Zhiyang is an Assistant Professor of Biostatistics in the Joseph J. Zilber College of Public Health at the University of Wisconsin-Milwaukee. Prior to the current appointment, he was an Assistant Professor in the Department of Statistics at the University of Manitoba. Zhiyang’s research is situated at the intersection of statistics and machine learning, focusing on the development of novel methods to enhance predictive performance and strengthen statistical inference. He also adapts and extends classical techniques to accommodate complex and heterogeneous data structures, applying rigorous statistical reasoning to address real-world challenges.

METHODOLOGICAL RESEARCH INTERESTS

• Functional data analysis (inference from trajectories, images, and complex data structures)
• Deep learning (leveraging multi-layer neural networks to approximate non-linear patterns)
• Transfer learning (applying knowledge from related domains to enhance inference)
• Survival analysis (modeling time-to-event data and estimating survival probabilities)
• Tensor data analysis (exploring multi-dimensional arrays to capture complex structures)
• Design of experiments (strategically planning and analyzing experiments)

COLLABORATIVE RESEARCH EXPERIENCE

Zhiyang has collaborated with investigators from many areas including the atmospheric science, cardiovascular disease, diabetes, infectious disease, mental health, and nutrition science.