Daniel Lobo is a PhD student in the Department of Sociology at UC Berkeley. Historically, his research interests have been in education inequality in K-12 and higher education, with a focus on the life outcomes of low-income students. Lobo is currently interested in two lines of research: the global political economy of higher education and the effects of social media on cultural production and reproduction. Epistemologically, he seeks to leverage big data and machine learning to bridge disciplines in his research and to ask predictive questions in the social sciences. As a CSSTP fellow, Lobo looks forward to learning about the ethics of computational methods, developing his quantitative skillset under the mentorship of Berkeley data science faculty, and being in fellowship with a diverse, talented group of interdisciplinary peers. Outside of the academy, he enjoys mentoring first-generation, low-income students of color. Lobo identifies as Black, queer, and working class. He holds a BA in Social Studies, with high honors, from Harvard College.
Causal Inference, Culture, Education, Race & Inequality, Social Media