Machine learning uses algorithms to build analytical models, helping computers “learn” from data. It can now be applied to huge quantities of data to create exciting new applications. Researchers at WID are developing new methodology and theory for extracting useful information from data which may be noisy or high-dimensional, contain missing elements, or come from a variety of different sensors or streaming input.

Machine learning at WID plays a key role in problems as diverse as understanding the immune system, finding the funniest cartoon captions, and developing driverless cars.

Machine learning is an important component of WID’s Data Science Hub.

A New Computational Tool Maps Genome Change, Helping Researchers See DNA in 3D

2025-08-26T08:58:31-05:00

How do genomes fit into the tiny confines of a cell nucleus? Genomes can be massive and making it more difficult, is that the genome may be repackaged across different biological dimensions and contexts such as cell types, developmental stages, disease states or points in time. Furthermore, it is not well understood which pieces of the genome control gene expression. Intrigued by this puzzle, researchers Sushmita Roy and recently graduated student, Da-Inn Lee introduce a powerful new computational tool in their latest study that could help systematically examine how DNA is arranged and how it changes across different dimensions.

A New Computational Tool Maps Genome Change, Helping Researchers See DNA in 3D2025-08-26T08:58:31-05:00

Professor Stephen Wright Announced Winner of the Test of Time Award at 2020 NeurIPS Conference

2024-11-14T21:55:17-06:00

Professor of Computer Sciences at WID Stephen Wright and three colleagues were announced winners of the prestigious Test of Time Award at the 2020 Conference on Neural Information Processing Systems.

Professor Stephen Wright Announced Winner of the Test of Time Award at 2020 NeurIPS Conference2024-11-14T21:55:17-06:00

UW–Madison to Continue Fundamental Data Science Research with Phase II Award from NSF

2025-01-27T14:42:03-06:00

The Wisconsin Institute for Discovery is home to the Institute for the Foundations of Data Science, which has received Phase II funding from the National Science Foundation.

UW–Madison to Continue Fundamental Data Science Research with Phase II Award from NSF2025-01-27T14:42:03-06:00

Air Force-Backed Center to Make Machine Learning More Independent, Predictable, Secure

2025-01-27T14:34:44-06:00

Much remains mysterious in the realm of machine learning. The next generation of machine learning algorithms is expected to not only bolster national defense capabilities, but also benefit civilians.

Air Force-Backed Center to Make Machine Learning More Independent, Predictable, Secure2025-01-27T14:34:44-06:00

Weaning Crops from Nitrogen Fertilizers: Examining Evolution’s Innovations

2024-11-14T22:15:51-06:00

WID researcher Sushmita Roy and collaborators at UW­–Madison and the University of Florida will use a $7 million grant from the U.S. Department of Energy to study how some plants partner with bacteria to create usable nitrogen and to transfer this ability to the bioenergy crop poplar.

Weaning Crops from Nitrogen Fertilizers: Examining Evolution’s Innovations2024-11-14T22:15:51-06:00

Machine Learning Can Detect a Genetic Disorder from Speech Recordings

2024-11-14T22:17:35-06:00

Machine learning is a form of artificial intelligence by which algorithms are "trained" to analyze new information using existing data. Researchers are using it to identify individuals with a genetic condition known as fragile X premutation.

Machine Learning Can Detect a Genetic Disorder from Speech Recordings2024-11-14T22:17:35-06:00

You may also like … Algorithms that improve drug discovery

2024-11-14T22:18:24-06:00

WID researchers Stephen Wright and Robert Nowak are part of a UW2020: WARF Discovery Initiative project to create machine learning tools that dramatically reduce the time and cost associated with screening compounds for therapeutic relevance.

You may also like … Algorithms that improve drug discovery2024-11-14T22:18:24-06:00

Understanding the Immune System with Machine Learning

2025-01-27T14:12:32-06:00

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.

Understanding the Immune System with Machine Learning2025-01-27T14:12:32-06:00
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