User Behavior Modeling

Behavior modeling focuses on understanding and predicting user interactions with AI systems through behavioral signals and interaction patterns. Key work includes developing models for search result prefetching using cursor movements and viewport behavior, studying mobile query reformulation patterns across different input modalities, and analyzing the economic and cognitive costs of annoying advertisements. The research encompasses interactive search, mouse movement modeling, and understanding how various interface elements affect user engagement and click-through behavior. These studies provide insights into user attention patterns and inform the design of more effective AI systems.