Tag: software
Software tools are a critical component or product of many WID projects and initiatives, especially within WID’s Data Science Hub.
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 Researchers Showcase “Virtual Diary Farm Brain” at American Dairy Science Association Meeting
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.
Sarah Stevens
Data Science Hub Facilitator
Facilitating connections and training researchers in data science.
Brian Yandell
Professor
Co-lead of Data Science Hub (datascience.wisc.edu). Research on systems genetics.
WID Researchers Looking to the Future with UW2020 Awards
Investigators from WID are among the recipients of the latest round of UW2020 awards.
Alec Archambault
Preparing the hololens for presentations and diving deeper into learning about the technology
Building Better Tools for the Big Data Boom
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.
Arthur Malulley Bovolim de Oliveira
VR educational application in the form of an arcade game to teach kids a bit about polar research
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.
Felipe Gutierrez Barragan
Computational Imaging, Illumination, and Optics • Computer Vision • Time of Flight Imaging
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.
Arezoo Movaghar
Develop computational models to improve our understanding of neurodevelopmental disorders
Sizhuo Ma
Reconsider motion-related computer vision problems from the perspective of camera design.
Laurence Loewe
Assistant Professor
Developing a stable, user-friendly programming language compiler for reproducible biodata analyses and general modeling in biology while building in-depth models for bioresearch
Adam Christensen
Assistant Scientist
Building optimization models that help untangle issues of environmental sustainability.
Lauren Michael
Research Computing Facilitator, Center for High Throughput Computing
Facilitating compute-driven transformations to research projects via personalized consulting.
Christina Koch
Research Computing Facilitator
Facilitating transformative science through computing.