Carlos' goal is to address problems of social significance through computational methods and interdisciplinary research, and his current focus is on algorithmic fairness. His background is web mining and information retrieval, and he has been influential in the areas of crisis informatics and web content quality and credibility. He is a prolific, highly cited researcher who has received two test-of-time awards, five best paper awards, and two best student paper awards. His works include a book on Big Crisis Data, as well as monographs on Information and Influence Propagation, and Adversarial Web Search. He leads the Web Science and Social Computing research group at Universitat Pompeu Fabra, and coordinates the Horizon Europe FINDHR project on non-discrimination in algorithmic hiring.
The focus of my research is algorithmic fairness. Currently, I work on automated risk assessment methods that satisfy algorithmic fairness criteria, such as separability and sufficiency, validating them through interdisciplinary research in various applied settings. I also work on algorithms for fair recommendation and fair search, seeking to give similar items similar exposure, as well as trying to steer people away from false or misleading information or harmful content.