Mid-Atlantic Numerical Analysis Day
A conference on numerical analysis and scientific computing for graduate students and postdocs in the Mid-Atlantic region.
The Conference
This one-day meeting will start at 10am to allow same-day travel.
It will be held in Room 617 Wachman Hall, Temple University, 1805 North Broad Street, just north of Montgomery Avenue.
It is an opportunity for graduate students and postdocs to present their research, and to meet other researchers.
There will be contributed talks and a poster session.
There is no registration fee, and no support for travel. Lunch will be provided.
We ask every participant to please register in advance, even if they are not planning to give a talk.
Keynote SpeakerMayya Tokman, University of California, Merced Why, What and How of Exponential IntegrationSimulating dynamics of a complex system evolving over a wide range of temporal and spatial scales is one of the most common tasks in scientific computing, and a problem that is encountered across science and engineering. To accomplish this task a system of coupled nonlinear differential equations has to be solved over long periods of time. For centuries this problem was addressed through development of different quadrature rules for integrals of functions, which led to construction of explicit and implicit time integration methods of different types. But in 1960’s a different approach of computing the solution of the system directly was proposed. Coupled with advances in numerical linear algebra in 1980’s, this approach led to development of practical exponential integration methods that offer significant computational advantages for a number of important problems. In this talk, we will discuss why exponential integration is an attractive way to solve the so-called stiff systems of equations. We will explain what considerations must be taken into account to construct an efficient exponential time integrator and what classes of exponential methods exist. We will also demonstrate how such methods perform in real-world applications drawing from such fields as computer graphics, plasma physics, climate and weather predictions. |
Registration and/or Abstract Submission
If you would like to participate (in any form), please register using the online registration form.
Deadline for the submission of talks: October 17, 2025.
Conference Poster and Booklet
Conference Poster
| Conference Booklet |
Schedule
9:15-9:50 | Registration and breakfast (provided) |
9:50-10:00 | Opening remarks |
10:00-11:00 | Presentations (Time-Stepping) |
11:00-11:20 | Coffee Break |
11:20-12:20 | Presentations (Low-Rank Methods) |
12:20-1:30 | Lunch (provided) |
1:30-2:30 | Keynote lecture (Mayya Tokman) |
2:30-3:00 | Coffee break |
3:00-4:00 | Presentations (Applications and CFD) |
4:00-4:20 | Coffee break |
4:20-5:00 | Presentations (Machine Learning) |
5:00-5:10 | Closing remarks |
6:00-8:00 | Group dinner (attendance optional) |
Speakers
Time-Stepping | |||
|---|---|---|---|
Sylvia | Amihere | University of Maryland, Baltimore County | Embedded Implicit-Explicit Strong Stability Preserving Runge-Kutta Methods |
Isaac Anthony | Castro | University of Delaware | Low-Rank Fully-Implicit Runge-Kutta Method for Linear PDEs |
Yifan | Hu | University of Maryland, Baltimore County | Adaptive-Step Time Integration for Gyrokinetic Equation with GENE-X |
Low-Rank Methods | |||
Jackie | Lok | Princeton University | Sketch-and-Project Solvers for Linear Systems with Low-Rank Structure |
Mikhail | Lepilov | Rensselaer Polytechnic Institute | Kernel Approximation Using the Proxy Point Method via Contour Integration |
Shambhavi | Suryanarayanan | Princeton University | On Trimming Tensor-Structured Measurements and Efficient Low-Rank Tensor Recovery |
Applications and CFD | |||
Ahmet Kaan | Aydin | University of Maryland, Baltimore County | Low-Rank All-at-Once Stochastic Galerkin Solvers for Incompressible Flows |
Arnab | Roy | University of Delaware | Inverse Modeling of Tear-Film Thinning: From ODE Dynamics to Neural Networks |
Alex | Sheranko | University of Maryland, Baltimore County | A Kernel Based SIR Model for Infectious Spread in Space and Time |
Machine Learning | |||
Noah | Amsel | New York University | The Polar Express: Optimal Matrix Sign Methods and Their Application to the Muon Algorithm |
Leonardo | Ferreira Guilhoto | University of Pennsylvania | Kolmogorov Superposition Meets Physics-Informed Neural Networks: A New Architecture for Scientific Machine Learning |
Each contributed talk will be 15 minutes, plus 5 minutes for discussion and switching speakers.
Accommodation
Make your own arrangements. Please feel free to contact us for information on accommodation.
Contact
Email: naday -at- temple.edu
Location
Organizers
Benjamin Seibold and Daniel B. Szyld
Sponsors
Sponsored and supported by the Department of Mathematics, the College of Science and Technology, the Graduate School, the Center for Computational Mathematics and Modeling, Temple University, and the Simons Foundation.
