Author

Carlos Pinheiro
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Distinguished Data Scientist

Dr. Carlos Pinheiro is a Distinguished Data Scientist at SAS, U.S., and an Adjunct Professor at SKEMA Business School, U.S. Dr. Pinheiro has a B.Sc. in Applied Mathematics and Computer Science, a M.Sc. in Computing and holds a D.Sc. in Engineering from Federal University of Rio de Janeiro (2005). He has accomplished a series of Post-Doctoral research terms in different fields, such as in Optimization at IMPA, Brazil (2006-2007), in Social Network Analysis at Dublin City University, Ireland (2008-2009), in Transportation Systems at Université de Savoie, France (2012), in Urban Mobility and Dynamic Social Networks at Katholieke Universiteit Leuven, Belgium (2013-2014) and in Urban Mobility and Multi-modal Traffic at Fundação Getúlio Vargas, Brazil (2014-1015). He has published several papers in international journals and conferences, is recipient of U.S. Patent, and author of the books Network Science: Analysis and Optimization Algorithms for Real-World Applications (2022, Wiley), Introduction to Statistical and Machine Learning Methods for Data Science (2021, SAS), Heuristics in Analytics: A Practical Perspective of What Influence Our Analytical World (2014, Wiley) and Social Network Analysis in Telecommunications (2011, Wiley).

Advanced Analytics | Analytics | Data Visualization
Carlos Pinheiro 0
Vehicle Routing Problem - A beer distribution example in Asheville

The Vehicle Routing Problem (VRP) algorithm aims to find optimal routes for one or multiple vehicles visiting a set of locations and delivering a specific amount of goods demanded by these locations. Problems related to the distribution of goods, normally between warehouses and customers or stores, are generally considered vehicle routing problems. For this article's example, let’s consider a real (and awesome) brewery that needs to deliver beer kegs to different bars and restaurants throughout multiple locations.

Advanced Analytics | Analytics | Artificial Intelligence | Data Visualization | Machine Learning
Carlos Pinheiro 0
Optimal tour of Brisbane based on a multi-modal transportation system

A few months ago, I published an article about network optimization and how to find an optimal tour when visiting multiple places of interest by using different types of transportation, like buses, trains, tram, metro, and even walking. For a real-world case, I decided to run these optimal tours in

Advanced Analytics | Analytics | Artificial Intelligence | Data for Good | Data Visualization | Machine Learning
Carlos Pinheiro 0
Mobility tracing: Helping local authorities in the fight against COVID-19

The current state of policy enforcement during an infectious disease pandemic is mostly reactive. Public health officials track changes in active cases, identify hot-spots and enforce containment policies primarily based on geographic proximity. By combining telecommunications data -- which we turn into mobility information -- with public health data of