Carlos Castillo Ocaranza

Carlos Castillo Ocaranza

Universitat Pompeu Fabra

Engineering Sciences

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.

Research interests

The focus of my research is algorithmic fairness. Currently, I work on automated risk assessment methods that satisfy algorithmic fairness criteria, validating them through interdisciplinary research, in various applied settings. One particular area of focus is the usage of algorithms for human recommendation, including algorithmic hiring, where I seek to define and enforce fairness criteria in algorithms for ranking.

Selected publications

- Karimi-Haghighi M, Castillo C, Tolan S & Lum K 2023, 'Effect of Conditional Release on Violent and General Recidivism: A Causal Inference Study.' Journal of Experimental Criminology, Springer.
- Merchant A & Castillo C 2023, 'Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks for Node Classification.' Proceedings CIKM '23, 1818-1827.