Big data refers to a collection of data sets so large and complex that that they are difficult to process using available database management tools or traditional data processing applications. WID researchers are making transformative contributions to the mathematical and theoretical underpinnings of tools for analyzing massive data sets.
Big data is an important component of WID’s Data Science Hub.
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.
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.
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.
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.
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.
Wisconsin Institute for Discovery (WID) researchers Rupa Sridharan and Sushmita Roy are combining their expertise in regenerative biology and computational biology to better understand how cells transition from one type to another through gene regulation.
Systems Biology researcher Sushmita Roy is leading an effort putting computational methods to work characterizing the gene regulatory networks responsible for cell differentiation.
Discovery fellows Rebecca Willett and Rob Nowak are creating algorithms to make sense of big data and help machines learn.
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.
Kris Saha and colleagues from the BIONATES Theme detail a new approach that can refine gene editing in this month’s issue of Stem Cell Reports.
Patent secured by the Systems Biology Theme members enhances single cell research.
David Page tackles relational databases and algorithms to predict and improve patient health.
