Research Scientist at Facebook Research - Core Data Science
I am currently a research scientist at at Facebook Research - Core Data Science Team. I received my Ph.D. in Statistics with minor in Computer Science from University of Wisconsin-Madison, advised by Prof. Karl Rohe. My research interests are in Machine Learning research including Social Network Analysis, Spectral Clustering, Community Detection, Network Driven Sampling, Natural Language Processing, Domain Adaptation, and Ranking Algorithms.
- Yilin Zhang, Karl Rohe. "Understanding Regularized Spectral Clustering via Graph Conductance", Proceedings of Neural Information Processing Systems (NeurIPS), 2018. [pdf][poster][video]
- Yilin Zhang, Marie Poux-Berthe, Chris Wells, Karolina Koc-Michalska, Karl Rohe. "Discovering Political Topics in Facebook Discussion threads with Graph Contextualization", The Annals of Applied Statistics, 12(2), 1096-1123, 2018. [pdf][R package: pairGraphText][code][shinyapp]
- Hao Henry Zhou, Yilin Zhang, Vamsi K. Ithapu, Sterling C. Johnson, Grace Wahba, Vikas Singh. "When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications", Proceedings of International Conference on Machine Learning (ICML), 2017.[pdf][supp][code][slides]
- Yilin Zhang, Karl Rohe, Sebastien Roch. "Reducing Seed Bias in Respondent-Driven Sampling by Estimating Block Transition Probabilities", under review at The Annals of Statistics.
- Yilin Zhang. "Community Detection and Sampling on Networks", Ph.D. Thesis.
- Xing-Jiang Zhu, Linqing Wen, George Hobbs, Yilin Zhang, et al. "Detection and Localization of Single-Source Gravitational Waves with Pulsar Timing Arrays", Monthly Notices of the Royal Astronomical Society, 449:16501663, 2015.
- Yilin Zhang, Qing Li, Charles Franklin, Karl Rohe. "Direct Evidence for Null Volatility in Election Polling". preprint.