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 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 29Book Club
"Factfulness: 10 Reasons We’re Wrong about the World – and Why Things are Getting Better" (2018), Hans Rosling
Chapters 1-3
February 5Michelle McCarthy
Boston University
February 12Daniel Nordman
Iowa State
February 19
Special Time of 1:00 PM
Olivia Prosper
University of Tennessee
February 26Book Club
"Factfulness: 10 Reasons We’re Wrong about the World – and Why Things are Getting Better" (2018), Hans Rosling
Chapters 4-6
March 12Lise-Marie Imbert-Gerard
University of Arizona
March 19Ethan Anderes
March 26Book Club
"Factfulness: 10 Reasons We’re Wrong about the World – and Why Things are Getting Better" (2018), Hans Rosling
Chapters 7-9
April 9Andrew Zammit Mangion
University of Wollongong
April 16Diogo Bolster
University of Notre Dame
April 23Kiona Ogle
Northern Arizon
April 30Book 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

Zoom link for book club. Please contact Jennifer Ryan at for further information and the Zoom link and password. 

Fall 2020

September 18Zachary 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.
September 25Book Club
“Weapons of Math Destruction”
Chapter 1-4
October 2
October 16Minah 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 30Book Club:
“Weapons of Math Destruction”
Chapters 5 - 7
November 6Mokshay 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 20Ayaboe 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 4Book Club
“Weapons of Math Destruction”
Chapters 8-10
Spring 2020
January 24Mevin Hooten
Colorado State University
Runnning on empty: Recharge dynamics from animal movement data
February 14Mark Risser
Lawrence Berkeley National Laboratory
Bayesian inference for high-dimensional nonstationary Gaussian processes
February 21Donna Calhoun
Boise State University
A fully unsplit wave propagation algorithm for shallow water flows on GPUs
February 28Matthias Katzfuss
Texas A&M
Gaussian-Process Approximations for Big Data
March 20Nancy Rodriguez
April 3Dan Nordman
April 10Grady Wright
April 24 Feng Bao
Fall 2019
August 23Chris Elvidge
NOAA and Mines' Payne Institute of Public Policy
VIIRS Data Gems From the Nights
September 13Cynthia Phillips
Sandia National Laboratory
Advanced Data Structures for National Cyber Security
September 20Will Kleiber
University of Colorado - Boulder
Mixed Graphical-Basis Models for Large Nonstationary and Multivariate Spatial Data Problems
October 4Igor Cialenco
Illinois Institute of Technology
Adaptive Robust Control Under Model Uncertainty
October 18Tathagata Bandyopadhyay
Indian Institute of Management Ahmedabad
Inference Problems in Binary Regression Model with Misclassified Responses
October 25Daniel Forger
University of Michigan
Math, Music and the Mind; Analysis of the performed Trio Sonatas of J.S. Bach
November 8Daniel Larremore
University of Colorado - Boulder
Complex Networks & Malaria: From Evolution to Epidemiology
November 22Marisa Eisenberg
University of Michigan
December 3Russell 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 25Steve Sain
Jupiter Intelligence
Data Science @ Jupiter
February 1Xingping Sun
Missouri State University
Kernel Based Monte Carlo Approximation Methods
February 8Mandy Hering
Baylor University
Fault Detection and Attribution for a Complex Decentralized Wastewater Treatment Facility
February 22Bailey K. Fosdick
Colorado State University
Inference for Network Regressions with Exchangeable Errors
March 8Radu Cascaval
University of Colorado - Colorado Springs
The Mathematics of (Spatial) Mobility
March 15Amneet Bhalla
San Diego State University
A Robust and Efficient Wave-Structure Interaction Solver for High Density Ratio Multiphase Flows
March 22Robert Lund
Clemson University
Stationary Count Time Series
April 5Hua Wang
Colorado School of Mines
Learning Sparsity-Induced Models for Understanding Imaging Genetics Data
April 26Wen Zhou
Colorado State University
Estimation and Inference of Heteroskedasticity Models with Latent Semiparametric Factors for Multivariate Time Series
May 3Olivier Pinaud
Colorado State University
Time Reversal by Time-dependent Perturbations
Fall 2018
August 31Michael Wakin
Colorado School of Mines
Modal Analysis from Random and Compressed Samples
September 14Michael Scheuerer
National Oceanic and Atmospheric Administration (NOAA)
Generating Calibrated Ensembles of Physically Realistic, High-Resolution Precipitation Forecast Fields based on GEFS Model Output
September 28Kathryn Colborn
CU Denver, Anschutz Medical Campus
Spatio-Temporal Modelling of Malaria Incidence for Early Epidemic Detection in Mozambique
October 12Philippe 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
October 26Carrie Manore
Los Alamos National Laboratory
Modeling Disease Risk with Social and Environmental Drivers and Non-traditional Data Sources
