Jon Bentley (computer scientist)

For the British TV presenter, see Jon Bentley (TV presenter).
Jon Bentley
Born Jon Louis Bentley
(1953-02-20) February 20, 1953
Long Beach, California, US
Alma mater University of North Carolina at Chapel Hill
Stanford University
Thesis Divide and conquer algorithms for closest point problems in multidimensional space (1976)
Doctoral advisor Donald Ford Stanat
Doctoral students

Jon Louis Bentley (born February 20, 1953 in Long Beach, California)[1] is an American computer scientist who is credited with the heuristic-based partitioning algorithm k-d tree.

Bentley received a B.S. in mathematical sciences from Stanford University in 1974, and M.S. and Ph.D in 1976 from the University of North Carolina at Chapel Hill; while a student, he also held internships at the Xerox Palo Alto Research Center and Stanford Linear Accelerator Center.[1] After receiving his Ph.D., he joined the faculty at Carnegie Mellon University as an assistant professor of computer science and mathematics.[1] At CMU, his students included Brian Reid, John Ousterhout, Jeff Eppinger, Joshua Bloch, and James Gosling, and he was one of Charles Leiserson's advisors.[2] Later, Bentley moved to Bell Laboratories.

He found an optimal solution for the two dimensional case of Klee's measure problem: given a set of n rectangles, find the area of their union. He and Thomas Ottmann invented the Bentley–Ottmann algorithm, an efficient algorithm for finding all intersecting pairs among a collection of line segments. He wrote the Programming Pearls column for the Communications of the ACM magazine, and later collected the articles into two books of the same name.

Bentley received the Dr. Dobb's Excellence in Programming award in 2004.

Bibliography

References

  1. 1 2 3 Biography from Bentley, J. L.; Ottmann, T. A. (1979), "Algorithms for reporting and counting geometric intersections", IEEE Transactions on Computers, C–28 (9): 643–647, doi:10.1109/TC.1979.1675432.
  2. ↑ Jon Bentley at the Mathematics Genealogy Project

External links

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