Alireza Javadian Sabet
Computational social scientist studying how transformative AI reshapes labor markets and innovation systems using large-scale datasets and empirical modeling.
Bio
Alireza Javadian Sabet is an incoming Postdoctoral Scholar at the University of Chicago Knowledge Lab and a Digital Fellow at Stanford’s Digital Economy Lab. He earned a PhD in Information Science from the Resilient Economy Lab at the University of Pittsburgh, where his research focused on mapping career adaptability and understanding how skills and experience translate into changing sets of opportunities over time. He also holds a master’s degree in Computer Science and Engineering from Politecnico di Milano (PoliMi) and previously served as a research fellow at PoliMi’s Data Science Lab and the DEpendable Evolvable Pervasive Software Engineering group. His work has been discussed in policy and business outlets, including The Economist and the American Enterprise Institute.
Research Summary
Alireza studies how transformative AI reshapes labor markets and innovation systems, developing models and measures from large-scale datasets that link technological capabilities to changes in skills, mobility, and knowledge production. His work combines text and trajectory data to track skill formation in education, quantify how career opportunities expand or concentrate over time, and connect these dynamics to the movement of talent across organizations and borders. He is motivated by the broader challenge of assessing and predicting technology outcomes, including how advances diffuse through tasks and institutions, and how choices around funding, training, and governance influence who benefits from technological change.