Serina Chang is a 5th year PhD student in Computer Science at Stanford University. She develops methods in machine learning and data science to tackle complex policy problems in public health and society. Her research focuses on large-scale human networks and novel data sensors, such as mobility networks from location data and query-click graphs from search engines. Her work has been published in venues including Nature, PNAS, KDD, AAAI, and EMNLP and featured in media outlets such as The New York Times and The Washington Post. Her work is also recognized by the KDD 2021 Best Paper Award, Meta PhD Fellowship, NSF Graduate Research Fellowship, EECS Rising Stars, Rising Stars in Data Science, and CRA Outstanding Undergraduate Researcher Award. Previously, Serina received her B.A. at Columbia University, where she studied Computer Science and Sociology.