Yiou Li earned her Ph.D. in Applied Mathematics from the Illinois
Institute of Technology in 2014. Prior to her appointment as an Assistant Professor, Li taught graduate-level statistics courses in the Department of Mathematical Sciences as an adjunct professor in 2013, and then as a Visiting Assistant Professor from 2014 to 2016.
Li's research interests are in statistics and computational mathematics. Specifically, Li works on developing new theories and methodologies in the statistical design of experiments, statistical learning, uncertainty quantification, and optimization. Li is also passionate about and has been working on interdisciplinary topics that apply statistical modeling and data science in economics and finance.
Selected Publications:
- A Maximin Phi_p-Efficient Design for Multivariate GLM. Statistica Sinica (2021), https://doi.org/10.5705/ss.202020.0278, (with L. Kang and X. Deng).
- Financial Contagion and Contagion Channels in the Forex Market: A New Approach via the Dynamic Mixture Copula-Extreme Value Theory. Economic Modelling (2021), 94, 401-414, (with H. Wang, Y. Yuan, and X. Wang).
- Are Transformed Low Discrepancy Points Also Low Discrepancy? Contemporary Experimental Design, Multivariate Analysis and Data Mining (2020), Springer, 69-92, (with L. Kang and F.J. Hickernell).
- An Efficient Algorithm for Elastic I-Optimal Design of Generalized Linear Models. The Canadian Journal of Statistics (2020), https://doi.org/10.1002/cjs.11571, (with X. Deng).