Courses: 2025-2026

The following courses were scheduled for the 2025-2026 academic year:

Advanced studies in Theoretical and Computational Biology

Instructor(s)

Prerequisites

  • Ordinary differential equations

  • Numerical methods (Numerical Analysis I and II)

  • Partial differential equations

  • Matrix theory

  • Linear systems

Registration

Registration for this course is not currently available.

Abstract

The purpose of this graduate course is to equip graduate students with cutting-edge techniques in data-driven mathematical and computational modelling, analysis and simulations of semi-linear parabolic partial differential equations (PDEs) of reaction-diffusion type. It will cover diverse areas in data-driven modelling using PDEs in biology. I will cover approaches on formulating models from data using first principles, mathematical analysis of reaction-diffusion systems such as linear stability analysis, basic concepts on bifurcation analysis and numerical bifurcation analysis. The second part will focus on numerical methods for PDEs including finite difference methods, and finite elements. This part will also deal with time-stepping schemes and nonlinear solvers for nonlinear PDEs. If time allows, we will look at applications of reaction diffusion theory to cell motility and pattern formation. To support theoretical modelling and numerical analysis, numerical algorithms will be developed and implemented in MATLAB as well as in open finite element source software packages such as FeNiCs, deal.ii and others. Students will be allowed to use packages of their choice as appropriate. Expertise and skills sets to be acquired through this course

  1. Acquire data-driven modelling skills and techniques in PDEs and their applications to biology
  2. Acquire techniques and knowledge in mathematical analysis of reaction-diffusion systems
  3. Acquire expertise and skills in bifurcation analysis, numerical bifurcation, and sensitivity analysis
  4. Acquire numerical analysis techniques and skills to compute approximate numerical solutions
  5. Acquire expertise and knowledge in finite difference methods for semi-linear parabolic PDEs
  6. Acquire expertise and knowledge in finite element methods for semi-linear parabolic PDEs
  7. Gain some knowledge in bulk-surface PDEs, and their analysis (might be covered if time allows) Key

Syllabus

  1. The art of mathematical modelling
    1. An introduction to the art of mathematical modelling
    2. The physical origins of partial differential equations and their applications
      1. Derivation of the heat equation: Heat Transfer (A taster of what to come)
      2. General classification of PDEs
    3. Mathematical Notations and Definitions
    4. Physical laws
    5. Exercises
  2. Reaction-diffusion systems on stationary domains: modelling, analysis and simulations
    1. Introduction
    2. Derivation of reaction-diffusion systems on stationary domains
    3. Classical nonlinear reaction kinetics
      1. Activator-depleted reaction kinetics
      2. Gierer-Meinhard reaction kinetics
      3. Thomas reaction kinetics
    4. Non-dimensionalisation – unit free
      1. Reaction-diffusion system with activator-depleted reaction kinetics
      2. Reaction-diffusion system with Gierer–Meinhardt reaction kinetics
      3. Reaction-diffusion system with Thomas reaction kinetics
  3. Stability analysis of reaction-diffusion systems on stationary domains and the generation of parameter spaces
    1. Introduction
      1. Preliminaries
    2. Linear stability analysis of reaction-diffusion systems on stationary domains
      1. Linear stability in the absence of spatial variations
      2. Linear stability in the presence of spatial variations
    3. Eigenfunctions in one dimension and on special domains in two dimensions
      1. Eigenfunctions in one dimension
      2. Eigenfunctions of a rectangle
  4. Numerical Methods for Reaction-Diffusion Systems on Stationary Domains
    1. Finite Difference Methods for Reaction-Diffusion Systems on Stationary Domains
      1. Finite Difference Stencils in 2- and 3-Dimensional Domains
      2. Forward Euler Method
      3. Backward Euler Method
      4. Crank-Nicholson Method
      5. Fractional-Step 𝜃 method
      6. Implicit and explicit (IMEX) time-stepping schemes for reaction-diffusion systems on stationary domains
    2. Finite Element Methods for Reaction-Diffusion Systems on Stationary Domains
      1. Sobolev Spaces
      2. Weak Variational Form
      3. Space discretisation
      4. Mesh Generation
      5. Time discretisation
    3. Fully implicit time-stepping schemes and non-linear solvers for systems of reaction-diffusion equations
    4. Algorithm development and implementation using finite element open source software pages
      1. Introduction to PDE computing with FeNiCs
      2. Algorithm development and testing in FeNiCs
  5. Introduction to reaction-diffusion systems on evolving domains and surfaces
    1. Reaction-diffusion systems on deforming domains and surfaces . . . . . .
    2. Finite element methods for reaction-diffusion systems on deforming domains and surfaces
  6. Summary of the course taught.

