معرفی
Yabo Niu is an Assistant Professor and Presidential Frontier Faculty in the Department of Mathematics at the University of Houston, with a joint appointment in the Department of Health Systems & Population Health Sciences within the Tilman J. Fertitta Family College of Medicine. They hold a Ph.D. in Statistics from Texas A&M University (2019) and a B.S. in Statistics from Nankai University, China (2013). Their research focuses on Bayesian statistical methods, including graphical models, nonparametric approaches, variable selection, and tree-based regression/classification techniques.
Recent contributions include the 2024 JASA Reproducibility Award-winning paper on covariate-assisted Bayesian graph learning for heterogeneous data. Dr. Niu has developed novel methodologies in network modeling and hybrid estimation techniques (e.g., EPSOM-Hyb). Their work bridges statistical theory with applications in health systems, neuroscience, and genomics. In 2024, they introduced a new Bayesian Statistics course (MATH 6397) at the University of Houston.
- Education:
- Ph.D. in Statistics, Texas A&M University (2014–2019)
- B.S. in Statistics, Nankai University (2009–2013)
- Research Highlights:
- Developed robust high-dimensional network modeling frameworks
- Advanced Bayesian approaches for heterogeneous data integration
- Investigated astrocyte structural plasticity using machine learning
- Teaching: Bayesian Statistics course (Spring 2024)
Current research emphasizes integrating omics data and advancing reproducible statistical practices. Dr. Niu’s group includes postdoctoral researchers like Ji Shi (jointly supervised with Demetrio Labate and Peng Zhao).
