Teaching

Workshop on interactive data visualisation in Python

This is a workshop I have given for various institutions including the Centre de Recherches Mathématiques, the Centre for Applied Mathematics in Bioscience and Medicine, and the Quantitative Life Sciences Dept. at McGill University. Slides and Jupyter notebooks are available at the Github repository.

QLSC 600, Resetting and Entraining Biological Oscillators, McGill

• Course outline
• Bootcamp on nonlinear dynamics (slides)
• Early warning signals for bifurcations (slides, Jupyter notebook)
• Cardiac arrhythmia (slides)

Math 127, Calculus I for the Sciences, UWat

• Lecture notes (handwritten)

Math 117, Calculus I for Engineering, UWat

Exercises and solutions (LaTeX):

• Inequalities, Exponentials and Logarithms, Inverses
• Composite Functions, Piecewise Functions, Partial Fractions
• Trigonometric Functions, Hyperbolic Functions
• Limits and Continuity
• Differential Calculus
• Differentials, L’Hopital’s Rule, and Curve Sketching
• Riemann Integrals, The FTC and Integration Techniques
• Further Integration Techniques and Applications
• Improper Integrals, Polar Coordinates and Complex Numbers

AMATH 777, Stochastic Processes in the Physical Sciences, UWat

• Lecture on Gillespie's algorithm
• Notebook to implement Gillespie's algorithm (Mathematica)

Teaching pedagogy

I am interested in the development and implementation of active learning techniques in the classroom. Below is an article I wrote as part of the Certificate in University Teaching at the Universtiy of Waterloo.

• On cooperative learning in undergraduate mathematics courses (2018)