Research Assistant (Project Lead)
MAPS Lab & Faculty of Agriculture
Developing a stochastic particle model for food waste dispersion simulation using Bayesian inference.
What I'm Doing
I am developing a stochastic particle model in PyTorch and GeoPandas that simulates food waste dispersion across Halifax. The model fits emission rates to the city's municipal collection records through Bayesian inference.
Impact (Expected)
The model aims to provide data-driven insights into food waste distribution patterns across Halifax, potentially informing municipal waste management decisions.
What I'm Learning
I am gaining experience with stochastic simulation models, Bayesian parameter estimation, and geospatial data processing with GeoPandas. The work requires fitting model parameters to real municipal data and validating simulation outputs against observed collection records.
Key Highlights
Developing a stochastic particle model in PyTorch and GeoPandas that simulates food waste dispersion across Halifax, fitting emission rates to the city's municipal collection records through Bayesian inference.