Published multiple papers including an arXiv paper on Bayesian optimized prompt engineering, and a formalization of multimedia recommendation through multimodal deep learning in ACM Transactions on Recommender Systems. Graduated with a Ph.D. cum laude. Won Best Short Paper - Runner Up at CIKM 2021 and MIT-IBM Watson AI Lab best paper award at AdvML@KDD 2021.
Research Experience
Worked for 3 years as an Applied Scientist at Amazon.com, focusing on Generative AI (Rufus and AmazonQ), Information Retrieval (Amazon Search), Recommender Systems, and Natural Language Processing. Completed a Summer Internship as an Applied Scientist at Amazon in the Amazon Search and Personalization Team, and a research visit at the Knowledge Media Institute under the supervision of Prof. Enrico Motta.
Education
Ph.D. from the Department of Electrical Engineering and Information Technology, Polytechnic University of Bari, supervised by Prof. Tommaso Di Noia.
Background
Working as a Science Manager at Cognism.com, leading a team of 5+ scientists. Research interests mainly focus on artificial intelligence, particularly Trustworthy AI and Generative AI. Special attention is given to recommender systems applications to study the robustness of modern ML recommender models affected by adversarial threats.