Data Science/Computational Social Science Seminar: Xuan Lu
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 get prepared 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 on the open-source software development community and 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 research fellow at the School of Information, the University of Michigan. She earned her PhD in computer science from Peking University. Her research interest lies in creating novel methodologies of human-centered data science and using them to understand and optimize the activities and outcomes (related to work, education, healthcare, etc.) of our future human society, especially those triggered by technology innovations. In particular, her recent work has focused on the domain of the Future of Work. Her work has been published in top conferences such as the Web conference, UbiComp, ICWSM, IMC, and ICSE, and top-tier journals such as TSE, TOSEM, and TMC. She is a recipient of the WWW Best Paper Award in 2019 and the Microsoft Research Asia Fellowship in 2017.