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Fox, Jeffrey S

Professor

Positions

Research Areas research areas

Research

research overview

  • My research is focused on computer simulation of signalling in neurons. I also work on representation theory for locally compact groups.

keywords

  • group representations, non-commutative geometry, computational neuroscience

Publications

selected publications

Teaching

courses taught

  • APPM 4650 - Intermediate Numerical Analysis 1
    Primary Instructor - Spring 2018 / Spring 2020
    Focuses on numerical solution of nonlinear equations, interpolation, methods in numerical integration, numerical solution of linear systems, and matrix eigenvalue problems. Stresses significant computer applications and software. Department enforced prerequisite: knowledge of a programming language. Same as MATH 4650.
  • MATH 2130 - Introduction to Linear Algebra for Non-Mathematics Majors
    Primary Instructor - Fall 2018 / Spring 2019 / Fall 2019 / Spring 2020 / Fall 2020 / Spring 2021 / Spring 2022 / Fall 2022 / Spring 2023
    Examines basic properties of systems of linear equations, vector spaces, inner products, linear independence, dimension, linear transformations, matrices, determinants, eigenvalues, eigenvectors and diagonalization. Intended for students who do not plan to major in Mathematics. Degree credit not granted for this course and MATH 2135 or APPM 3310. Formerly MATH 3130.
  • MATH 3001 - Analysis 1
    Primary Instructor - Fall 2018
    Provides a rigorous treatment of the basic results from elementary Calculus. Topics include the topology of the real line, sequences of numbers, continuous functions, differentiable functions and the Riemann integral.
  • MATH 3210 - Euclidean and Non-Euclidean Geometry
    Primary Instructor - Spring 2018
    Axiomatic systems; Euclid's presentation of the elements of geometry; Hilbert's axioms; neutral, Euclidean and non-Euclidean geometries and their models.
  • MATH 3430 - Ordinary Differential Equations
    Primary Instructor - Spring 2021
    Involves an elementary systematic introduction to first-order scalar differential equations, nth order linear differential equations, and n-dimensional linear systems of first-order differential equations. Additional topics are chosen from equations with regular singular points, Laplace transforms, phase plane techniques, basic existence and uniqueness and numerical solutions. Formerly MATH 4430.
  • MATH 3510 - Introduction to Probability and Statistics
    Primary Instructor - Fall 2021
    Introduces the basic notions of Probability: random variables, expectation, conditioning, and the standard distributions (Binomial, Poisson, Exponential, Normal). This course also covers the Law of Large Numbers and Central Limit Theorem as they apply to statistical questions: sampling from a random distribution, estimation, and hypothesis testing. Credit not granted for this course and MATH 2510 or MATH 4510.
  • MATH 4510 - Introduction to Probability Theory
    Primary Instructor - Spring 2023
    Studies axioms, combinatorial analysis, independence and conditional probability, discrete and absolutely continuous distributions, expectation and distribution of functions of random variables, laws of large numbers, central limit theorems, and simple Markov chains if time permits. Degree credit not granted for this course and APPM 3570 or ECEN 3810 or MATH 3510. Same as MATH 5510.
  • MATH 4650 - Intermediate Numerical Analysis 1
    Primary Instructor - Spring 2018 / Spring 2020
    Focuses on numerical solution of nonlinear equations, interpolation, methods in numerical integration, numerical solution of linear systems, and matrix eigenvalue problems. Stresses significant computer applications and software. Department enforced restriction: knowledge of a programming language. Same as APPM 4650.
  • MATH 5510 - Introduction to Probability Theory
    Primary Instructor - Spring 2023
    Studies axioms, combinatorial analysis, independence and conditional probability, discrete and absolutely continuous distributions, expectation and distribution of functions of random variables, laws of large numbers, central limit theorems, and simple Markov chains if time permits. Same as MATH 4510.

Background

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