Thematic Sessions

Propose a thematic session

Proposals for thematic sessions will be accepted until August 18th September 1st. A successful proposal should include a descriptive title and abstract, list of organizers, and number of potential speakers. The abstract should describe the topic of the session clearly and is meant to attract both audience members and speakers.

Thematic session proposals can be submitted through the online form.

Sessions will consist of up to six 20 minute talks with 5 minutes of of questions per talk. Sample sessions from the 2017 Conference can be found at that meeting's website.

Proposals are subject to approval by the 2019 SIAM PNW Organizing Committee.

Accepted Thematic Sessions

1. Algebra, Geometry, and Applications

Organizer: Nathan Ilten (Simon Fraser University)
Methods and results from algebra and geometry are increasingly finding application in a variety of fields such as statistics, biology, and data science. This session will focus on recent developments in algebraic geometry and related areas, with a view towards applications.

2. Stochastic Models in Mathematical Finance

Organizers: Tim Leung (University of Washington) and Bahman Angoshtari (University of Washington)
This session will showcase recent work in the development and analysis of stochastic models arising from different practical applications in finance, ranging from derivatives pricing to dynamic trading.

3. Recent Advances in Nonlinear Waves

Organizers: John Carter (Seattle University) and Bernard Deconinck (University of Washington)
This session brings together scientists and mathematicians from a variety of areas. With a focus on nonlinear waves, the speakers will present new experimental, analytical, and numerical results.

4. Machine Learning Methods for Dynamical Systems

Organizers: Jason Bramburger (University of Victoria) and Henning Lange (University of Washington)
This session features recent advances in machine learning techniques for the analysis of dynamical systems. Topics include data driven discovery of governing equations, dimensionality reduction or reduced order modeling, and forecasting of dynamical systems which may exhibit multiple timescales, non-linear behavior or unstructred as well structured noise. As the session is focused on algorithms, each talk will provide applications of their method to motivating and illustrative examples coming from areas such as engineering, physics, chemistry, biology, meteorology and ecology.

5. Fluid Mechanics: Systems and Models

Organizers: Ralph Showalter (Oregon State University) and Choah Shin (Oregon State University)
This session is devoted to fluids and their occurrence within mechanical systems. These include the theory and modeling of free fluid, flow through porous media, and other types of fluid-solid coupled systems.

6. Mathematics of the Weather & Climate

Organizers: David Muraki (Simon Fraser University) and Ray Walsh (Simon Fraser University)
The key questions of weather and climate are about quantifying change. Presented in this session are new approaches that target a better understanding of our changing environment. These span the mathematics of data methods, numerical computations and geophysical models. A collection of talks tell the mathematical stories of reconstructing of paleoclimate, computing the dynamics of sea ice, and uncovering the waves behind the evolution of cloud shapes.

7. Mathematical Ecology and Epidemiology

Organizers: Benjamin Liu (University of Washington) and Kelsey Marcinko (University of Washington)
This session will feature work on mathematical modeling and analysis of the dynamics of populations and infectious diseases. Topics will include models for the movement and spread of populations as well as transmission and spread of infectious diseases.

8. Uncertainty Quantification

Organizers: Arnab Bhattacharya (PNNL) and Xiu Yang (Lehigh University)
Uncertainty quantification (UQ) involves the quantitative characterization and management of uncertainty in a broad range of applications involving computational models, observational data and theoretical analysis. UQ addresses research questions on a broad range of topics including uncertainty propagation, sensitivity analysis, statistical inference, optimal sampling, multi-fidelity modeling, machine learning etc. This session aims to bring researchers working on current state-of-the-art UQ methods from different disciplines with focus on dynamical systems, decision-making under uncertainty, stochastic optimization and machine learning.

9. Nonlinear Dynamical PDEs

Organizers: David Goluskin (University of Victoria) and Slim Ibrahim (University of Victoria)
Speakers will present results on various nonlinear dynamical PDEs, including the Kuramoto–Sivashinsky equation, the nonlinear Schrödinger equation, and other wave equations. All talks will involve analysis; some talks will include computational results.

10. Advances in Mathematical Neuroscience

Organizers: Andrew Oster (Eastern Washington University) and Alex Dimitrov (WSU-Vancouver)
Due to the complexity of neurological systems, mathematical and computational techniques are essential to gain insight to the mechanisms underlying neural processes. In this session, mathematical approaches will be showcased in order to study phenomena from areas such as neuromechanics, synaptic plasticity, neurodevelopment, and working memory.

11. Numerical Analysis and Scientific Computing

Organizers: Malgorzata Peszynska (Oregon State University) and Grady Wright (Boise State University)
This session focuses on recent results in the design, analysis, and efficient implementation of numerical methods and on their applications to challenging scientific problems. Talks will be on topics including numerical methods for differential equations, numerical linear algebra, approximation theory, and parallel computing.

12. Inverse Problems in Imaging

Organizer: Thomas Humphries (University of Washington Bothell)
This session features work on the mathematical solution of inverse problems in imaging, including analytical and iterative methods, sparse recovery, and approaches using machine learning.

13. Mathematical Modeling for Multiphase flow

Organizers: Amanda Howard (PNNL) and W. Steven Rosenthal (PNNL)
Presentations in this session focus on mathematical methods for simulations of multiphase fluid flows, including fluid-fluid and fluid-solid flows.

14. Numerical Methods for Atmosphere and Ocean

Organizers: Michal Kopera (Boise State University) and Donna Calhoun (Boise State University)
This session is focused on computational approaches to simulation of phenomena in the atmosphere and ocean. Topics of interests include simulations with global and local area models, validation of numerical methods on simplified test cases, alternative approaches to the modeling of physical processes (including AI and machine learning), parallelization and model efficiency, as well as practical issues in model development.

15. Models and Theories in Mathematical Biology and Biophysics

Organizers: Ying-Jen Yang (University of Washington) and Yu-Chen Cheng (University of Washington)
In this session, speakers will discuss recent advances in mathematical models and/or theories for biological systems. Approaches discussed include dynamical systems, probability theory and stochastic processes, information theory, as well as thermodynamics and statistical mechanics.