Other Information

Class Schedule

  • TBA

Remote Access

We will use zoom for each lecture. Course notes will be distributed in advance and lecture notes will be distributed after each lecture.

Availability

This course may be open to students from universities outside of the PIMS network.

Optimal Transport: Theory and Applications

Instructor(s)

Prerequisites

  • First year graduate course in real analysis and/or probability.

Registration

This course is available for registration under the Western Dean's Agreement but registrations must be approved by the course instructor. Please contact the instructor (using the email link to the left) including details of how you meet the course prerequisites. Next, you must complete the Western Deans' Agreement form , with the following course details:

Course Name
Optimal Transport: Theory and Applications
Course Number

University of Washington Students:

  • University of Washington: Math 581

All Other WDA Students:

  • University of British Columbia: Math 606D:101 (to be confirmed, contact yhkim@math.ubc.ca)
Section Number
Section Code

Completed forms should be returned to your graduate advisor who will sign it and take the required steps. For students at PIMS sites, please see this list to find your graduate advisor, for other sites, please see the Western Deans' Agreement website .

The Western Deans' Agreement provides an automatic tuition fee waiver for visiting students. Graduate students paying normal required tuition fees at their home institution will not pay tuition fees to the host institution. However, students will typically be be required to pay other ancillary fees to the host institution, or explicitly request exemptions (e.g. Insurance or travel fees). Details vary by university, so please contact the graduate student advisor at your institution for help completing the form. Links to fee information and contact information for PIMS member universities is available below in the WDA section.

Students at universities not covered by the WDA but which are part of the Canadian Association for Graduate Studies (CAGS) may still be eligible to register for some courses under the terms of the Canadian University Graduate Transfer Agreement (CUGTA). Details of this program vary by university and registration is also typically subject to ancillary fees. Both your local and the hosting university must participate in the agreement (e.g. UBC does not participate in CAGS). Please contact the relevant graduate student advisors for more information.

Abstract

The modern theory of Monge-Kantorovich optimal transport is barely three decades old. Already it has established itself as one of the most happening areas in mathematics. It lies at the intersection of analysis, geometry, and probability with numerous applications to physics, economics, and serious machine learning. This two quarter long graduate topics course will serve as an introduction to this rich and useful theory. We will roughly follow the following outline. Fall: Classical theory. Analytic description of solutions. Duality. Displacement convexity. The geometry of the Wasserstein space and Otto calculus. Winter: Entropy-regularized OT. Schroedinger bridges and statistical OT. This is a continuation of the sequence of OT+X courses under the Kantorovich Initiative.

Other Information

Delivery Details

Registration

Students at Canadian PIMS Member Universities may register through the Western Deans Agreement for the “shadow course” offered at UBC (see registration details above). Students at UW may register directly for the UW course. Course codes and other registration details for students in either of these cases are listed in the registration section above. Students at other institutions should contact one of the instructors to attend the course as a non-registered student.

Class Schedule

  • TBA

Remote Participation

Online instructions over Zoom. Written on a tablet. Notes will be provided. A Slack channel will be created for answering student questions. Weekly in person office hours will be held at UW and UBC.

Lecture notes will be distributed over Slack. Recorded lectures may be viewed on our YouTube channel.

Availability

This course may be open to students from universities outside of the PIMS network, and those coming from industry/government.

Algebraic Topology I

Instructor(s)

Prerequisites

  • a first course in real analysis, and some point-set topology, including quotient topologies, connectedness, path-connectedness.

  • Homotopy of maps and homotopy equivalence of spaces will be assumed, but the necessary background here can be quickly covered by self-study.

  • Fundamental groups and covering spaces, while helpful, are not necessary.

  • the theory of abelian groups, isomorphism theorems and the classification of finitely generated abelian groups.

  • Ring theory and the theory of modules over commutative rings is extremely helpful, but not formally required.

Registration

Registration for this course is not currently available.

Abstract

This is a course in homology and cohomology of topological spaces. We study spaces and continuous functions by means of abelian groups and their homomorphisms. Topics will include cellular homology of spaces, calculation techniques and applications (e.g., fixed point theorems, invariance of domain), homological algebra, and cohomology, including the cup product and Poincaré duality.

