Rebecca Willett is an American statistician and computer scientist whose research involves machine learning, signal processing, and data science. She is a professor of statistics and computer science at the University of Chicago.[1]
Willett has a Ph.D. in electrical and computer engineering from Rice University, completed in 2005. She worked as a faculty member in electrical and computer engineering at Duke University from 2005 until 2013, when she moved to the University of Wisconsin–Madison.[1] She moved again to the University of Chicago in 2018.[2]
Her research has included machine learning methods for the analysis of corn crop quality,[3] and weather patterns.[4] She was named a SIAM Fellow in the 2021 class of fellows, "for contributions to mathematical foundations of machine learning, large-scale data science, and computational imaging",[5] and an IEEE Fellow in 2022 "for contributions to the foundations of computational imaging and large-scale data science".[6] In 2022, she was elected Vice Chair of the Society for Industrial and Applied Mathematics Activity Group on Imaging Science (SIAM SIAG/IS).[7]
References
edit- ^ a b Profile: Rebecca Willett, University of Chicago Computer Science Department
- ^ DSP Alum Rebecca Willett Joins University of Chicago, Digital Signal Processing at Rice University, June 25, 2018
- ^ "New Silage App Designed to Improve Corn Silage Quality", Dairy Herd Management, June 1, 2018
- ^ Mitchum, Rob (September 11, 2018), "Multi-university collaboration will use climate data analysis to improve regional forecasts", UChicago News
- ^ "SIAM Announces Class of 2021 Fellows", SIAM News, Society for Industrial and Applied Mathematics, March 31, 2021, retrieved 2021-04-03
- ^ 2022 newly elevated fellows (PDF), IEEE, archived from the original (PDF) on November 24, 2021, retrieved 2022-03-02
- ^ "SIAM Activity Groups Election Results". SIAM News. Retrieved 2022-05-28.
External links
edit- Home page
- Rebecca Willett publications indexed by Google Scholar