Ibrahim Al Hazwani

Ibrahim's research aims at enhancing the recommender system experience through novel visualization approaches. In particular, his research looks at addressing the explainability goals proposed by Tintarev et al., including transparency, scrutability, trust, effectiveness, persuasiveness, efficiency, and satisfaction. He aims to achieve this through interactive data visualizations based on Data Humanism principles proposed by Lupi in 2017, which prioritize the human aspects of data representation over purely algorithmic approaches. By creating personalized, context-aware visualizations that reveal the underlying patterns and relationships within recommendation systems, his work bridges the gap between complex algorithmic processes and user understanding. This human-centered approach not only improves the interpretability of recommendations but also the overall user experience.

Ibrahim holds an M.Sc. in Computational Data Science from the Free University of Bozen-Bolzano and a B.Sc. in Biomedical Engineering from the University of Bologna.

His professional experience spans several industries and roles. At the LEGO Group, he worked as a Data Scientist for his Master's thesis analyzing over 100,000 comments from online forums.  As a Data Engineer at Humanitas Research Hospital, he created reports using SAP BO, crafted interactive dashboards with PowerBI and Tableau. Additionally, he develop his UI/UX skills at the Apple Developer Academy in Naples, where he used Challenge-Based Learning methodology to design iOS applications addressing societal issues while collaborating with Apple Evangelists on critical thinking and presentation skills.