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About the Major

Ancient thinkers recognized mathematics as the language of the natural world. Today we know it drives science and social science, business and industry, even art and design. Math majors at Hamilton explore both the abstract, theoretical aspects of mathematics and its applications to a variety of topics. The curriculum delves into the many branches of math, and courses foster deductive reasoning, persuasive writing, and analytical and quantitative problem-solving. Those who love math will find themselves among like-minded peers and mentors, talking shop outside their professors' offices and producing research that they may present at a professional conference. The department also offers a minor in statistics.

Students Will Learn To:

  • Use mathematical and/or statistical tools to model real-world problems
  • Construct mathematical proofs based on rules of logical inference
  • Communicate complete mathematical and/or statistical arguments

A Sampling of Courses

Math Lounge

Graph Theory

An introduction to the theory and applications of graph theory. Topics include: trees; connectivity; Eulerian and Hamiltonian graphs; vertex-, edge- and map-colorings; digraphs; tournaments; matching theory; planarity and Ramsey numbers.

Explore these select courses:

An introduction to point set topology, a foundational topic for much of modern mathematics. We will cover topological spaces, separation axioms, quotient spaces, compactness, connectedness, path connectedness, and homotopy. In the last part of the course we will cover the fundamental group, the most basic algebraic topological invariant.

An introduction to set-theoretic probability with applications to mathematical statistics. Topics include probability spaces, discrete and continuous random variables, single and multivariate distributions, and limit theorems, leading into the mathematical theory of estimators, sampling distributions, confidence intervals, and hypothesis testing.

This course covers statistical methods in machine learning such as decision trees, random forests and support vector machines The course will use a project-based approach to give students hands-on experience using these techniques by analyzing large and complex real-world datasets. More importantly, they will learn the statistical principles behind these procedures, such as loss functions, maximum likelihood estimation and bias-variance trade-off as well as why these principles matter in real world settings.

Number theory is the study of the properties of the positive integers. Topics include divisibility, congruences, quadratic reciprocity, numerical functions, Diophantine equations, continued fractions, distribution of primes. Applications will include cryptography, the practice of encrypting and decrypting messages, and cryptanalysis, the practice of developing secure encryption and decryption protocols and probing them for possible flaws. Speaking Intensive.

Our world is built of networks: the internet, social networks, transportation networks, communication networks, biological networks. Natural and useful question include "What makes a network robust?" "Can we predict where failures might occur?" "What can we do to slow propagation of viruses along a network?" This courses will cover abstract mathematical properties of networks that can help us answer these questions. These will be examined in the context of both theoretical and real world networks. Further, student groups will analyze and report on a real world network of their choice.

Meet Our Faculty

Sally Cockburn

Chair, the William R. Kenan Jr. Professor of Mathematics

scockbur@hamilton.edu

discrete mathematics, particularly graph theory and combinatorial optimization, with a secondary teaching interest in philosophy of mathematics

Debra Boutin

Samuel F. Pratt Professor of Mathematics

dboutin@hamilton.edu

graph theory, graph symmetries, geometric graph theory, combinatorics

Clark Bowman

Assistant Professor of Mathematics and Statistics

cbowman@hamilton.edu

uncertainty quantification, probabilistic modeling and simulation, mathematical biology, and high-performance computing

Jose Ceniceros

Assistant Professor of Mathematics

jcenicer@hamilton.edu

low dimensional topology; knot theory; Heegaard Floer homology; differential geometry; contact geometry

Andrew Dykstra

Associate Professor of Mathematics

adykstra@hamilton.edu

dynamical systems, symbolic dynamics, and ergodic theory

Courtney Gibbons

Associate Professor of Mathematics

crgibbon@hamilton.edu

commutative algebra, homological algebra, and applied algebra

Robert Kantrowitz

Marjorie and Robert W. McEwen Professor of Mathematics

rkantrow@hamilton.edu

analysis and commutative Banach algebras

Chinthaka Kuruwita

Associate Professor of Statistics

ckuruwit@hamilton.edu

nonparametric density estimation and quantile regression models

Michelle LeMasurier

Associate Professor of Mathematics

mlemasur@hamilton.edu

dynamical systems and topological dynamics

Tural Sadigov

Visiting Assistant Professor of Mathematics and Statistics

tsadigov@hamilton.edu

statistics/probability, partial differential equations, determining forms

Richard Bedient

Professor of Mathematics Emeritus (retired)

rbedient@hamilton.edu

low dimensional topology, knot theory, fractal geometry and chaos theory

Timothy Kelly

Samuel F. Pratt Professor of Mathematics and Statistics Emeritus (retired)

tkelly@hamilton.edu

mathematical education; probability, statistics, stochastic processes and pre-calculus; and probabilistic and statistical reasoning

Larry Knop

Professor of Mathematics and Statistics Emeritus (retired)

lknop@hamilton.edu

statistics, linear algebra, mathematical modeling, computer-augmented learning, and algebra

Robert Redfield

Samuel F. Pratt Professor of Mathematics Emeritus (retired)

rredfiel@hamilton.edu

lattice-ordered fields, rings and groups, vector lattices and ordered topological spaces

Explore Hamilton Stories

Jeremy Gordon ’22

Gordon ’22 to Teach at Shady Hill School, Pursue M.S. Education

After realizing the many possible paths of a math major, Gordon will graduate with a degree in mathematics, and intends to use that degree as he works to become a middle school math teacher.

James Mondi '22

James Mondi ’22 on the Job at Bank of America

James Mondi ’22 graduated in December and is already working as an operations senior analyst at Bank of America in New York City. He shared some advice about the job search and how Hamilton helped prepare him for the position.

Mathletics Team 2021

Putnam Exam No Problem for Mathletics Team

The Putnam is the preeminent math competition for undergraduates in the United States and Canada, and took the form of a six-hour written exam, which the team had trained for throughout the semester.

Careers After Hamilton

Hamilton graduates who majored in mathematics are pursuing careers in a variety of fields, including:

  • Financial Analyst, The New York Times
  • Resident Physician, Westchester Medical Center
  • Business Analyst, Federal Reserve Bank of New York
  • Professor of Industrial Engineering, Northeastern University
  • Software Engineer, Mitre Corp.
  • Legal Analyst, Department of Justice
  • Actuarial Analyst, GEICO
  • Math Teacher, Midlakes High School
  • Infectious Disease Epidemiologist, UNC Gillings School of Global Public Health

Contact

Department Name

Mathematics and Statistics Department

Office Location
198 College Hill Road
Clinton, NY 13323

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