Brazilian society is facing a public security crisis whose causes transcend purely criminal issues. Urban factors such as population density, presence of commercial and industrial establishments, location of bars and restaurants, people flow, presence of parks, climatic factors, in addition to socioeconomic conditions, strongly influence the pattern and dynamics of crime in each location in a city. Thus, an integrated analysis of crime data, urban infrastructure, climate, and socio-environmental factors is essential to identify crime patterns reliably. In this lecture we will present data science and machine learning tools that allow the joint analysis of crime data and external variables, assisting agencies responsible for public security in the elaboration of policies aimed at crime prevention in urban areas.
* Text informed by the author.
When: February 11, 2021, at 3 pm.
Where: Via Zoom
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Speaker: Luis Gustavo Nonato - Graduated in Mathematics at the Universidade Estadual Paulista Júlio de Mesquita Filho (1991), master's (1994) and doctorate (1998) in Applied Mathematics at the Pontifical Catholic University of Rio de Janeiro, having completed a post-doctorate at the University of Utah (2008-2010) and served as a visiting professor at New York University (2016-2018). He is currently a Full Professor at the University of São Paulo. He has experience in Data Science, Visualization, Geometric Processing, and Applied Mathematics.