Chris Leary has been a member of the Geneseo faculty since 1992.
Office Hours: Spring 2019
- M: 10:00a - 11:00a
- Tu: 11:00a - 12:00p
- W: 1:30p -2:30p
- F: 11:00a - 12:00p
- or by appointment
B.A., Oberlin College; 1979
Ph.D., University of Michigan; 1985
SUNY Geneseo 1992-current
United States Agency for International Development (2017-2018)
Eberhard Karls Universität Tübingen, Germany (2005–2006)
The University of Calgary (1998)
Stetson University (1991-1992)
Oberlin College (1985-1991)
A Friendly Introduction to Mathematical Logic (2nd Edition) (with Lars Kristiansen), (2015), Milne Library, Geneseo NY. Available at http://minerva.geneseo.edu/a-friendly-introduction-to-mathematical-logi…
Fractals, average distance, and the Cantor set (with Dennis Ruppe and Gregg Hartvigsen), Fractals, vol. 18, no. 3 (2010), pp. 327-341.
Component averages in subgraphs of circulant-like graphs (with Jaqueline M. Dresch, Niels C. Hansen, Gregg Hartvigsen and Anthony J. Macula), Bulletin of the Institute for Combinatorics and its Application, vol. 51 (2007), pp. 55-68.
Tuning Degree Distributions: Departing from scale-free networks (with Hans-Peter Duerr, Markus Schwehm and Martin Eichner), Physica A: Statistical Mechanics and its Applications, vol. 382 (2007), pp. 731?738.
The impact of contact structure on infectious disease control: influenza and antiviral agents. (with Hans-Peter Duerr, Markus Schwehm, SJ DeVlas and Martin Eichner), Epidemiology and Infection, vol. 135, no. 07, (2007), pp.1124-1132.
Network structure, population size, and vaccination strategy and effort interact to affect the dynamics of influenza epidemics (with Gregg Hartvigsen, Jacqueline Dresch, Amy Zielinski, and Anthony Macula), The Journal of Theoretical Biology, vol. 246 (2007), pp. 205?215.
High infection rates at low transmission potentials in West African onchocerciasis (with Hans-Peter Duerr and Martin Eichner), International Journal for Parasitology, vol. 36, no. 13 (2006), pp. 1367-1372.
Filter games on omega and the dual ideal (with Claude Laflamme), Fundamenta Mathematicae, vol. 173, no. 2 (2002), pp. 159?173.
The structure of pleasant ideals. Notre Dame Journal of Formal Logic. 1994;35(2):292-98.
Pleasant ideals. Notre Dame Journal of Formal Logic. 1991;32(4):612-17.
Patching ideal families on P-kappa-lambda. Archive for Mathematical Logic. 1990;30(4):269-75.
Patching ideal families and enforcing reflection. J. Symbolic Logic. 1989; 54: 26–37.
Latin square achievement games (with Frank Harary). J. Recreational Mathematics. 1983-1984; 16(4): 241–246.
My research training was in the areas of set theory and logic. In particular, I have published papers dealing with infinitary combinatorics and large cardinals. More recently I have become interested in modeling and applications of mathematics to biology. I have also been fortunate enough to work with members of the Institut für Medizinische Biometrie at the University of Tübingen.
MATH 160: Media Statistics
This course will help students learn how to think about statistics and probability, how to identify the tools needed to study a particular problem and how to read and critically evaluate quantitative information presented in the media. The course format involves extensive reading and discussion of newspaper and journal articles, computer activities, writing assignments, and student projects.
MATH 222: Calculus II
Topics studied are methods of integration, applications of definite integrals, sequences, improper integrals, and series, parametric equations and polar coordinates.
MATH 237: R/Intro Discrete Mathematics
This course covers the basic tools of mathematics and computer science - logic, proof techniques, set theory, functions, inductive processes, counting techniques - with applications to such areas as formal languages, circuit theory and graph theory.
MATH 262: R/Applied Statistics
An introduction to statistics with emphasis on applications. Topics include the description of data with numerical summaries and graphs, the production of data through sampling and experimental design, techniques of making inferences from data such as confidence intervals and hypothesis tests for both categorical and quantitative data. The course includes an introduction to computer analysis of data with a statistical computing package.