Serina Chang
I recently completed my PhD in CS at Stanford, advised by Jure Leskovec and Johan Ugander. I look forward to starting at Berkeley in July 2025 as an Assistant Professor, with a joint appointment in EECS and Computational Precision Health! Before then, I'll be doing a postdoc at Microsoft Research NYC in the Computational Social Science group. I'm recruiting students from Berkeley EECS and CPH in Fall 2024, so please note my name in your application if you'd like to work with me.
My research falls at the intersection of AI, public health, and social science. Specifically, I develop AI methods to improve public health, understand human behavior, and guide data-driven policymaking. I'm interested in leveraging novel data sources - such as mobility data and search logs - to better understand human networks and behaviors at the center of societal challenges. These data sources provide new opportunities to capture individuals at scale, with the potential to improve decisions that affect billions every day. However, novel data also introduce new challenges, such as how to infer networks from aggregated data (Nature'21, ICML'24), estimate causal spillover effects of policies (AAAI'23), or extract precise behavioral signals from vast unlabeled data such as search logs (arXiv'23), speeches (PNAS'22), news articles (EMNLP'19), and social media (EMNLP'18). To address these challenges, I develop new methods blending machine learning, network science, and natural language processing. I use these methods to develop policy insights and tools (KDD'21, IAAI'22), which have been widely used by policymakers.
My work is recognized by a KDD Best Paper Award, NSF Graduate Research Fellowship, Meta PhD Fellowship, EECS Rising Stars, Rising Stars in Data Science, and Cornell Future Faculty Symposium, and has been featured by over 650 news outlets, including The New York Times and The Washington Post.
Recent News
- 🎓 Spring 2024: I graduated from Stanford and defended my dissertation! Special thanks to my thesis committee and all the wonderful people who have supported me throughout my PhD. Here are recordings of the Defense and Acknowledgements!
- 🎤 Jun 2024: invited talk at Oxford Networks Seminar.
- 🎤 Feb 2024: invited talk at AAAI'24 Workshop on Graphs and more Complex structures for Learning and Reasoning (GCLR).
- 🎤 Dec 2023: invited talk at the Network Science Institute at Northeastern.
- 🏆 Nov 2023: accepted to Rising Stars in Data Science, organized by University of Chicago and UCSD, and EECS Rising Stars at Georgia Tech!
- 🎤 Oct 2023: invited talk at the Stanford Graph Learning Workshop.
- 🏆 Sep 2023: accepted to the Cornell Future Faculty Symposium!
- 🎤 Aug 2023: I'm attending KDD 2023! I'm co-organizing the Data Science for Social Good Workshop (DSSG), presenting our work ⬇️ on search logs and vaccines, and moderating a panel at KDD EDI Day.