## Applied Mathematics Colloquium - Nalini Joshi

Oct. 29, 2021

Nalini Joshi, Department of Applied Mathematics, The University of Sydney, New South Wales, Australia Motion and monodromy Newton was inspired by Kepler’s laws of planetary motion to study motion on curves. This led him immediately to transcendental functions, that is, functions that cannot arise as solutions of polynomial equations. A...

## Applied Mathematics Colloquium - Lisa Fauci

Oct. 22, 2021

Lisa Fauci, Department of Mathematics, Tulane University Buckling, mixing, swimming, dissolving: adventures with helices at the microscale. The motion of passive or actuated elastic filaments in a fluid environment is a common element in many biological and engineered systems. Examples at the microscale include bacterial flagella propelling a cell body...

## Applied Mathematics Colloquium - Eduardo Corona

Oct. 8, 2021

Eduardo Corona, Department of Applied Mathematics, University of Colorado Boulder A crash course in boundary integral methods with applications to Stokesian suspensions Boundary integral methods consist on re-formulating PDE boundary value problems in terms of integral operators. If this integral formulation is chosen carefully, this can reduce the dimensionality of...

## Applied Mathematics Colloquium: Margaret Cheney

Oct. 1, 2021

Margaret Cheney, Department of Mathematics at Colorado State University, will talk, "Passive Source Localization" This talk introduces the problem of localizing electromagnetic sources from measurements of their radiated fields at two moving sensors. Two approaches are discussed, the first based on measuring quantities known as “time difference of arrivals“ and...

## Applied Mathematics Colloquium - Leslie Greengard

Sept. 24, 2021

Leslie Greengard, Courant Department of Mathematics, New York University Adaptive methods for the simulation of diffusion and fluid flow in complex geometries We will review the state of the art in integral equation methods for the solution of the heat equation and fluid flow in moving geometries. With suitable fast...

## Applied Mathematics Colloquium - John Bush

Sept. 10, 2021

John Bush, Department of Mathematics, Massachusetts Institute of Technology (MIT) Hydrodynamic quantum analogs In 2005, Yves Couder and Emmanuel Fort discovered that droplets walking on a vibrating fluid bath exhibit several features previously thought to be exclusive to the microscopic, quantum realm. These walking droplets propel themselves by virtue of...

## Applied Mathematics Colloquium - Doug Nychka and Florian Gerber

Sept. 3, 2021

Doug Nychka, Department of Applied Mathematics and Statistics, Colorado School of Mines Florian Gerber, Department of Biostatistics, University of Zurich Climate models, large spatial datasets, and harnessing deep learning for a statistical computation Numerical simulations of the motion and state of the Earth's atmosphere and ocean yield large and complex...

## Applied Mathematics Colloquium - Mason Porter

Aug. 27, 2021

Mason Porter; Department of Mathematics; University of California, Los Angeles (UCLA) Opinion Dynamics on Networks From the spreading of diseases and memes to the development ofopinions and social influence, dynamical processes are influenced heavilyby the networks on which they occur. In this talk, I'll discuss the socialinfluence and opinion models...

## APPM Department Colloquium - Matthew Peters

April 30, 2021

Matthew Peters, Senior Research Scientist, Allen Institute for Artificial Intelligence A guided tour of contextual word representations for language understanding The last 3-4 years have seen a tremendous increase in the abilities of natural language understanding systems to perform tasks such as text generation, question answering, and information extraction. These...

## APPM Department Colloquium - Abdelrahman Mohamed

April 26, 2021

Abdelrahman Mohamed, Research Scientist, Facebook AI Research Recent advances in speech representation learning Self-supervised representation learning methods recently achieved great successes in NLP and computer vision domains, reaching new performance levels while reducing required labels for many downstream scenarios. Speech representation learning is experiencing similar progress, with work primarily focused...