Graduate Reading Courses

In-depth, specialized learning opportunities for graduate students.

Specialized reading courses supplement our regular graduate course offerings, allowing you to go even deeper on a particular topic. Faculty members can offer reading courses on virtually any topic in the world of math—ranging from Historiography of Mathematics to Mathematical Models of Whole Genomes Analysis. These fascinating options change from term to term.

To enroll in a Reading Course, complete the Course Add/Drop Form, obtain the instructor's signature, and return form to the Graduate Program Assistant.

Reading Course Offerings Summer 2019

MATH 894-2 - Representing Graphs with Semidefinite Programming (course outline coming soon!)

Previous Reading Course Offerings

2018 Reading Courses

  • Applications of Convex Optimization in Machine Learning, Zhaosong Lu
  • Compressed Sensing, Structure and Imaging, Ben Adcock
  • Machine Learning, Paul Tupper
  • Historiography of Modern Mathematics, Tom Archibald
  • Sheaves and Cohomology in Algebraic Geometry, Nathan Ilten

2017 Reading Courses

  • Represetation Theory of Lie Groups and Algebras, Nathan Ilten
  • Summer School in Probabiity, Marni Mishna
  • Hilbert Spaces, Approximation, and the Spectral Theory of Compact OperatorsNilima Nigam
  • Contact Processes and Disease Models on Complex Networks, Alexander Rutherford
  • Topics in Besov Spaces, Interpolation and Non-linear Approximation, Ben Adcock
  • Topics in Computer Algebra, Michael Monagan

2016 Reading Courses

  • Wavelets, Approximation Theory and Signal Processing, Ben Adcock
  • Introduction to Measure-Theoretic Probability, Paul Tupper
  • Boundary Element Methods, Nilima Nigam
  • Non-Linear Discrete Optimization, Tamon Stephen
  • Singularity Analysis and Combinatorial Enumeration, Marni Mishna
  • History of Mathematical Analysis, 1600–1950, Tom Archibald
  • Toric Geometry, Nathan Ilten
  • Operational Research Applied to Epidemiology and Health Services, Sandy Rutherford & JF Williams

2015 Reading Courses

  • An Introduction to Compressed Sensing, Ben Adcock
  • Applied Combinatorics Field School, Karen Yeats & Marni Mishna
  • Topics in Computer Algebra, Michael Monagan

2014 Reading Courses

  • Fast Direct Solvers for Integral Equations, MC Kropinski
  • Elliptic Curves, Nils Bruin
  • Stochastic Processes in Physics and Chemistry, Paul Tupper
  • Further Topics in Complex Analysis, Nilima Nigam
  • Topics in Computer Algebra, Michael Monagan

2013 Reading Courses

  • Topics in Kinetic Theory, Weiran Sun
  • Introduction to Measure-Theoretic Probability, Paul Tupper
  • Topics in Computer Algebra, Michael Monagan
  • Spectral Methods, Manfred Trummer
  • Analytic Combinatorics in Several Variables, Karen Yeats
  • p-adic analysis, Nils Bruin

2012 Reading Courses

  • Computational Aspects of Medical Imaging, Manfred Trummer
  • Several Complex Variables and Analytical Combinatorics, Karen Yeats
  • Symbolic Dynamics, Bojan Mohar
  • Matroid Theory, Matt DeVos
  • Modelling of Complex Social Systems, Vahid Dabbaghian
  • PDE and Pseudo-Differential Operators, Nilima Nigam
  • Dynamical Systems, Chaos, and Noise, Sandy Rutherford
  • Topics in Magnetohydrodynamics (MHD) and Computational MHD, Steven Pearce
  • Fundamentals of Arithmetic Geometry, Nils Bruin
  • Introduction to Measure-Theoretic Probability, Paul Tupper

2011 Reading Courses

  • Historiography of Modern Mathematics, Tom Archibald
  • Modified Generalized Laguerre Functions Tau Method for Solving the Lane-Emden Equation, Steven Pearce
  • Topics in Computer Algebra, Michael Monagan
  • Geometry and Optimization, Luis Goddyn and Matt DeVos
  • The Numerical Solution of Integral Equations, Mary-Catherine Kropinski
  • Mathematical Models of Whole Genomes Analysis, Cedric Chauve
  • Mathematical Epidemiology, Ralf Wittenberg and Sandy Rutherford