Hello, I am Germano Barcelos a Master Computer Science Student at UFV studying Deep Learning to model Human Mobility Patterns. My journey in Data Science began in 2019 when I joined into NESPED-Lab as an Undergradute Research to study about geospatial data enrichment. There I developed the package MoreData which uses OpenStreetMap, Geopandas and others tools to provide an ease way to enrich data from different databases. In 2021, I participated in GSoC developing Spatial Optimization (Location Set Covering, P-Center, P-Median and Maximal Covering Set Models) models. When GSoC finished I joined into the developers team of PySAL which is the organization that I contributed for, specifically to spopt project.
Semantic Enrichment, Deep Learning, Human Mobility, Spatial Optimization, Machine Learning
Below there is the most beautiful formulas created by Newton but is used in Human Mobility to study shifting patterns. As the Tobler’s First Law of Geography states: “everything is related to everything else, but near things are more related than distant things”.
$$X_{ij}=G\frac{Y_i^{\beta_1}Y_j^{\beta_2}}{d_{ij}^{\beta_3}}$$