Michael Ekstrand

Michael Ekstrand is an Assistant Professor in the Department of Information Science at Drexel University's College of Computing & Informatics, where he leads the INERTIA Laboratory (Impact, Novation, Effectiveness, and Responsibility of Technology for Information Access). His research blends information retrieval, human-computer interaction, and machine learning to ensure AI-powered information access systems (e.g., recommender systems) promote equity and societal well-being. Previously, he co-led the People and Information Research Team (PIReT) at Boise State University.

Education: PhD in Computer Science (University of Minnesota, 2014), BS in Computer Engineering (Iowa State University).

Research Focus: Ekstrand's work centers on fairness-aware algorithms, social impact quantification, and ethical AI deployment. Key themes include:

• Algorithmic bias mitigation in recommender systems
• User behavior modeling in information access
• Cross-disciplinary approaches to AI ethics
• Evaluation methodologies for equitable systems

Publication Trends: His recent articles (2020-2025) demonstrate a strong focus on algorithmic fairness, particularly gender bias in information systems, statistical evaluation rigor, and user behavior analysis. Over 50% of his latest works directly address fairness metrics or bias mitigation strategies.

Advising & Grants: Actively mentors PhD students (e.g., Samira Vaez Barenji, Sushobhan Parajuli) and has supervised 11+ graduate researchers. Secured NSF CAREER funding for projects on recommender systems' societal impact.

Leadership: Maintains LensKit (open-source recommender toolkit), holds roles in ACM RecSys/FAccT conferences, and directs the INERTIA lab focusing on responsible information access technologies.