I'm happy to serve as a mentor for undergraduate research projects or directed readings in dynamical systems and climate.
Students who are interested in working with me should have taken Calculus I and II (MATH 1110 and 1120, or equivalent) and Linear Algebra (MATH 2210) or at least
one course dealing with mathematical models (e.g. MATH 3610) (or be currently enrolled). They should also be willing to learn a mathematical programming
language like MATLAB, Python, or Mathematica. Prior knowledge of programming is not necessary! If you're interested in working on a project with me, please send me a short email with the following items:
(1) the reason you are interested in doing a math research project,
(2) what interests you about math and climate, and
(3) a few times you are available to meet in the coming week for a 30 minute discussion about possible projects.
In your email, please feel free to address me by my first name. The University of Minnesota Undergraduate Research Office has a nice sample letter if you're struggling to get started.
Past Mentees
I mentored four undergraduate projects at the University of Minnesota. Below are my students and their project titles:
E. Jaschke, "Adapting the Budyko Energy Balance Model to Pluto"
K. Kieu, "Detecting rate-induced tipping in two dimensional systems"
E. Reed, "Proposed Effects of Early Agriculture on Current Climate"
J. Sherman, "Constraints on the Oceanic Carbon Sink using Atmospheric Oxygen Data"
Three of these projects were funded summer projects. Another was a directed study. If you have questions about these opportunities, please ask!
My Undergraduate Research
As an undergraduate I worked with Mark Schneider on a physics
project showing interference between two photons and Marc Chamerbland on a computational combinatorics
project featuring the multiplicative partitions of positive integers. I also worked with Kevin Hartshorn
on a compuational geometry project that investigated the folding of non-convex polygons.
Even though these projects are unrelated to my current research, they were good stepping stones for learning the analytical, computational, and organizational skills needed to conduct successful research.
Last Modified: August 29, 2019 The views and opinions expressed in this page are strictly those of the page author.
The contents of this page have not been reviewed or approved by Cornell University.