Other Information

Class Schedule

  • TBA

Remote Access

Remote access for this course will be provided via zoom. The instructor intends to lecture from handwritten notes on a tablet. Lecture notes will be provided after the lectures have been delivered.

Availability

This course may be open to students from universities outside of the PIMS network, and those coming from industry/government.

Applied Stochastic Analysis

Instructor(s)

Prerequisites

  • Good upper level undergraduate or early graduate knowledge of:

    • Probability
    • Linear Algebra
    • PDEs
    • ODEs
    • Prior experience with numerical analysis is helpful but not necessary

Registration

Registration for this course is not currently available.

Abstract

This course will introduce the major tools in stochastic analysis from an applied mathematics perspective. Topics to be covered include Markov chains (both discrete and continuous), Gaussian processes, Ito calculus, stochastic differential equations (SDEs), numerical algorithms for solving SDEs, forward and backward Kolmogorov equations and their applications. It will pay particular attention to the connection between stochastic processes and PDEs, as well as to physical principles and applications. The class will attempt to strike a balance between rigour and heuristic arguments: it will assume that students have seen a little analysis, particularly in the context of studying PDEs, but will generally avoid measure theory. The target audience is graduate students in applied mathematics or related fields, who wish to use these tools in their research for modelling or simulation. The course will be divided roughly into two parts: the first part will focus on stochastic processes, particularly Markov chains, and the second part will focus on stochastic differential equations and their associated PDEs.

Syllabus

syllabus.pdf

Other Information

Class Schedule

  • TBA

Remote Access

Remote access will be provided via zoom. The lectures will be delivered mostly on blackboards with occasional slides. PDF lecture notes will be handed out.

Availability

This course is open to students from within the PIMS network of universities.

Discrete Optimization

Instructor(s)

Prerequisites

  • A first course in linear algebra

  • A 3rd year course in any area of discrete mathematics or combinatorics

Registration

This course is available for registration under the Western Dean's Agreement but registrations must be approved by the course instructor. Please contact the instructor (using the email link to the left) including details of how you meet the course prerequisites. Next, you must complete the Western Deans' Agreement form , with the following course details:

Course Name
Discrete Optimization
Course Number
MATH 428/529
Section Number
A02
Section Code
CRN 12140

Completed forms should be returned to your graduate advisor who will sign it and take the required steps. For students at PIMS sites, please see this list to find your graduate advisor, for other sites, please see the Western Deans' Agreement website .

The Western Deans' Agreement provides an automatic tuition fee waiver for visiting students. Graduate students paying normal required tuition fees at their home institution will not pay tuition fees to the host institution. However, students will typically be be required to pay other ancillary fees to the host institution, or explicitly request exemptions (e.g. Insurance or travel fees). Details vary by university, so please contact the graduate student advisor at your institution for help completing the form. Links to fee information and contact information for PIMS member universities is available below in the WDA section.

Students at universities not covered by the WDA but which are part of the Canadian Association for Graduate Studies (CAGS) may still be eligible to register for some courses under the terms of the Canadian University Graduate Transfer Agreement (CUGTA). Details of this program vary by university and registration is also typically subject to ancillary fees. Both your local and the hosting university must participate in the agreement (e.g. UBC does not participate in CAGS). Please contact the relevant graduate student advisors for more information.

Abstract

Discrete optimization focuses on developing efficient methods to determine the maximum or minimum value of a function over a finite (discrete) domain. This course will cover a wide range of topics in discrete optimization which may include linear programming, semi-definite programming, dynamic programming, matroids, combinatorial algorithms, duality, hardness reductions, among others. We will also see many interesting applications of tools from Discrete Optimization to problems in combinatorics and other areas of mathematics and computer science.

Other Information

Course Webpage

This course will have an accompanying webpage

Materials related to the course, links and other updates will be posted to the course webpage as the course proceeds.

Class Schedule

  • Monday, Thursday 1:00-2:20pm (PT)

Remote Access

Remote access for this course will be provided via zoom. This course will be taught from the UVic Multiaccess classroom HHB 110. The room is equipped with multiple cameras in the ceiling which can capture two blackboard areas and TV screens that can be used to show the Zoom gallery. A demonstration of this system can be seen in the instructor’s existing Extremal Combinatorics Network Wide Course playlist. Notes and other course related material will be made available on the instructor’s website (see e.g. notes for Extreemal Combinatorics).

