Li Zeng is a PhD candidate at the University of Washington Information School (UW iSchool). She is also a PhD Student Fellow at the UW Data Science and Analytics Lab. Her research develops theory and methods for the analysis of large-scale social media data with a focus on how such data can be used to better understand human behavior and improve social systems, combining techniques from Machine Learning, Social Network Analysis, and Natural Language Processing. Her research has been published in AAAI ICWSM, IEEE HICSS, iConference and Field Methods. She is a Pre-Doctoral Lecturer at UW iSchool, teaching an undergraduate-level data science course and a graduate-level social media data mining course. Prior to her PhD, Li obtained a M.S. in Information Science from the University of Washington and a Bachelor’s degree in Information Management and Information Systems from Communication University of China. She has received several fellowships and awards including William and Ruth Gerberding Endowed Fellowship, the Chinese National Scholarship, China Central Television Scholarship, Tokyo Broadcasting System Television Inc. Scholarship, University of Washington Top Scholar Award, a Best Paper Award by the International Conference on Social Computing and Social Media, and a Lee Dirks Best Paper Award Finalist at the iConference.