cse23

AI for Science

Deep learning can help solve problems in areas such as materials design that face the curse of dimensionality.

Designing the Smart Grid of the Future

Ongoing shifts will make the supply of electricity less centralized, less predictable, and more difficult to control.

President’s Column: Musings on SIAM and CSE23

Sven Leyffer reflects on recent happenings in the SIAM community, including CSE23 and trends in student involvement.

Lowering the Entry Barrier to Uncertainty Quantification

The interface UM-Bridge provides a universal link between any uncertainty quantification code and any model software.

Anticipating the 2023 SIAM Conference on Computational Science and Engineering in Amsterdam

CSE23 will facilitate discussions about a variety of large-scale problems in computational science and engineering.

Two-day SIAM Hackathon at CSE23 Explores Critical Problems in Industry

In the first-ever SIAM Hackathon, 150 participants tackled a wide variety of industry-based challenges from six...

Early-career Panel at CSE23 Explores Strategies for Healthy Career Advancement

Panelists shared their personal early-career experiences and offered advice to the forthcoming generation at CSE23.

Automating Conference Scheduling with Genetic Algorithms at CSE23 and Beyond

The scheduling process for a SIAM conference was automated for the first time with a set of C++ and Python codes.

CSE23 Panel Reflects on Key Aspects of Mid-career Development

Panelists gave insights into managing the responsibilities and opportunities of the mid-career stage at CSE23.

Photos from the 2023 SIAM Conference on Computational Science and Engineering

View a selection of photos from the recent 2023 SIAM Conference on Computational Science and Engineering.

Diversity and Retention in the Workforce Take Center Stage at CSE23

A CSE23 panel discussed observations and experiences with mentoring and retention in the context of diversity.

Color Image-driven Deep Autoencoders Predict Atmospheric Pollutant Patterns

Powerful new machine learning algorithms can predict spatial patterns that are influenced by wind-driven dynamics.

Can Mathematics Help Patients with Burn Injuries?

Mathematical models can forecast the expected scenarios for post-burn dermal evolution and help identify treatments.

CNN-based Model Facilitates Classification and Damage Detection After Car Accidents

The auto industry’s rapid growth has intensified the need for efficient car classification and damage...

Stratocumulus Clouds and Predator-prey Dynamics

The use of inverse modeling builds bridges between two very different mathematical models of stratocumulus clouds.

Evaluating the Effectiveness of Mitigation Policies Against Disinformation

Mathematical models tested the effectiveness of various mitigation strategies to combat disinformation in a repeatable way.

Numerical Simulation of Ice Crystal Trajectories and Fragmentation Dynamics Around the XRF1 Fuselage Nose

The development of multiphysics numerical simulation tools to assess ice crystal icing is critical in the...

Breaking Blood Flow with Wires in Aneurysm Coiling Treatment Simulations

Numerical simulations could support coil choice for aneurysm treatment by estimating the outcomes in silico.

Smartwatches Should Facilitate the Aggregation of Mental Health Data

Mobile technologies such as smartwatches can help monitor the real-time health signals of individuals with depression.

The Role of Artificial Intelligence (En)during the COVID-19 Pandemic

Some interesting results have recently emerged in the overlap between artificial intelligence and epidemiology.

Gone with the Wind: Adaptive Mesh Refinement Captures the Turbulent Whirls and Eddies in Aerodynamics

The simultaneous use of multiple solvers and meshes supports a dynamic overset mesh system for wind farm...

Modeling Permafrost: Soil, Ice, and Some Really Hard Mathematics

Efficient computational models for permafrost thaw require accurate mathematical representations of physical processes.

Predicting Biophysical Properties of Proteins

Machine learning models can help discover the useful information that is hidden in protein structural data.

A Computational Framework for the Simulation of Microswimming

The framework for microswimming simulation is based on mathematical models for fluid-structure interactions.

The Same, but Different, but Still the Same: Discovering Differences Between Neutrophil Elastase and Cathepsin G

A workflow compares conformational changes in similar proteins whose amino acid sequences have different lengths.

Dynamics of Droplet Formation and Pinch-off with a One-dimensional Mathematical Model

The droplet formation process is full of physics and mathematics that describe the governing method of droplet...

Rotational Propulsion of Soft Rod-like Robots

Can a rotating magnetic field propel an axisymmetric and fore-aft symmetric robot if it is soft and deformable?

Swimming and Feeding Performance of Choanoflagellates with Captured Prey

The effects of load carrying on the performance of microscopic organisms at low Reynolds numbers are poorly...

Collective Cellular Motion in Tissues

Mathematical models depict angiogenesis and address the motion of epithelial cells on a planar substrate.

Quantifying Tissue Growth, Shape, and Collision in Epithelial Monolayers

Researchers combined data with mathematical modeling and Bayesian inference to examine the dynamics of epithelial...

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