معرفی
Fernando Diaz is an Associate Professor at Carnegie Mellon University's Language Technologies Institute within the School of Computer Science. His research spans Information Retrieval, Recommender Systems, and the Societal Impacts of Artificial Intelligence, with a focus on fairness, ethics, and evaluation metrics.
- Education: PhD in Computer Science from University of Massachusetts Amherst
Research Interests include:
- Information Retrieval (web search, crisis informatics, search latency)
- Recommender Systems (multi-interest personalization, cultural content recommendation)
- AI Fairness (exposure fairness, data minimization, bias mitigation)
- Evaluation Methodology (metric robustness, contextual meta-evaluation)
- Human-AI Collaboration (mouse behavior analysis, preference-based evaluation)
- Retrieval-Augmented Generation (fair ranking, model synthesis)
His recent work analyzes scaling laws, tip-of-the-tongue retrieval, and multisided fairness in AI systems. Diaz also explores the cultural implications of AI in music recommendation and content curation.
- Teaching: Leads courses on Search Engines and LTI Colloquium
- Advisees: Shaily Jagat Bhatt, Athiya Deviyani, Alfredo Gomez, Jessica Huynh, To Eun Kim
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