Dr Diogo Pacheco
Lecturer in Computer Science
My name is Diogo F. Pacheco, and I am passionate about data; by its capacity to inform and to mislead. I am particularly interested in computational social science and modeling complex social behavior, i.e. combining the expertise of social, cognitive, and STEM scientists to develop tools to enhance our understanding about society.
I started my academic life at the University of Pernambuco (Recife-PE, Brazil) aiming to use computational intelligence to solve practical real world problems. My bachelors and masters in Computer Engineering main contribution was building a decision support system (DSS) for the sugarcane harvest problem. The DSS was empowered by an evolutionary multi-objective optimization algorithm processing leveraged information from artificial neural networks.
In 2013, after a 5-year break from Academia working in the Industry, I moved to the USA to start my Ph.D. focusing on the exploration of social media data (the digital footprints) as a proxy for understanding human behavior, at the Florida Institute of Technology. In 2018, I joined (and still affiliated) the Observatory on Social Media and Center for Complex Networks and Systems Research at Indiana University as a postdoctoral fellow. We focused our research in the misinformation arena, trying to understand the biases making us vulnerable to it, and detecting coordinated groups exploiting social media platforms.
- Ph.D. Computer Science, "Information Densification of Social Constructs via Behavior Analyses of Social Media Users - A Study on Twitter", Florida Institute of Technology (FIT), USA 2017.
- M.Sc. Computer Engineering, "An Evolutionary Multi-Objective Approach to Decision Support in Sugarcane Harvest", University of Pernambuco (UPE), Brazil 2008.
- B.Sc. Computer Engineering, "Decision Support in Intelligent Systems for Agricultural Crops", University of Pernambuco (UPE), Brazil 2006.
I more than welcome motivated students, self-funded PhD, and postdocs to do research on Social Media Analysis and Complex Networks, specifcally, to combat misinformation and inauthentic behavior online. These links might be useful: