# Colloquia

The Applied Mathematics and Statistics Colloquium takes place at 3 p.m. on Fridays. The format for the seminars this semester is a 30 minute talk + interview via Zoom. Please contact Jennifer Ryan at jkryan@mines.edu for further information and the Zoom link and password.

View colloquium videos on YouTube.

## Spring 2021

**Book Club** (See schedule and discussed chapters below): As part of our colloquia this semester, we will share a discussion of:

The summary provided from the wikipedia page describes the book in the following manner:

“Rosling suggests the vast majority of human beings are wrong about the state of the world. He demonstrates that his test subjects believe the world is poorer, less healthy, and more dangerous than it actually is, attributing this not to random chance but to misinformation.

Rosling recommends thinking about the world as divided into four levels based on income brackets (rather than the prototypical developed/developing framework) and suggests ten instincts that prevent us from seeing real progress in the world “

January 29 | Book Club "Factfulness: 10 Reasons We’re Wrong about the World – and Why Things are Getting Better" (2018), Hans Rosling Chapters 1-3 |
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February 5 | Michelle McCarthy Boston University |

February 12 | Daniel Nordman Iowa State |

February 19 Special Time of 1:00 PM | Olivia Prosper University of Tennessee |

February 26 | Book Club "Factfulness: 10 Reasons We’re Wrong about the World – and Why Things are Getting Better" (2018), Hans Rosling Chapters 4-6 |

March 12 | Lise-Marie Imbert-Gerard University of Arizona |

March 19 | Ethan Anderes UCDavis |

March 26 | Book Club "Factfulness: 10 Reasons We’re Wrong about the World – and Why Things are Getting Better" (2018), Hans Rosling Chapters 7-9 |

April 9 | Andrew Zammit Mangion University of Wollongong |

April 16 | Diogo Bolster University of Notre Dame |

April 23 | Kiona Ogle Northern Arizon |

April 30 | Book Club "Factfulness: 10 Reasons We’re Wrong about the World – and Why Things are Getting Better" (2018), Hans Rosling Chapter 9-10 + Factfulness Rules of Thumb |

**Book Club** (See schedule and discussed chapters below): As part of our colloquia this semester, we will share a discussion of:

“Weapons of Math Destruction” by Cathy O’Neil

https://weaponsofmathdestructionbook.com

**Zoom link for book club.** Please contact Jennifer Ryan at jkryan@mines.edu for further information and the Zoom link and password.

## Fall 2020

September 18 | Zachary J. Grant Oak Ridge National Lab Analysis and Development of Strong Stability Preserving Time Stepping Schemes High order spatial discretizations with monotonicity properties are often desirable for the solution of hyperbolic partial differential equations. These methods can advantageously be coupled with high order strong stability preserving time scheme to accurately evolve solutions forward in time while preserving convex functionals that are satisfied from the design of the spatial discretization. The search for high order strong stability time- stepping methods with large allowable strong stability coefficient has been an active area of research over the last three decades. In this talk I will review the foundations of SSP time stepping schemes as in how to analyze a given scheme, and how to optimally build a method which allows the largest effective stable time step. We will then discuss some extensions of the SSP methods in recent years and some ongoing research problems in the field, and show some the need of the SSP property through simple yet demonstrative examples. |
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September 25 | Book Club “Weapons of Math Destruction” Chapter 1-4 |

October 2 | |

October 16 | Minah Oh James Madison University Fourier Finite Element Methods and Multigrid for Axisymmetric H(div) Problems An axisymmetric problem is a problem defined on a three-dimensional (3D) axisymmetric domain, and it appears in numerous applications. An axisymmetric problem can be reduced to a sequence of two-dimensional (2D) problems by using cylindrical coordinates and a Fourier series decomposition. Fourier Finite Element Methods (Fourier-FEMs) can be used to approximate each Fourier-mode of the solution by using a suitable FEM. Such dimension reduction is an attractive feature considering computation time, but the resulting 2D problems are posed in weighted function spaces where the weight function is the radial component r. Furthermore, the grad, curl, and div operators appearing in these weighted problems are quite different from the standard ones, so the analysis of such weighted problems requires special attention. Multigrid is an effective iterative method that can be used to solve large matrix systems arising from FEMs. In this talk, I will present a multigrid algorithm that can be applied to weighted H(div) problems that arise after performing a dimension reduction to an axisymmetric H(div) problem. Theoretical results that show the uniform convergence of the multigrid V-cycle with respect to meshsize will be presented as well as numerical results. |

