Professor Gedas Adomavicius

This research involves computational techniques for aiding decision-making in information-intensive environments, which includes personalization technologies and recommender systems, machine learning and data analytics, and electronic market mechanisms. Some specific studies include: understanding and quantifying bias in recommender systems, developing algorithms for special-purpose recommender systems, detecting meaningful patterns in various social network data, and others.