When
Thursday, April 23, 2026, at 2:00 p.m.
Xuan Lu
Assistant Professor
College of Information Science
University of Arizona
"The Future of Work: From Human Signals to AI-Supported Scientific Discovery"
ENGR 301
Abstract: Recent years have witnessed major transformations in how work is communicated, organized and performed, from the rise of remote work during the COVID-19 pandemic to the growing role of AI in the workplace. With data accumulated through these changes, it is crucial to involve data science methodologies to understand them, predict their outcomes and prepare for future developments. In this talk, I will introduce a comprehensive human-centered data science approach (especially featuring machine learning and causal inference) for studying the future of work across multiple settings. First, I examine how socio-emotional signals such as emoji use reduce dropout in remote collaboration on GitHub and what team characteristics contribute to resilience under external shocks. Second, I show how a hybrid work strategy, as a form of organizational design, influences individual career outcomes of turnover and promotion using data from a real-world company. Finally, using scientific research as a specific form of work, I discuss how large language models can be used to extract causal knowledge from scientific literature, a fundamental step in scientific discovery, offering an initial view of how AI may reshape the future of work.
Bio: Xuan Lu is an assistant professor in the College of Information Science at the University of Arizona. Her research focuses on creating novel methodologies of human-centered data science and using them to understand and optimize the activities and outcomes of our future human society, especially those triggered by technology innovations, with a recent emphasis on the domain of Future of Work. Her work has been published in multiple leading conferences and journals in data science and related fields and she is a recipient of the WWW Best Paper Award (2019) and the Microsoft Research Asia Fellowship (2017).