
About
Yushu Li is an Associate Professor in the Department of Mathematics at the University of Bergen. His research spans statistics, data science, and econometrics, with a focus on wavelet methods, sparse Bayesian learning, and statistical surveillance. He has taught courses like Monte Carlo Methods, Statistical Learning, and Theory of Finance at institutions including the University of Bergen (UIB), Norwegian School of Economics (NHH), and NTNU.
Research Interests:
- Wavelet analysis for time series and econometrics
- Sparse Bayesian learning for statistical modeling
- Density forecasting and statistical surveillance
- Machine learning applications in finance and economics
Recent Publications: His 2024 work on Sparse Bayesian learning using TMB and forecasting milk delivery highlights his contributions to computational statistics and agricultural economics. Earlier studies on oil price volatility, structural breaks, and unit root testing underscore his expertise in nonlinear time series and financial modeling.
Supervision: He has supervised 1 Ph.D. project (Ingvild M. Helgøy, 2023) and over 10 master's theses since 2012, including topics on density forecasting, wavelet methods, and machine learning classifiers.
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