Lectures will also be live-streamed on the instructors YouTube channel and also be available to view there asynchronously.

Availability

This course may be open to students from universities outside of the PIMS network, and those coming from industry/government.

Elliptic Curves and Modular Forms

Instructor(s)

Prerequisites

  • The course is designed to be accessible to M.Sc. students and above

    • Complex Analysis
    • Abstract Algebra

Registration

This course is available for registration under the Western Dean's Agreement but registrations must be approved by the course instructor. Please contact the instructor (using the email link to the left) including details of how you meet the course prerequisites. Next, you must complete the Western Deans' Agreement form , with the following course details:

Course Name
Elliptic Curves and Modular Forms
Course Number
Section Number
Section Code

Completed forms should be returned to your graduate advisor who will sign it and take the required steps. For students at PIMS sites, please see this list to find your graduate advisor, for other sites, please see the Western Deans' Agreement website .

The Western Deans' Agreement provides an automatic tuition fee waiver for visiting students. Graduate students paying normal required tuition fees at their home institution will not pay tuition fees to the host institution. However, students will typically be be required to pay other ancillary fees to the host institution, or explicitly request exemptions (e.g. Insurance or travel fees). Details vary by university, so please contact the graduate student advisor at your institution for help completing the form. Links to fee information and contact information for PIMS member universities is available below in the WDA section.

Students at universities not covered by the WDA but which are part of the Canadian Association for Graduate Studies (CAGS) may still be eligible to register for some courses under the terms of the Canadian University Graduate Transfer Agreement (CUGTA). Details of this program vary by university and registration is also typically subject to ancillary fees. Both your local and the hosting university must participate in the agreement (e.g. UBC does not participate in CAGS). Please contact the relevant graduate student advisors for more information.

Abstract

This course is an introduction to the theory of elliptic curves and modular forms at the graduate level. Elliptic curves will be introduced through both their classical analytic construction over the real and complex numbers and their algebraic realizations via normal forms over arbitrary fields. Moduli and monodromy considerations lead us to study the special role of the elliptic modular group SL(2,Z) and the crucial notions of modular functions and forms. Studying torsion points and level structure then motivates the extension to finite index subgroups and the theory of modular curves. Throughout the course, there will be an emphasis on hands-on explicit computations. Directed by the instructor, each student will complete a final project, presentation, and paper. Possible topics could include post-quantum elliptic curve cryptography, applications in string theory, geometry of elliptic modular surfaces, features of periods and Picard-Fuchs operators, etc.

Other Information

Class Schedule

  • TBA

Remote Access

The course will be taught over Zoom using a tablet and shared screen. Lecture notes will be written out live on a tablet. There will also be pre-prepared slides on certain topics. The in-class lecture notes will be saved and distributed as .pdf files. There will be a course webpage to host all of these plus additional course materials and readings.

The format will be Zoom based, with videos on. Breakout rooms will be used periodically for small group work. Students will be encouraged to “raise hands” with questions at any time.

Availability

This course may be open to students from universities outside of the PIMS network, and those coming from industry/government.

Modern Biophysics

Instructor(s)

Prerequisites

Registration

This course is available for registration under the Western Dean's Agreement but registrations must be approved by the course instructor. Please contact the instructor (using the email link to the left) including details of how you meet the course prerequisites. Next, you must complete the Western Deans' Agreement form , with the following course details:

Course Name
Modern Biophysics
Course Number
PHYS 555 (to be confirmed)
Section Number
Section Code

Completed forms should be returned to your graduate advisor who will sign it and take the required steps. For students at PIMS sites, please see this list to find your graduate advisor, for other sites, please see the Western Deans' Agreement website .

The Western Deans' Agreement provides an automatic tuition fee waiver for visiting students. Graduate students paying normal required tuition fees at their home institution will not pay tuition fees to the host institution. However, students will typically be be required to pay other ancillary fees to the host institution, or explicitly request exemptions (e.g. Insurance or travel fees). Details vary by university, so please contact the graduate student advisor at your institution for help completing the form. Links to fee information and contact information for PIMS member universities is available below in the WDA section.

Students at universities not covered by the WDA but which are part of the Canadian Association for Graduate Studies (CAGS) may still be eligible to register for some courses under the terms of the Canadian University Graduate Transfer Agreement (CUGTA). Details of this program vary by university and registration is also typically subject to ancillary fees. Both your local and the hosting university must participate in the agreement (e.g. UBC does not participate in CAGS). Please contact the relevant graduate student advisors for more information.

