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.
Zhaoyi Zhang
Use machine learning model to predict the antibiotic resistance of certain bacteria
Oscar Zhang
Automated API toolkit for data ingestion from dairy farms to aggregated database for data analytics
Kushin Mukherjee
Modeling how we learn and represent visual concepts and use them to perform visual tasks
Nam Ho-Nguyen
Optimization under uncertainty, data-driven optimization, machine learning, statistics
New Faculty Bring New Possibilities to WID, UW
Claudia Solís-Lemus and Daniel Pimentel-Alarcón are experts in statistics and machine learning, augmenting WID’s data science expertise.
Electronic Records Pin Broad Set of Health Risks on Genetic Premutation
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.
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.
Noah Stafford
Exploring multitask learning algorithms for single cell network inference
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
Jordan Nunez
Expedite process of transferring large power grid files using python web apps
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.
Bochao Li
Using data visualization tool HiGlass and matrix factorization to process biomedical data
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.