November 2Jon Trevelyan
Durham University, UK
Enriched Simulations in Computational Mechanics
November 9Sarah Olson
Worcester Polytechnic Institute
Modeling Cell Motility: From Agent Based Models to Continuous Approximations
November 30Elwin van't Wout
Pontificia Universidad Católica de Chile
Efficient Numerical Simulations of Wave Propagation Phenomena
December 7Bruce Bugbee
National Renewable Energy Laboratory (NREL)
Spring 2018
March 2Grant Brown
University of Iowa Biostatistics
Working with Approximate Bayesian Computation in Stochastic Compartmental Models
March 9Victoria Booth
University of Michigan Mathematics
Neuromodulation of Neural Network Dynamics
March 23Daniel Appelö
University of Colorado Applied Math
What’s New with the Wave Equation?
April 6Grad Student Showcase
April 20Jem Corcoran
University of Colorado Applied Math
A Birth-and-Death Process for the Discretization of Continuous Attributes in Bayesian Network Structure Recovery
May 4Ian Sloan
University of New South Wales Mathematics
Sparse Approximation and the Cosmic Microwave Background
Fall 2017
August 25Zachary Kilpatrick
University of Colorado Boulder, Department of Applied Mathematics
Evidence accumulation in changing environments: Neurons, organisms, and groups
September 8Lincoln Carr
Colorado School of Mines, Department of Physics
Many-Body Quantum Chaos of Ultracold Atoms in a Quantum Ratchet
September 22Joe Guinness
North Carolina State University, Department of Statistics
A General Framework for Vecchia Approximations of Gaussian Processes
October 13Eliot Fried
Okinawa Institute of Science and Technology, Mathematics, Mechanics, and Materials Unit
Shape Selection Induced by Competition Between Surface and Line Energy
October 20Arthur Sherman
National Institutes of Health
Diabetes Pathogenesis as a Threshold-Crossing Process
November 3Adrianna Gillman
Rice University, Department of Computational and Applied Mathematics
Fast Direct Solvers for Boundary Integral Equations
November 17Laura Miller
University of North Carolina at Chapel Hill, Departments of Mathematics and Biology
Using Computational Fluid Dynamics to Understand the Neuromechanics of Jellyfish Swimming
December 1AMS Graduate Student Showcase
Spring 2017
January 13Roger 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
January 27Wolfgang Bangerth
Colorado State University, Department of Mathematics
Simulating complex flows in the Earth mantle
February 10Chris Mast
Mercer, Actuary and Employee Benefits Consultant
Actuarial problems in employer-sponsored healthcare
February 24Natasha 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
March 10Michael Sprague
National Renewable Energy Laboratory, Computational Science Center
A computational model for a dilute biomass suspension undergoing mixing and settling
March 24Randall J. LeVeque
University of Washington, Department of Applied Mathematics
Generating random earthquakes for probabilistic hazard assessment
Special joint colloquium with US Geological Survey
April 7Fred J. Hickernell
Illinois Institute of Technology, Department of Applied Mathematics
Think like an applied mathematician and a statistician
April 14Ian Sloan
University of New South Wales, School of Mathematics
How high is high dimensional?
April 21Mark Embree
Virginia Tech, Department of Mathematics
Using interpolatory approximations to learn from an instrumented building
April 28James A. Warren
National Institute of Standards and Technology, Material Measurement Laboratory
The Materials Genome Initiative: NIST, data, and open science
Special joint colloquium with Department of Metallurgical and Materials Engineering
May 5Jessica F. Ellis
Colorado State University, Department of Mathematics
The features of college calculus programs: An overview of the MAA two calculus projects' main findings
Fall 2016
September 2Stephen Becker
University of Colorado Boulder, Department of Applied Mathematics
Subsampling large datasets via random mixing
September 16Art Owen
Stanford University, Department of Statistics
Permutation p-value approximation via generalized Stolarsky invariance
September 30Stefan Wild
Argonne National Laboratory, Mathematics and Computer Science Division
Beyond the black box in derivative-free and simulation-based optimization
October 14Erica Graham
Bryn Mawr College, Department of Mathematics
Modeling physiological and pathological mechanisms in ovulation
October 28Jim Koehler
Google Boulder, Principal Statistician
Statistical methods supporting Google's ad business
November 11Dennis Cook
University of Minnesota, School of Statistics
An Introduction to envelopes: Methods for improving efficiency in multivariate statistics
December 2Howard Elman
University of Maryland, Department of Computer Science
Efficient computational methods for parameterized partial differential equations