Abstract

This graduate course is designed to provide graduate students with key concepts and practical applications in Biophysics, with an emphasis on the quantitative tools as they are used in current research. Biophysics is a highly interdisciplinary field—the researchers who attend the annual Biophysical Society meeting, for example, come from departments spanning all of the STEM disciplines. Nevertheless, they share a common interest to establish a quantitative understanding of living matter. Despite growing interest however, a gap remains in graduate training to prepare students to contribute effectively to this broad and rapidly evolving field. This course aims to address this gap by covering both foundational and advanced concepts and applications that are commonly used by practicing biophysicists today. The structure of the course will follow selected advanced material from Physical Biology of the Cell by Rob Phillips, Jane Kondev, Julie Theriot, and Hernan G. Garcia. Each topic will be introduced conceptually, developed mathematically, and explored through real biological case studies using both textbook material and current literature. Given student interest, the course may include interviews with leading biophysicists on their recent published work. Topics will include:

  • Diffusion problems in biology
  • Enzymatic reactions including ODEs, diffusion-limited reactions, and Michaelis-Menton reactions
  • Statistical mechanics as it applies to Biology, including Gibbs free energy of biochemical reactions
  • Liquid-liquid phase separation, and its role in the cell and in transcription
  • Polymer physics; DNA looping, persistence length, polymer entropy
  • Heterogeneous mixtures and osmotic pressure
  • Quantitative analysis of genetic networks
  • Expression distributions of transcription and translation
  • Phase portrait analysis and stability/metastability of cellular states
  • Genetics of enhancers – from a biophysical perspective
  • Pattern formation including Turing patterns, symmetry breaking in an embryo
  • Quantitative genomics (time permitting)

Syllabus

syllabus.pdf

Other Information

Class Schedule

  • TBA

Remote Access

Remote participation will be via zoom. Lectures will also be recorded and shared via UBC’s media capture system Panopto. Annotated notes on pre-distributed PDF slides are made during class using an iPad, recorded in real time, and uploaded to UBC’s Canvas server after class, along with links to the lecture recording.

Availability

This course may be open to students at universities outside of the PIMS network.

Topics in Optimization: Mathematical Foundations of Machine Learning

Instructor(s)

Prerequisites

  • Mathematical maturity at the second year master’s level or higher

  • Measure theory

Registration

This course is available for registration under the Western Dean's Agreement but registrations must be approved by the course instructor. Please contact the instructor (using the email link to the left) including details of how you meet the course prerequisites. Next, you must complete the Western Deans' Agreement form , with the following course details:

Course Name
Discrete Optimization
Course Number
MATH 604
Section Number
Section Code

Completed forms should be returned to your graduate advisor who will sign it and take the required steps. For students at PIMS sites, please see this list to find your graduate advisor, for other sites, please see the Western Deans' Agreement website .

The Western Deans' Agreement provides an automatic tuition fee waiver for visiting students. Graduate students paying normal required tuition fees at their home institution will not pay tuition fees to the host institution. However, students will typically be be required to pay other ancillary fees to the host institution, or explicitly request exemptions (e.g. Insurance or travel fees). Details vary by university, so please contact the graduate student advisor at your institution for help completing the form. Links to fee information and contact information for PIMS member universities is available below in the WDA section.

Students at universities not covered by the WDA but which are part of the Canadian Association for Graduate Studies (CAGS) may still be eligible to register for some courses under the terms of the Canadian University Graduate Transfer Agreement (CUGTA). Details of this program vary by university and registration is also typically subject to ancillary fees. Both your local and the hosting university must participate in the agreement (e.g. UBC does not participate in CAGS). Please contact the relevant graduate student advisors for more information.

Abstract

This course is a bridge into the machine learning literature for graduate students in mathematics. Compared to existing course offerings in our neighbouring departments (mainly https://www.cs.ubc.ca/~dsuth/532D/23w1 (https://www.cs.ubc.ca/~dsuth/532D/23w1)) we will assume that you know somewhat more analysis, but prior coding experience will not be required. Briefly, the learning objectives are:

  • understand the different “learning paradigms” considered in ML (supervised learning, unsupervised learning, reinforcement learning, etc.) and their relation with existing statistical theory
  • be comfortable with mathematical tools (eg. kernel methods) which appear commonly in the ML literature but are not well known among pure mathematicians
  • see some natural connections between ML theory and: optimization/calculus of variations, measure theory, PDE, etc
  • gain fluency reading ML papers (which can be less trustworthy than pure math papers)
  • start to think about how to bring your area of mathematical expertise to bear on ML problems.

