Computational Models and Simulations of Epidemic Infectious Diseases

In this episode of the Data Exchange I speak with Bruno Gonçalves, a data scientist working at the intersection of Data Science and Finance. I have known Bruno for several years and we met when I recruited him to teach several extremely popular conference tutorials and talks on machine learning and deep learning. Prior to shifting over to data science, he spent several years as a researcher focused on mathematical models in Epidemiology – a field with a rich history dating as far back as the 1920s.  This episode is devoted to tools and techniques for modeling epidemics.Our conversation covered:Bruno’s background and his experience in modeling epidemics.The field of epidemic models: what techniques are used, the size of the community of researchers, and how do models get evaluated.His two recent posts: “Epidemic Modeling 101 – Or why your CoVID-19 exponential fits are wrong” and  “Epidemic Modeling 102 – All CoVID-19 models are wrong, but some are useful”The role that epidemic models play in decision making.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Data Exchange Newsletter.