Dan Zhu

Dr. Dan Zhu is a Professor in the Department of Econometrics and Business Statistics at Monash University. She holds a PhD in Financial Mathematics and Actuarial Science from the University of Melbourne's Economics department. Her research focuses on numerical methods for sensitivity analysis, financial mathematics, Bayesian analysis, and stochastic dynamical systems optimization. She has led multiple research projects including 'Efficient Bayesian Markov chain Monte-Carlo for Ultra-High-Dimensional Time Series' (2025) and contributed to initiatives like the 'Carer payments assessment process' (2024–2025).

Key areas of expertise include Bayesian VAR models, macroeconomic forecasting, and financial risk analysis. Her work frequently addresses computational challenges in high-dimensional statistical models, with applications to policy analysis and financial engineering. Notable collaborations span institutions including CSIRO Data61 and the Australian Research Council.

Dr. Zhu’s recent research emphasizes structural analysis of vector autoregressions, quantile-based forecasting methods, and the integration of climate variables into macroeconomic risk frameworks. Her methodologies have advanced sensitivity analysis techniques critical for robust policy evaluation and financial decision-making.