Tag: machine learning
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.
Claudia Solís-Lemus
Assistant Professor
My research involves the development of statistical models to answer biological questions.
Kudirat Alimi
My work consists of completing a variety of administrative tasks that promote the VE Lab's projects.
WID Researchers Collaborate on UW2020 Projects
Researchers at the Wisconsin Institute for Discovery are co-Principal Investigators and co-Investigators on four UW2020: WARF Discovery Initiative projects.
Ryan Herringa
Associate Professor
Neurodevelopmental mechanisms of stress and mental illness in youth
Jon Eckhardt
Associate Professor
Entrepreneurship, including firm formation, venture finance, and university driven entrepreneurship
Bryce Sprecher
Acquire, process, interpret, and display spatial data for education, insight, and experience.
WID Seeks Machine Learning and “Fluxomics” Hires
WID seeks to add to its roster of excellent faculty with two new hires in emerging cutting-edge fields.
WID Hubs Launch at Illuminating Connections Event
WID’s new hubs—Data Science, Multi-Omics, and Illuminating Discovery—represent a new path forward for collaborative research projects and fields.
Erika Da-Inn Lee
Developing computational tools to learn the principles of genome organization
Yue Xie
Nonconvex, stochastic, distributed optimization with application in data science
New Technology for Controlling Neural Tissue Manufacturing
A paper published in eLife this week by an interdisciplinary team at WID describes new methods for reproducibly manufacturing brain and spinal cord organoids with strict control over morphogenic and developmental processes.
Using Data Science to Find the Next El Nino
A new approach to climate data analysis hopes to improve regional forecasts.
Air Force-Backed Center to Make Machine Learning More Independent, Predictable, Secure
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.
WID Researchers Looking to the Future with UW2020 Awards
Investigators from WID are among the recipients of the latest round of UW2020 awards.
Applying Control Theory to Algorithm Design Earns Laurent Lessard an NSF CAREER Award
Laurent Lessard is working to improve the algorithms and computer software that keep the modern world running smoothly.
Weaning Crops from Nitrogen Fertilizers: Examining Evolution’s Innovations
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.
App Helps Farmers Make the Most of their Corn Harvest
A new tool developed at UW-Madison could save farmers time and money during the fall feed-corn harvest and make for more content, productive cows year-round.
Scott Sievert
Large scale machine learning, distributed optimization and active learning.
Nowak Research Group
The NRG focuses on signal processing, machine learning, optimization, and statistics. Areas of focus include sparsity and active learning, learning graphs and networks, and interactive machine learning with humans.