Data Science Talk Series 

Title: Towards Sustainable Remote Work: A Practice of Human-Centered Data Science 

Abstract: The COVID-19 pandemic has dramatically accelerated the decentralization processes of organizations, such as the transition from in-person workplaces to remote work. With data accumulated through these emergent changes on both the organization side and the worker side, it is crucial to involve data science methodologies to understand these changes, 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) to analyzing and improving the sustainability of remote workers and teams. In particular, the presented work will focus primarily on the open-source software development community analyze the factors that affect the sustainability of virtual teams under shock, and promote the long-term contribution of individual developers.

Speaker Bio: Xuan Lu is a tenure-track assistant professor at 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 technological innovations, with a recent emphasis on the domain of the Future of Work. Her work has been published in multiple leading conferences and journals in the field of data science, and she is a recipient of the WWW Best Paper Award (2019) and the Microsoft Research Asia Fellowship (2017).