Randall Dougherty

Randall Dougherty
Randall Dougherty taking a swim 2009
Born 1961 (age 5657)
Nationality American
Alma mater University of California, Berkeley
Scientific career
Fields Mathematics
Institutions Ohio State University
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 & 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

  1. "Universität Trier: DBLP Bibliography Server"
  2. "Randall Dougherty's results". International Mathematical Olympiad.
  3. "The Mathematical Association of America's William Lowell Putnam Competition"
  4. "The Ohio State University Department of Mathematics--Alumni News"
  5. Dougherty, Freiling, and Zeger. Insufficiency of Linear Coding in Network Information Flow. and


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