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Data-driven models and machine learning for the physical sciences

Date:  Thursday, May 23rd, 2019

Time: 4:00pm

Location:100 Willamette Hall

Speaker: David Hogg, New York University and Flatiron Institute

Abstract: There is immense hype, and immense promise, in machine learning for physics and astronomy. I use the case of stellar astrophysics as an example area in which to explore these ideas, but my points will be general and apply to any physics area where there are substantial data sets and good but not perfect physical models. When the information in the data is good enough to consistently rule out (in a statistical goodness-of-fit


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Raymer receives the Innovation and Impact Award

The innovation and impact award will be presented to Michael Raymer, a professor in the Department of Physics. The award is given to an outstanding individual or team that distinguished themselves and the university through entrepreneurial activities that resulted in innovations with a measurable societal or environmental benefits.

Raymer was chosen for his scientific leadership and lobbying efforts on behalf of the National Quantum Initiative Act, a $1.2 billion initiative that promises to revolutionize everything from computing to navigation to encryption. Raymer traveled to Washington, D.C.