October 30 | Book Club: “Weapons of Math Destruction” Chapters 5 - 7 |

November 6 | Mokshay Madiman University of Delaware Concentration of information for log-concave distributions In 2011, S. Bobkov and the speaker showed that for a random vector X in R^n drawn from a log-concave density f=e^{-V}, the information content per coordinate, namely V(X)/n, is highly concentrated about its mean. The result demonstrated that high-dimensional log-concave measures are in a sense close to uniform distributions on the annulus between 2 nested convex sets (generalizing the well known fact that the standard Gaussian measure is concentrated on a thin spherical annulus). We present recent work that obtains an optimal concentration bound in this setting, using a much simplified proof. Applications that motivated the development of these results include high-dimensional convex geometry, random matrix theory, and shape-constrained density estimation. The talk is based on joint works with Sergey Bobkov (University of Minnesota), Matthieu Fradelizi (Université Paris Est), and Liyao Wang. |

November 20 | Ayaboe Edoh Edwards AFRL Balancing Numerical Dispersion, Dissipation, and Aliasing for Time-Accurate Simulations The investigation of unsteady flow phenomena calls for the need to improve time-accurate simulation capabilities. Numerical errors responsible for affecting solution accuracy and robustness can be broadly categorized in terms of dispersion, dissipation, and aliasing. Their presence is a consequence of discretizing the continuous governing equations, and their impact may be felt at all scales (albeit to varying degrees). The task of constructing an effective numerical method may therefore be interpreted in terms of reducing the influence of these errors over as broad a range of scales as possible. Here, a concerted assembly of scheme components is chosen relative to a target aliasing limit. High-order and optimized finite difference stencils are employed in order to achieve accuracy; meanwhile, split representations for nonlinear transport terms are used in order to greatly improve robustness. Finally, tunable and scale-discriminant artificial-dissipation methods are incorporated for de-aliasing purposes and as a means of further enhancing both accuracy and stability. The proposed framework is motivated by the need to devise a numerical format capable of mitigating discretization effects in Large-Eddy Simulations. |

December 4 | Book Club “Weapons of Math Destruction” Chapters 8-10 |

##### Spring 2020

January 24 | Mevin Hooten Colorado State University Runnning on empty: Recharge dynamics from animal movement data |
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February 14 | Mark Risser Lawrence Berkeley National Laboratory Bayesian inference for high-dimensional nonstationary Gaussian processes |

February 21 | Donna Calhoun Boise State University A fully unsplit wave propagation algorithm for shallow water flows on GPUs |

February 28 | Matthias Katzfuss Texas A&M Gaussian-Process Approximations for Big Data |

March 20 | Nancy Rodriguez |

April 3 | Dan Nordman |

April 10 | Grady Wright |

April 24 | Feng Bao |

##### Fall 2019

August 23 | Chris Elvidge NOAA and Mines' Payne Institute of Public Policy VIIRS Data Gems From the Nights |

September 13 | Cynthia Phillips Sandia National Laboratory Advanced Data Structures for National Cyber Security |

September 20 | Will Kleiber University of Colorado - Boulder Mixed Graphical-Basis Models for Large Nonstationary and Multivariate Spatial Data Problems |

October 4 | Igor Cialenco Illinois Institute of Technology Adaptive Robust Control Under Model Uncertainty |

October 18 | Tathagata Bandyopadhyay Indian Institute of Management Ahmedabad Inference Problems in Binary Regression Model with Misclassified Responses Video |

