Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms. - Nathan Dennler; Anaelia Ovalle; Ashwin Singh; Luca Soldaini; Arjun Subramonian; Huy Tu; William Agnew; Avijit Ghosh; Kyra Yee; Irene Font Peradejordi; Zeerak Talat; Mayra Russo; et al. (AIES, 2023)

A Multidisciplinary Lens of Bias in Hate Speech. - Paula Reyero Lobo; Joseph Kwarteng; Mayra Russo; Miriam Fahimi; Kristen M. Scott; Antonio Ferrara 003; Indira Sen; Miriam Fernández (ASONAM, 2023)

Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms. - Organizers Of QueerInAI; Nathaniel Dennler; Anaelia Ovalle; Ashwin Singh; Luca Soldaini; Arjun Subramonian; Huy Tu; William Agnew; Avijit Ghosh; Kyra Yee; Irene Font Peradejordi; Zeerak Talat; et al. (CoRR, 2023)

Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts. - José Alberto Benítez-Andrades; María Teresa García-Ordás; Mayra Russo; Ahmad Sakor; Luis Daniel Fernandes Rotger; Maria-Esther Vidal (Semantic Web, 2023)

Leveraging Ontologies to Document Bias in Data. - Mayra Russo; Maria-Esther Vidal (AEQUITAS@ECAI, 2024)

Bridging Research and Practice Through Conversation: Reflecting on Our Experience. - Mayra Russo; Mackenzie Jorgensen; Kristen M. Scott; Wendy Xu; Di H. Nguyen; Jessie Finocchiaro; Matthew Olckers (EAAMO, 2024)

Policy Advice and Best Practices on Bias and Fairness in Artificial Intelligence. - José M. Álvarez 002; Alejandra Bringas Colmenarejo; Alaa Elobaid; Simone Fabbrizzi; Miriam Fahimi; Antonio Ferrara 003; Siamak Ghodsi; Carlos Mougan; Ioanna Papageorgiou; Paula Reyero Lobo; Mayra Russo; Kristen M. Scott; et al. (EWAF, 2024)

Tracing the Impact of Bias in Link Prediction. - Mayra Russo; Sammy Fabian Sawischa; Maria-Esther Vidal (SAC, 2024)

Employing Hybrid AI Systems to Trace and Document Bias in ML Pipelines. - Mayra Russo; Yasharajsinh Chudasama; Disha Purohit; Sammy Sawischa; Maria-Esther Vidal (IEEE Access, 2024)

Articulation Work and Tinkering for Fairness in Machine Learning. - Miriam Fahimi; Mayra Russo; Kristen M. Scott; Maria-Esther Vidal; Bettina Berendt; Katharina Kinder-Kurlanda (Proc. ACM Hum. Comput. Interact., 2024)

Policy advice and best practices on bias and fairness in AI. - José M. Álvarez 002; Alejandra Bringas Colmenarejo; Alaa Elobaid; Simone Fabbrizzi; Miriam Fahimi; Antonio Ferrara 003; Siamak Ghodsi; Carlos Mougan; Ioanna Papageorgiou; Paula Reyero Lobo; Mayra Russo; Kristen M. Scott; et al. (Ethics Inf. Technol., 2024)

Tracing Bias for Fairer Content-Based Misinformation Detection. - Mayra Russo; Flavio Merenda; José Manuél Gómez-Pérez; Maria-Esther Vidal (WWW (Companion Volume), 2025)

Towards an Ontology-Driven Approach to Document Bias. - Mayra Russo; Maria-Esther Vidal (J. Artif. Intell. Res., 2025)