Data Science Fellow Steven Brunton and colleagues recently published a paper in PNAS applying machine learning to dynamical systems and control in engineering. This work involves a novel approach to discovering governing equations from data.
Video abstract: https://www.youtube.com/watch?v=gSCa78TIldg
Paper : http://www.pnas.org/content/113/15/3932.abstract
Eli Shlizerman, Data Science Fellow and Assistant Professor in Applied Mathematics and Electrical Engineering, and his biologist colleagues published a model for a sun compass used by monarch butterflies for navigation during their annual migration. Modeling data from butterfly neurons in the attennae and eyes, they identified that input cues from the Sun alone can […]
Anthony Arendt, eScience Institute Data Science Fellow and Applied Physics Laboratory Senior Research Scientist, contributed an American Geophysical Union blog post about two Earth sciences projects that were part of the recently completed 2016 Winter Data Science Incubator. He notes that this program provides a novel approach to addressing the urgent challenge of offering education […]
USA Today quoted eScience Associate Director Bill Howe in an April 5th article about the 11.5 million documents recently leaked from a Panamanian law firm pertaining to hidden offshore accounts and business transactions. Howe notes that cloud computing as well as openly available software for translation, indexing, and data mining now make quick work of […]
Brittany Fiore-Gartland and Anissa Tanweer
Data science has many characterizations, but in academia it is often talked about as pushing the limits of both methodological and domain science, what Josh Bloom, a Professor of Astronomy at U.C. Berkeley, has referred to as “novelty squared”. Bloom sees this as the “great challenge of modern interdisciplinary scientific collaboration”. […]