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Contact: hilltp66@charter.net or hill@math.gatech.edu

Academic CV


Benford's LawResearch Area I - The Significant Digit Phenomenon or Benford's Law

A century-old empirical observation now called Benford's Law says that the significant digits of many real datasets are logarithmically distributed, rather than uniformly distributed, as might be expected. This research includes discoveries that help explain the ubiquity of Benford data sets. For example, it has now been shown that iterations of many common functions (including all polynomials, power, exponential, and trigonometric functions, as well as compositions thereof), dynamical systems and differential equations, geometric Brownian motion (hence most stock market models), mixtures of data from different sources, and Newton's method, all produce Benford sequences. These publications also include applications to fraud detection and to diagnostic tests for mathematical models, many examples, and open Benford-related problems in dynamical systems, probability, number theory, and differential equations. For American Scientist article on this topic, click here.

For a free searchable online bibliographic database on Benford's Law, see www.benfordonline.net.

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Deciding when to stopResearch Area II - Optimal Stopping Theory and Secretary Problems

In many basic processes in science (and in life), there is an element of chance involved, and a crucial problem is deciding when to stop. The process could be debugging large software programs, proofreading a paper, waiting to buy Google stocks, performing medical experiments, looking at houses to buy, gathering laboratory data, or interviewing for a new secretary (or spouse). The typical framework is that a sequence of random variables is being observed, and the objective is to decide when to stop in order to maximize the expected reward. These publications include basic "prophet inequalities" ( comparisons of the expected return of a gambler who has foresight, or inside information, with a gambler who does not' game-theoretic extensions to the classical secretary problem, and determiation of optimal rules and optimal bounds for generalized stopping. For American Scientist article on this topic, click here.

For the French version in Pour la Science, click here.


Fair Division Research Area III - Fair Division Problems

The general subject of this research is the question of whether an object (such as a cake or piece of land) can be divided among a number of people so that each receives a portion he considers a fair share, according to his own values. (Formally, there are n measures on the same object - a measurable space - and a typical goal is to find a partition of the object into n pieces so that the minimum value of the i-th measure on the i-th piece is as large as possible). These publications include generalizations of Steinhaus'classical "Ham Sandwich Problem", Neyman and Pearson's "Bisection Problem", and Fisher's "Problem of the Nile", determination of optimal bounds and extreme-case measures, generalizations of Lyapounov's Convexity Theorem, and applications to disarmament, dividing inheritances, and lotterized allocations of indivisible goods. For American Scientist article on this topic, click here.


Le Grand K

 

"Weird" Science and Mathematical Miscellany

Is the fundamental physical constant called  "Avogadro's number" odd or even? For American Scientist article on this topic, click here.

Is there a natural and purely mathematical definition of the kilogram? For article on this topic, click here.

How can data from completely different experiments best be consolidated? For articles on this topic, click here and here.

Dividing a ham sandwich fairly

Can the classical Ham Sandwich Theorem of Steinhaus be strengthened to conclude that the knife will also spread mayonnaise on each ingredient? For article on this topic, click here.

Raising questions like these is part of my current "recreational" scientific research, and has led to new collaborations, publications and a "Weird Science" award.


Letters to the Editor


Scientific Collaborators

  • Jon Aaronson, University of Tel Aviv, Israel
  • Arno Berger, University of Alberta, Canada
  • Lisa Bloomer, Middle Tennessee State University
  • Frans Boshuizen, Vrije U. Amsterdam; SNS REALL, Netherlands
  • Leonid Bunimovich, Georgia Institute of Technology
  • Robert Burton, University of Oregon
  • Albert C. Censullo, California Polytechnic State U., San Luis Obispo
  • Marco Dall’Aglio, LUISS Guido Carli University, Italy
  • Herold Dehling, Ruhr-Universität Bochum, Germany
  • Stephen Demko, Georgia Institute of Technology
  • John Elton, Georgia Institute of Technology
  • Robert Foley, Georgia Institute of Technology
  • Ronald Fox, Georgia Institute of Technology
  • Jeffrey Geronimo, Georgia Institute of Technology
  • David Gilat, University of Tel Aviv, Israel
  • Arie Hordijk, Leiden University, Netherlands
  • Bahar Kaynar, Vrije Universiteit Amsterdam, Netherlands
  • Douglas Kennedy, Cambridge University, U.K.
  • Robert Kertz, Georgia Institute of Technology
  • Ulrich Krengel, University of Göttingen, Germany
  • James Mann
  • Jack Miller, Lawrence Berkeley National Laboratory
  • Michael Monticino, University of North Texas
  • Kent Morrison, California Polytechnic State U., San Luis Obispo
  • Victor Perez-Abreu, Centro de Investigación en Matemáticas, Mexico
  • Victor Pestien, University of Miami
  • Ad Ridder, Vrije Universiteit Amsterdam, Netherlands
  • Klaus Schuerger, University of Bonn, Germany
  • David Sitton, Planning Systems Inc.
  • Carl Spruill, Georgia Institute of Technology
  • Yung Tong, Georgia Institute of Technology
  • Jan Van der Wal, University of Amsterdam, Netherlands
  • Benjamin Weiss, Hebrew University, Israel