Explainable Collaborative Filtering Recommendations Enriched with Contextual Information. - Alexandra Vultureanu-Albisi; Costin Badica (ICSTCC, 2021)

Recommender Systems: An Explainable AI Perspective. - Alexandra Vultureanu-Albisi; Costin Badica (INISTA, 2021)

Improving Students' Performance by Interpretable Explanations using Ensemble Tree-Based Approaches. - Alexandra Vultureanu-Albisi; Costin Badica (SACI, 2021)

Optimizing Regularized Multiple Linear Regression Using Hyperparameter Tuning for Crime Rate Performance Prediction. - Alexandra Vultureanu-Albisi; Costin Badica (WorldCIST (1), 2021)

A survey on effects of adding explanations to recommender systems. - Alexandra Vultureanu-Albisi; Costin Badica (Concurr. Comput. Pract. Exp., 2022)

A Microservice-Based Multi-agent System for the Job Market. - Ionut Muraretu; Daniel-Costel Bouleanu; Alexandra Vultureanu-Albisi; Costin Badica; Dimitrios Sarafis; Kalliopi Kravari; Periklis Chatzimisios (IDC, 2023)

The Significance of Enhancing Data Fairness in Educational Recommender Systems. - Alexandra Vultureanu-Albisi; Costin Badica (RoEduNet, 2023)

Agent-Based Simulation Leveraging Declarative Modeling for Efficient Resource Allocation in Emergency Scenarios. - Ionut Muraretu; Alexandra Vultureanu-Albisi; Sorin Ilie; Costin Badica (AIMSA, 2024)

A Trustworthy and Explainable AI Recommender System: Job Domain Case Study. - Alexandra Vultureanu-Albisi; Ionut Muraretu; Costin Badica (INISTA, 2024)

eXING-IoT conceptual framework for explainability integration in next generation-IoT. - Alexandra Vultureanu-Albisi; Costin Badica; Mirjana Ivanovic (Connect. Sci., 2025)