Modeling is the process of developing and testing mathematical representations of processes or events.
Modeling is foundational to much of the work done at WID, from modeling evolutionary and biological systems to power grids and fish habitats. Researchers at WID work on the fundamental algorithms and formulations that allow them to build the best and most useful models to solve difficult problems.
Modeling is a key tool for WID’s Data Science Hub.
Systems Biology researchers Deborah Chasman and Sushmita Roy are using machine learning to identify virus and pathogenicity-specific regulatory networks which may guide the design of effective therapeutics for infectious diseases. The work is described in a recent paper in PLOS Computational Biology.
Professor Thomas Rutherford, WID Optimization, and colleagues used numerical models to examine whether the threat of carbon tariffs might lower the cost of reductions in world carbon emissions in a paper published in the February issue of the American Economic Journal: Economic Policy.
UW-Madison and WID are on the front lines of the applied algebra movement, changing the way scientists in a wide range of disciplines solve problems.
David Page tackles relational databases and algorithms to predict and improve patient health.
Published today in Stem Cell Reports, researchers led by Randolph Ashton and Ethan Lippmann present a unifying protocol to create neural stem cells from diverse regions of the hindbrain and spinal cord.
WID Optimization teams with local wildlife agencies to improve Great Lakes basin habitat.
What if a computer program could take a problem you’re trying to solve and send back the most efficient solution?
Harvesting data and harvesting crops? There’s an app for that.
