Daniel Verdi

Bio

Computational Social Science • Social Computing • Science of Science • Human-Centered AI

I apply data science methods, mainly natural language processing (NLP) and social network analysis, to study science and technology communication and governance. A focus of my work is what happens to academic knowledge once it leaves the lab: how it is translated for public audiences, amplified or distorted through digital media, and taken up in political debate. I’m particularly interested in how algorithmic systems like AI and social media are changing information ecosystems and how their own risks and benefits are transmitted to the public. At the core of my work is a commitment to questions of equity, ethics, and social justice.

Beyond conducting research, I am also passionate about designing tools and events to put science in conversation with communities and create opportunities for marginalized students to engage with research and technology. I’m especially interested in improving digital and AI literacies, as well as in using AI and other technologies in informal education.

Before Stanford, I graduated from the University of Richmond as a Richmond Scholar, the institution's most prestigious and competitive academic award. Additionally, I have conducted research at universities such as Carnegie Mellon, USC, and University of Copenhagen, and interned at Amazon Alexa AI. I’m also proud to have co-founded one of Brazil's largest high school science fairs, the Brazilian Fair of Young Scientists (FBJC), which has engaged over 2,000 participants and received over 1M website visits.