Syllabus

Outline:

  • Unit 0: (~1 week) What is machine learning?
  • Unit 1: (~4 weeks) Supervised learning: The statistical learning theory framework. Inference in high dimension. Falsibiability of models and measures of model complexity. Regression and classification. Kernel methods. Learning with neural networks. Double-descent and failure of Ockham’s razor.
  • Unit 2: (~3 weeks) Unsupervised learning: Clustering and dimensionality reduction. Manifold hypothesis. Geometric graph methods. Inferring probability distributions: density estimation, sampling, generative models.
  • Unit 3: (~4 weeks) Reinforcement learning: Exploration-exploitation tradeoff. Sequential decision problems. Markov decision processes and connections with control theory. Efficient exploration for bandit problems and small-scale games. Complexity notions and learnability for large scale games.

Main references: for textbook references we will use a couple chapters from each.

  • Unit 0: Vapnik, “The nature of statistical learning theory”.
  • Unit 1: Wainwright, “High-dimensional statistics”. Bach, “Learning theory from first principles”.
  • Unit 2: There is no good textbook for unsupervised learning that I am aware of. I have course notes. We will also look at some classic research papers, for example for geometric graph methods we will read “Laplacian eigenmaps for dimensionality reduction and data representation” by Belkin and Niyogi.
  • Unit 3: Foster and Rakhlin, RL theory notes: https://arxiv.org/abs/2312.16730

Other Information

Class Schedule

  • TBA

Remote Access

Remote access to this course will be via zoom. The delivery mechanism will be either blackboard or via tablet depending on available rooms. A PDF textbook and/or research article readings will be distributed in advance of each class.

Availability

This course may be open to students from universities outside of the PIMS network.

Mathematical Biology - Nonlinear PDE Models

Instructor(s)

Prerequisites

Registration

This course is available for registration under the Western Dean's Agreement but registrations must be approved by the course instructor. Please contact the instructor (using the email link to the left) including details of how you meet the course prerequisites. Next, you must complete the Western Deans' Agreement form , with the following course details:

Course Name
Mathematical Biology - Nonlinear PDE Models
Course Number
MATH559
Section Number
MATH_O 559
Section Code
PLEASE NOTE: This course is hosted at the UBC Okanagan campus. Requests for registration under the WDA should be directed to graduate admissions at UBC Okanagan

Completed forms should be returned to your graduate advisor who will sign it and take the required steps. For students at PIMS sites, please see this list to find your graduate advisor, for other sites, please see the Western Deans' Agreement website .

The Western Deans' Agreement provides an automatic tuition fee waiver for visiting students. Graduate students paying normal required tuition fees at their home institution will not pay tuition fees to the host institution. However, students will typically be be required to pay other ancillary fees to the host institution, or explicitly request exemptions (e.g. Insurance or travel fees). Details vary by university, so please contact the graduate student advisor at your institution for help completing the form. Links to fee information and contact information for PIMS member universities is available below in the WDA section.

Students at universities not covered by the WDA but which are part of the Canadian Association for Graduate Studies (CAGS) may still be eligible to register for some courses under the terms of the Canadian University Graduate Transfer Agreement (CUGTA). Details of this program vary by university and registration is also typically subject to ancillary fees. Both your local and the hosting university must participate in the agreement (e.g. UBC does not participate in CAGS). Please contact the relevant graduate student advisors for more information.

Abstract

In this course we are learning to build and analyse nonlinear partial differential equation models. The focus of the course will be models of ecological systems, but the techniques learned apply broadly across application areas. We learn a wide variety of analytic, graphic, and simplification techniques which elucidate the behaviour of these mathematical models, whether or not a closed-form solution is available. By the end of the class, the students will be able to competently read and follow a research paper presenting and analysing a differential equation model from a wide variety of application areas. Broadly, the topics that we cover are applications of ecological applications of travelling waves, disease models, and pattern formation in reaction-diffusion and reaction-diffusion-chemotaxis models.

Syllabus

syllabus.pdf

Other Information

Class Schedule

TBA

Remote Access

Lectures will be livestreamed via zoom. The lecturer will be writing on a whiteboard interspersed with pdf presentations. Lecture notes will be posted on Canvas.

Availability

This course may be open to students from universities outside of the PIMS network.