Yubo (Mars) Zhou
📧 [email protected] ｜ Google Scholar ｜ CV
Master of Information Science Student
University of Michigan, School of Information
I am a Master of Information Science student (thesis track) at the University of Michigan School of Information, advised by Prof. Ceren Budak and working with Prof. Anhong Guo and Prof. Yulin Yu. I study how algorithmic and AI-mediated interventions shape participation and user agency in online communities, with particular attention to heterogeneous effects: who benefits, who does not, and why. I combine causal inference and large-scale experiments with human-centered design to translate these findings into better platform mechanisms.
Before Michigan, I received my B.S. (First Class Honours) in Business Computing and Data Analytics from Hong Kong Baptist University, where I worked with Prof. Jianliang Xu and Prof. Renchi Yang.
Beyond research, I care about putting these ideas into practice — through teaching, mentoring, and building scholarly communities.
Explore my research, publications, teaching, service, and awards.
Research Interests
- Computational social science and online communities
- Causal inference and large-scale field experiments
- Human-AI interaction and user agency
Selected Publications
- Yubo Zhou, Pengyu Chen, Ceren Budak. "Who Benefits from Wikipedia's Growth Mentorship? The Role of Newcomer Information Needs." ICWSM, 2026.
- Haoran Zheng, Renchi Yang, Yubo Zhou, Jianliang Xu. "Rethinking Message Passing Neural Networks with Diffusion Distance-Guided Stress Majorization." ACM SIGKDD, 2025.
View full publication list →
Selected Awards
- HKSAR Government Scholarship (top recipients)
- Teresa Noel Urban Blaurock Student Research Award, University of Michigan
- ETHGlobal Brussels — World Top 10 Finalist (top award)
- Mathematical Contest in Modeling — Meritorious Winner (top 2–7%)