 2021: Final presentation of problem solutions

AARMS COVID-19 Seminar: Cindy Feng (Dalhousie)
2021-07-12 15:00 - 16:30 (America/Halifax) | Zoom seminar
Spatial-Temporal Modeling of COVID-19 Mortality Risk in Toronto, Canada
In this talk, a spatial-temporal model for modeling georeferenced COVID -19 mortality data in Toronto, Canada will be presented. A range of factors and spatial-temporal terms are incorporated into the model. The non-linear and interactive effects of the neighborhood-level factors, i.e., population density and average of income, are modeled as a two-dimensional spline smoother. The change of spatial pattern over time is modeled as a three-dimensional tensor product smoother. By fitting this model, the space-time effect can uncover the underlying spatial-temporal pattern that is not explained by the covariates. The performance of the modeling method based on the individual data is also compared to the modeling methods based on the aggregated data in terms of in-sample and out-of-sample predictive checking. The results suggest that the individual-level based analysis provided a better overall model fit and higher predictive accuracy for detecting epidemic peaks as compared to the analysis based on the aggregated data in this application.
More information about this seminar series. This is a virtual zoom seminar. If you would like to attend, please email the organizers for connection details. All times are given in the Atlantic timezone.

Junior Math and Computer Science Camp
2021-07-05 - 2021-07-09 | Acadia University, Wolfville, Nova Scotia, Canada
This week-long day camp is an opportunity for students entering
grade 5 or 6 in the Annapolis Valley to participate in fun and enriching
science-based activities with Acadia faculty and students to develop
their curiosity and enjoyment of math and computer science. It
represents an important piece of a multi-year plan to develop the
mathematical skills of students in the Annapolis Valley by bringing
young students into the Acadia University outreach program. This will
begin the process of positively engaging students with math and
computer science at a critical time in their educational careers.
Bursaries are provided for those who qualify for financial assistance.

Aiden Bruen 80th Birthday Geometry Conference
2021-06-13 - 2021-06-18 | Fields Institute, 222 College St., Toronto, Ontario, M5T 3J1, Canada
This conference is in celebration of Professor Aiden Bruen’s 80th birthday, to acknowledge and honour his contributions to finite geometry, design theory, coding theory, and combinatorics in general. Professor Bruen has had a tremendous impact in these areas, publishing dozens of highly cited articles. including but certainly not limited to Inventiones Mathematicae, Journal of Combinatorial Theory, Series A, Journal of Combinatorial Designs, and Designs, Codes and Cryptography. Professor Bruen is also an author of Cryptography, Information Theory, and Error Correction: a Handbook for the 21st Century, by A.A. Bruen and M.A. Forcinito, Wiley, 2004. This conference will bring together top researchers in the themed areas to present their latest work, and will facilitate opportunities for collaboration in order to further research in theses areas.
