معرفی
Jinzhou Li is a Postdoctoral Scholar in the Department of Statistics at Stanford University, advised by Emmanuel Candès. Previously, he earned his PhD from ETH Zürich under the supervision of Marloes Maathuis and Nicolai Meinshausen. His research focuses on developing reliable statistical methodologies for uncovering conditional independence relations and causal mechanisms, with applications in genomics, epidemiology, and econometrics. He emphasizes rigorous error-rate control in his methods, such as false discovery rate (FDR) control and simultaneous error bounds.
Education
- PhD in Statistics, ETH Zürich (2022), Advisors: Marloes Maathuis and Nicolai Meinshausen
- Postdoctoral Fellowship, Stanford University (2022–present), Mentor: Emmanuel Candès
Research Interests
Li’s work addresses challenges in causal inference, high-dimensional statistics, and error-controlled learning. He designs methods to identify causal relationships in complex systems (e.g., gene networks, disease mechanisms) and quantifies uncertainty through FDR control. His applications span genetics, public health (e.g., SARS-CoV-2 monitoring), and policy analysis (e.g., effects of education).
Publications
Recent work highlights include causal discovery algorithms, FDR control in graphical models, and R package development for epidemic monitoring. His research bridges theory and practice, with contributions to both statistical methodology and domain-specific solutions.
Advising & Grants
While currently focused on postdoctoral research, Li’s work has been supported by grants from institutions including Stanford and ETH Zürich. He has not yet listed formal advisees.
