Xuan Liang

Xuan Liang is a Lecturer in Statistics at the Research School of Finance, Actuarial Studies and Statistics (RSFAS), Australian National University. With a PhD from Peking University and postdoctoral experience at Monash University, his research focuses on spatial statistics, nonparametric modeling, and environmental data analysis.

• Education: PhD in Statistics (Peking University, 2017), BSc in Statistics (Zhejiang University, 2012)

His work addresses methodological challenges in spatial panel data analysis, network modeling, and air pollution quantification. He has developed novel techniques for meteorological confounder adjustment in air quality assessments and contributed to distributed data analysis methods.

Recent research trends include:

• Advancing quasi-score matching for spatial econometric models
• Improving subbagging algorithms for big data
• Creating robust distributed data aggregation frameworks
• Refining spatial autoregressive panel data methodologies

Scientific contributions include:

• ANU Vice-Chancellor’s Citation for Outstanding Contribution to Student Learning (Early Career), 2022
• CBE Teaching Commendation for Outstanding Teaching, 2020
• Co-development of the ggmatplot R package for matrix visualization
• Co-inventor of Chinese patent 201811183512.0 for air quality assessment

He teaches advanced courses in time series analysis, regression modeling, and mathematical statistics at ANU, while maintaining active research collaborations in econometrics and environmental statistics.