Randall Dougherty
Randall Dougherty | |
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Randall Dougherty taking a swim 2009 | |
Born | 1961 (age 54–55) |
Nationality | American |
Fields | Mathematics |
Institutions | Ohio State University |
Alma mater | University of California, Berkeley |
Doctoral advisor | Jack Silver |
Randall Dougherty (born 1961) is an American mathematician. Dougherty has made contributions in widely varying areas of mathematics, including set theory, logic, real analysis, discrete mathematics, computational geometry, information theory and coding theory.[1]
Dougherty is a three-time winner of the U.S.A. Mathematical Olympiad, 1976, 1977, 1978 and a three-time medalist in the International Mathematical Olympiad.[2] He is also a three-time Putnam Fellow 1978, 1979, 1980.[3] Dougherty earned his Ph.D. in 1985 at University of California, Berkeley under the direction of Jack Silver.[4]
With Matthew Foreman he showed that the Banach-Tarski decomposition is possible with pieces with the Baire property, solving a problem of Marczewski that remained unsolved for more than 60 years.[5] With Chris Freiling and Ken Zeger, he showed that linear codes are insufficient to gain the full advantages of network coding.[6]
Selected publications
- Dougherty, Randall and Matthew Foreman (1994). "Banach-Tarski decompositions using sets with the property of Baire". Journal of the American Mathematical Society (American Mathematical Society) 7 (1): 75–124. doi:10.2307/2152721. JSTOR 2152721.
- Randall Dougherty, Chris Freiling, and Ken Zeger (2005). "Insufficiency of linear coding in network information flow". IEEE Transactions on Information Theory 51 (8): 2745–2759. doi:10.1109/tit.2005.851744.
References
- ↑ "Universität Trier: DBLP Bibliography Server"
- ↑ Randall Dougherty's results at the International Mathematical Olympiad
- ↑ "The Mathematical Association of America's William Lowell Putnam Competition"
- ↑
- ↑ "The Ohio State University Department of Mathematics--Alumni News"
- ↑ Dougherty, Freiling, and Zeger. Insufficiency of Linear Coding in Network Information Flow. and
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