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Susan Paddock

From Wikipedia, the free encyclopedia

Susan Mary Paddock is an American statistician whose publications have included work on nonparametric Bayesian inference,[1][2] substance abuse,[2] and the safety of autonomous vehicles.[3]

Paddock is a graduate of the University of Minnesota and has a Ph.D. from Duke University.[4] Her 1999 doctoral dissertation, Randomized Polya Trees: Bayesian Nonparametrics for Multivariate Data Analysis, was supervised by Mike West.[1] Formerly head of the RAND Statistics Group at the RAND Corporation, she moved to NORC at the University of Chicago in 2019 as chief statistician and executive vice president.[2]

She was named a Fellow of the American Statistical Association in 2013,[5] and in the same year won the Mid-Career Achievement Award of the American Statistical Association's Health Policy Statistics Section.[6] She was the 2019 chair of the association's Section on Bayesian Statistical Science.[7]

References

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  1. ^ a b Susan Paddock at the Mathematics Genealogy Project
  2. ^ a b c "Susan Paddock Named Executive Vice President and Chief Statistician of NORC at the University of Chicago", Press Release, NORC at the University of Chicago, retrieved 2021-05-18
  3. ^ Mangan, Dan (12 April 2016), Fool's errand? Testing the safety of self-driving cars, CNBC
  4. ^ "Susan Paddock", Experts, NORC at the University of Chicago, retrieved 2021-05-18
  5. ^ ASA Fellows list, American Statistical Association, retrieved 2021-05-18
  6. ^ Health Policy Statistics Section Achievement Awards, American Statistical Association, retrieved 2021-05-18
  7. ^ "Current Officers", Section on Bayesian Statistical Science, American Statistical Association, retrieved 2021-05-18
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