Deep behavioral and machine learning analysis explaining why mobile users systematically report lower satisfaction with AI systems. Includes SHAP explainability, cognitive load modeling, device-context effects, interaction metadata analysis, and end-to-end reproducible research code and visuals.

This study explores the link between eating disorders and online communities, analyzing user interactions on Twitter for insights into prevention and detection strategies. Is the real-life relationship reflected in social media interactions?

Group-Level Main Effects and Interactions in High-Dimensional Data.

Psychiatry-informed research workspace for configurable analysis of human-AI interaction patterns.

EKEEL Learning Analytics — Learning analytics model for data pattern recognition and usage behavior modeling (Deliverable D4.1)

End-to-end pharmacogenomic workflow identifying miRNA modifiers of ICS response in childhood asthma.

Dual FAISS indices: semantic (text) + structural (primitives). Segment registry, query CLI. Behavior-first retrieval combining interaction mechanics + semantic similarity.

Input Regime Comparison

All-in-one web platform for protein pocket prediction, ligand docking, ADMET profiling, and MM-GBSA rescoring — powered by P2Rank, AutoDock Vina, RDKit, and OpenMM.

Non-semantic structural measurement

Beyond Content: Papers

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