Matthew J. Salganik

Matthew J. Salganik is the Alexander Stewart 1886 Professor of Sociology at Princeton University, with affiliations in the Office of Population Research and the Center for Statistics and Machine Learning. His research focuses on computational social science, social networks, and the ethical implications of algorithmic prediction. He has contributed to methodologies for estimating hidden populations, improving survey techniques, and advancing machine learning applications in public health and cultural studies.

• Research Interests: Social networks, computational methods, algorithmic prediction, cultural markets, differential privacy
• Awards: Outstanding Article Award (2×), Outstanding Statistical Application Award
• Funding Sources: NSF, NIH, UNAIDS, Russell Sage Foundation

Salganik’s work bridges academia and industry, with visiting roles at Cornell Tech, Microsoft Research, and the New York Times. He emphasizes reproducibility in research, leading initiatives like the Fragile Families Challenge, and publishes widely in journals such as Science and PNAS. His book Bit by Bit: Social Research in the Digital Age explores modern social research methodologies.

Current projects include validating mortality predictions using machine learning and exploring the ethics of life outcome forecasting. He serves on the Board of Mathematica and advocates for transparent reporting standards in computational science.