October 25 | Daniel Forger University of Michigan Math, Music and the Mind; Analysis of the performed Trio Sonatas of J.S. Bach |

November 8 | Daniel Larremore University of Colorado - Boulder Complex Networks & Malaria: From Evolution to Epidemiology Video |

November 22 | Marisa Eisenberg University of Michigan |

December 3 | Russell Cummings United States Air Force Academy The DoD High Performance Computing Modernization Program’s Hypersonic Vehicle Simulation Institute: Objectives and Progress -A Mechanical Engineering Seminar- |

##### Spring 2019

January 25 | Steve Sain Jupiter Intelligence Data Science @ Jupiter |

February 1 | Xingping Sun Missouri State University Kernel Based Monte Carlo Approximation Methods |

February 8 | Mandy Hering Baylor University Fault Detection and Attribution for a Complex Decentralized Wastewater Treatment Facility |

February 22 | Bailey K. Fosdick Colorado State University Inference for Network Regressions with Exchangeable Errors |

March 8 | Radu Cascaval University of Colorado - Colorado Springs The Mathematics of (Spatial) Mobility |

March 15 | Amneet Bhalla San Diego State University A Robust and Efficient Wave-Structure Interaction Solver for High Density Ratio Multiphase Flows Video |

March 22 | Robert Lund Clemson University Stationary Count Time Series |

April 5 | Hua Wang Colorado School of Mines Learning Sparsity-Induced Models for Understanding Imaging Genetics Data Video |

April 26 | Wen Zhou Colorado State University Estimation and Inference of Heteroskedasticity Models with Latent Semiparametric Factors for Multivariate Time Series Video |

May 3 | Olivier Pinaud Colorado State University Time Reversal by Time-dependent Perturbations Video |

##### Fall 2018

August 31 | Michael Wakin Colorado School of Mines Modal Analysis from Random and Compressed Samples Video |

September 14 | Michael Scheuerer National Oceanic and Atmospheric Administration (NOAA) Generating Calibrated Ensembles of Physically Realistic, High-Resolution Precipitation Forecast Fields based on GEFS Model Output Video |

September 28 | Kathryn Colborn CU Denver, Anschutz Medical Campus Spatio-Temporal Modelling of Malaria Incidence for Early Epidemic Detection in Mozambique Video |

October 12 | Philippe Naveau Laboratoire des Sciences du Climat et de l'Environnement, IPSL-CNRS, France Analysis of Extreme Climate Events by Combining Multivariate Extreme Values Theory and Causality Theory Video |

October 26 | Carrie Manore Los Alamos National Laboratory Modeling Disease Risk with Social and Environmental Drivers and Non-traditional Data Sources |

November 2 | Jon Trevelyan Durham University, UK Enriched Simulations in Computational Mechanics Video |

November 9 | Sarah Olson Worcester Polytechnic Institute Modeling Cell Motility: From Agent Based Models to Continuous Approximations Video |

November 30 | Elwin van't Wout Pontificia Universidad Católica de Chile Efficient Numerical Simulations of Wave Propagation Phenomena Video |

December 7 | Bruce Bugbee National Renewable Energy Laboratory (NREL) |

##### Spring 2018

March 2 | Grant Brown University of Iowa Biostatistics Working with Approximate Bayesian Computation in Stochastic Compartmental Models Video |

March 9 | Victoria Booth University of Michigan Mathematics Neuromodulation of Neural Network Dynamics Video |

March 23 | Daniel Appelö University of Colorado Applied Math What’s New with the Wave Equation? Video |

April 6 | Grad Student Showcase Video |

April 20 | Jem Corcoran University of Colorado Applied Math A Birth-and-Death Process for the Discretization of Continuous Attributes in Bayesian Network Structure Recovery Video |

May 4 | Ian Sloan University of New South Wales Mathematics Sparse Approximation and the Cosmic Microwave Background Video |

