Mathematical modeling is the process of developing mathematical descriptions, or models, of real-world systems. These models can be linear or nonlinear, discrete or continuous, deterministic or ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

Tech-enabled SaaS growth companies are among the most progressive companies when it comes to making use of data science. In a global survey conducted by McKinsey Analytics in 2020, only 16% of ...

The Computational Science and Modeling (CSM) Laboratory is an interdisciplinary facility designed to support student-learning by enabling the integration of computation in research and teaching at ...

While machine learning (ML) weather models are emerging as promising tools for predicting weather conditions on a global scale, their coarse resolution and systematic biases limit practical ...

Science is about to become much more exciting—and that will affect us all, argues Google's former CEO. It’s yet another summer of extreme weather, with unprecedented heat waves, wildfires, and floods ...

EPA develops software models and tools to address a range of environmental issues. These developments have exploded with the advent of technology since the turn of the century. The Community ...

There's been a seismic shift in science, with scientists developing new AI tools and applying AI to just about any question that can be asked. Researchers are now putting actual seismic waves to work, ...

Atmospheric modeling is used by air quality managers to make decisions on effective and efficient ways to implement the National Ambient Air Quality Standards (NAAQS) and improve air quality. EPA has ...