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.
The Bazaar, happening throughout February, 2021, has the theme Data Science for the Social Good.
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.
Assistant professor of plant pathology Claudia Solís-Lemus is a recipient of funding from the Department of Energy to develop statistical theory and tools for computational biology.
Jon Eckhardt, Robert Nowak, and Kevin Ponto were among the recipients of nine mini grants from the American Family Insurance Data Science Institute to advance data science.
WID’s Data Science Hub is part of the COVID-19 Data Science Research Group that is interpreting data, using that data to create models, and sharing information and findings.
Discovery Fellow Jim Luedtke, a professor of industrial and systems engineering at the University of Wisconsin-Madison, specializes in stochastic and integer optimization, a natural fit for power systems.
A new data science project, “WEREWOLF”, puts powerful modeling tools into the hands of Wisconsin policymakers to create the energy systems of tomorrow.
Claudia Solís-Lemus and Daniel Pimentel-Alarcón are experts in statistics and machine learning, augmenting WID’s data science expertise.
WID graduate student Arezoo Movaghar was a collaborator in a study that employed machine learning to mine decades of electronic health records of nearly 20,000 individuals.
Discover Fellow Andreas Velten and collaborators, drawing on the lessons of classical optics, have shown that it is possible to image complex hidden scenes using a projected “virtual camera” to see around barriers.
Researchers at the Wisconsin Institute for Discovery are co-Principal Investigators and co-Investigators on four UW2020: WARF Discovery Initiative projects.
WID researchers used a collaborative combination of computational and wet lab experimental techniques to find a connection between a transcription factor and a neurodevelopment gene.
WID’s new hubs—Data Science, Multi-Omics, and Illuminating Discovery—represent a new path forward for collaborative research projects and fields.
The Wisconsin Institute for Discovery will launch a suite of hubs designed to bring together researchers from across campus and provide access to specialized tools and resources.
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.
By combining information from many farms, predictive models and analytic tools can be developed to help producers and consultants navigate, visualize. and analyze the data they are getting from an increasing number of sources to support better management decisions.
A new approach to climate data analysis hopes to improve regional forecasts.
Ten highly innovative projects have been chosen to receive University of Wisconsin–Madison Data Science Initiative funding, including two led by Wisconsin Institute for Discovery investigators.
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.
Investigators from WID are among the recipients of the latest round of UW2020 awards.
Laurent Lessard is working to improve the algorithms and computer software that keep the modern world running smoothly.
WID researchers are engaging in fundamental mathematical and statistical research to support the development, testing, and fine-tuning of tools for the future, finding new ways to make sense of the mountains of data that are available in the 21st century and bringing into view important applications on the horizon.
The new institute, housed at UW–Madison’s Wisconsin Institute for Discovery (WID), will play a key role in the future of data science, developing fundamental techniques for handling increasingly massive data sets in shorter times.