Course on stochastic spatial dynamics in the coming semester

I am teaching a course on stochastic spatial dynamics in biology. This is an advanced course, relatively mathematical, but covers topics that are directly state of the art in research in spatial ecology. Here are details.

Title: Stochastic and Spatial Dynamics in Biology (EC 303: 2:1 credits)

Instructor: Vishwesha Guttal

Dept: CES, IISc

Overview: This course will cover topics on stochastic and spatial dynamics in biology that will have applications to various topics such as the ecology of species to pattern formation in cellular systems. Tentative topics are: 1) Brownian motion, basics of stochastic processes, diffusion approximations, Levy walks for organismal movement and dispersal, 2) Single-species dynamics accounting for stochasticity and space; using bifurcation theory, reaction-diffusion equations, Fisher Kolmogorov equation, Fokker- Planck and Langevin equations, etc. 3) Multi-species spatial dynamics. 4) Self-organization and pattern formations in biological systems; Turing patterns; swarm dynamics and swarm intelligence (agent-based models; non-equilibrium statistical physics), etc. Concepts of Phase Transitions in Biology.

Pre-requisites/Eligibility:  EC 201 or equivalent (i.e. proficiency in basic concepts of ecology, nonlinear dynamical models of theoretical ecology, calculus and good programming skills in R/Python/Matlab/C/C++). Instructor may allow students with exceptional interest to take without the pre-requisite of EC 201 if they demonstrate necessary background. UG/MTech/PHD students are all welcome. Auditing students are welcome too — as long as you are willing to work though all assignments like regular students.

Tentative Class Schedule: Wednesdays (11 am – 12:30 pm) and Fridays (2 pm–5 pm). 


If you are interested, please fill in this form as soon as possiblehttps://forms.gle/zgvzdXKPQS7ykn1n7

One thought on “Course on stochastic spatial dynamics in the coming semester

  1. Pingback: Best theoretical ecology paper award by ESA | Theoretical Ecology and Evolution Laboratory

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