##### Fall 2017

August 25 | Zachary Kilpatrick University of Colorado Boulder, Department of Applied Mathematics Evidence accumulation in changing environments: Neurons, organisms, and groups |

September 8 | Lincoln Carr Colorado School of Mines, Department of Physics Many-Body Quantum Chaos of Ultracold Atoms in a Quantum Ratchet Video |

September 22 | Joe Guinness North Carolina State University, Department of Statistics A General Framework for Vecchia Approximations of Gaussian Processes Video |

October 13 | Eliot Fried Okinawa Institute of Science and Technology, Mathematics, Mechanics, and Materials Unit Shape Selection Induced by Competition Between Surface and Line Energy |

October 20 | Arthur Sherman National Institutes of Health Diabetes Pathogenesis as a Threshold-Crossing Process Video |

November 3 | Adrianna Gillman Rice University, Department of Computational and Applied Mathematics Fast Direct Solvers for Boundary Integral Equations Video |

November 17 | Laura Miller University of North Carolina at Chapel Hill, Departments of Mathematics and Biology Using Computational Fluid Dynamics to Understand the Neuromechanics of Jellyfish Swimming Video |

December 1 | AMS Graduate Student Showcase Video |

##### Spring 2017

January 13 | Roger Ghanem University of Southern California, Department of Aerospace and Mechanical Engineering Uncertainty quantification at the interface of computing and everything else Special joint colloquium with Department of Mechanical Engineering Video |

January 27 | Wolfgang Bangerth Colorado State University, Department of Mathematics Simulating complex flows in the Earth mantle Video |

February 10 | Chris Mast Mercer, Actuary and Employee Benefits Consultant Actuarial problems in employer-sponsored healthcare Video |

February 24 | Natasha Flyer National Center for Atmospheric Research, Computational Math Group Bengt Fornberg University of Colorado Boulder, Department of Applied Mathematics Radial basis functions: Freedom from meshes in scientific computing Video |

March 10 | Michael Sprague National Renewable Energy Laboratory, Computational Science Center A computational model for a dilute biomass suspension undergoing mixing and settling Video |

March 24 | Randall J. LeVeque University of Washington, Department of Applied Mathematics Generating random earthquakes for probabilistic hazard assessment Special joint colloquium with US Geological Survey Video |

April 7 | Fred J. Hickernell Illinois Institute of Technology, Department of Applied Mathematics Think like an applied mathematician and a statistician Video |

April 14 | Ian Sloan University of New South Wales, School of Mathematics How high is high dimensional? Video |

April 21 | Mark Embree Virginia Tech, Department of Mathematics Using interpolatory approximations to learn from an instrumented building Video |

April 28 | James A. Warren National Institute of Standards and Technology, Material Measurement Laboratory The Materials Genome Initiative: NIST, data, and open science Video Special joint colloquium with Department of Metallurgical and Materials Engineering |

May 5 | Jessica F. Ellis Colorado State University, Department of Mathematics The features of college calculus programs: An overview of the MAA two calculus projects' main findings Video |

##### Fall 2016

September 2 | Stephen Becker University of Colorado Boulder, Department of Applied Mathematics Subsampling large datasets via random mixing Video |

September 16 | Art Owen Stanford University, Department of Statistics Permutation p-value approximation via generalized Stolarsky invariance Video |

September 30 | Stefan Wild Argonne National Laboratory, Mathematics and Computer Science Division Beyond the black box in derivative-free and simulation-based optimization Video |

October 14 | Erica Graham Bryn Mawr College, Department of Mathematics Modeling physiological and pathological mechanisms in ovulation Video |

October 28 | Jim Koehler Google Boulder, Principal Statistician Statistical methods supporting Google's ad business |

November 11 | Dennis Cook University of Minnesota, School of Statistics An Introduction to envelopes: Methods for improving efficiency in multivariate statistics Video |

December 2 | Howard Elman University of Maryland, Department of Computer Science Efficient computational methods for parameterized partial differential equations Video |