Carlos Castillo

Carlos Castillo is an ICREA Research Professor at Universitat Pompeu Fabra, leading the Social and Responsible Computing Research Group. Their work focuses on algorithmic fairness, social computing, and mitigating bias in AI systems across criminal justice, education, healthcare, and hiring. Key projects include the Horizon Europe FINDHR initiative to detect discrimination in algorithmic hiring, causal inference studies on recidivism risk prediction, and analyzing gender biases in student evaluations.

Research Interests: Algorithmic fairness, bias mitigation in AI systems, social data ethics, criminal justice analytics, education technology, and health informatics. Notable contributions include the FA*IR fair ranking algorithm and foundational work on auditing algorithms in digital health.

Recent Trends in Articles: Recent work emphasizes interdisciplinary applications of algorithmic fairness—e.g., improving representativeness in hiring datasets, analyzing disparities in medical AI models, and addressing bias in student satisfaction surveys. Publications also explore radicalization pathways via recommendation systems and the societal impact of algorithmic decision-making.

• Awards: Best Paper Awards in CIKM 2022 (Francesco Fabbri), ICAIL 2019 (Marius Miron), and ISCRAM 2013 (Muhammad Imran).
• Grants: Leads the Horizon Europe FINDHR project and collaborates with the European Commission on algorithmic discrimination research.
• Labs/Teams: Directs the Social and Responsible Computing Group, focusing on interdisciplinary projects with PhD students and industry partnerships.