Yuzhuo Kang
Infer the ancestral sequences and states of the animal and plant virus sequences using various model
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.
Data Science Research Bazaar Seeks Proposals
The Bazaar, happening throughout February, 2021, has the theme Data Science for the Social Good.
Joe Holt
Assist research software development, implementing a distributed variable batch size optimization
Jakob Coles
Active learning in deep neural networks; theoretical aspects of deep learning
UW–Madison to Continue Fundamental Data Science Research with Phase II Award from NSF
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.
WID Researchers Among Data Science Institute Mini Grant Recipients
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.
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
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.
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.