Rate My Professor Shuangzhe Liu

Shuangzhe Liu is an Associate Professor in the Faculty of Science and Technology at the University of Canberra, where he joined in 2003. He earned his doctorate in econometrics from the Tinbergen Institute at the University of Amsterdam, the Netherlands, under the supervision of Professor Heinz Neudecker. Prior to his current position, Liu worked at the University of Basel in Switzerland and the Australian National University. He teaches a number of statistics units for both undergraduate and postgraduate students and leads research efforts in statistical modeling and data analytics.

Liu's research specializations encompass distribution theory and its applications, financial, insurance, and environmental statistics and data analytics, as well as matrix differential calculus. With 184 research outputs, including 124 articles, his work has garnered over 3,000 citations on Google Scholar. Key publications include 'A shape-enhanced outlier-detection framework for regression tasks' (Xiong, Han, Ma, and Liu, 2026, Knowledge-Based Systems), 'Tri-SEM: A shape-aware robust regression method via chain-like segmentation and residual analysis' (Xiong, Han, Ma, and Liu, 2026, Pattern Recognition), 'Addressing the omitted variables problem in a three-equation linear system' (Xiong, Ma, and Liu, 2025, Journal of Statistical Computation and Simulation), 'Shrinkage estimation in geographically weighted regression with applications to digital platform pricing' (Yüzbaşı, Ahmed, and Liu, 2026, Spatial Statistics), and 'A saddle point-guided clustering algorithm for data with complex structure' (Huang, Jin, Zhuang, Ma, van de Velden, and Liu, 2025, Knowledge-Based Systems). He serves as a reviewer for more than 35 mathematics, statistics, econometrics, and other journals and as an associate editor for four international journals. Liu's contributions have advanced areas such as outlier detection, robust regression, model diagnostics, and multivariate statistical analysis, influencing statistical and econometric methodologies.