معرفی
Cristina Menghini is a postdoctoral researcher at Brown University's Data Science Institute, working with Prof. Stephen Bach in the BATS lab. Her research focuses on developing responsible AI systems, addressing technical challenges in model adaptation and ethical deployment. She holds a Ph.D. in Computer Engineering from Sapienza University (Italy), advised by Aris Anagnostopoulos and Stefano Leonardi, and a Master's in Data Science from Sapienza, with an exchange at EPFL's School of Computer and Communication Sciences. She also earned a Bachelor's in Statistics, Economics, and Finance from Sapienza.
Her research interests span AI ethics, pseudolabeling strategies for vision-language models like CLIP, zero-shot learning, network polarization analysis, and algorithmic fairness. Notable contributions include work on low-resource language AI, CLIP-based prompt tuning, and Wikipedia's structural bias. Her work has been recognized with awards at NeurIPS, WebSci, and WSDM conferences.
Menghini has contributed to projects such as TAGLETS (a semi-supervised learning system), RePBubLik (network polarization mitigation), and studies on social media discourse drifts. She actively participates in academic activities like organizing the WiDS datathon and presenting at venues like Amherst College and MLSys. Her research bridges technical innovation with societal implications, emphasizing ethical AI practices and inclusive algorithm design.
