Zhanrui CAI

Zhanrui Cai is a researcher at The University of Hong Kong, specializing in statistical inference with privacy. Their work focuses on developing robust statistical methods for high-dimensional data analysis, including causal discovery, conditional independence tests, and model-free inference techniques. Cai's research integrates privacy-preserving methods, such as differential privacy, into statistical modeling and inference, particularly in genomics and machine learning. They have contributed to areas like synthetic data generation, feature screening, and change-point detection. Their publications emphasize statistical frameworks for handling complex data structures and ensuring reliable inference in high-dimensional settings.