I am Felice Antonio Merra a PhD Student working on Security and Adversarial Machine Learning on Recommender Systems. I am earning my PhD in Computer Science and Engineering at the Department of Electrical Engineering and Information Technology, Polytechnic University of Bari working with Prof. Tommaso Di Noia.

My research activities mainly focus on artificial intelligence (AI). My investigation is devoted to novel approaches and applying machine learning (ML) algorithms, particularly to Trustworthy AI. In particular, I devote my attention to recommender system (RS) applications to study the robustness of modern ML recommender models affected by adversarial threats. After having assessed the state-of-the-art of AML techniques in RS, I have investigated three main areas of study: (i) the robustness of recommender models when affected by hand-engineered shilling attacks, (ii) the formal study of the effects of AML training strategies on the beyond-accuracy effects of recommenders, i.e., bias disparity, fairness, novelty, and (iii) the proposal of adversarial attacks against multimedia retrieval models. In the future, I plan to extend the previous line of study and continue to investigate AML approaches on other ML tasks, e.g., computer vision and reinforcement learning, with the aim to bridge the final users’ at the core of my research to verify how much they can trust an ML system.