Dr. Nanwei Wang got his PhD in Statistics from York University in 2017. Supervised by Prof. Helene Massam, he mainly worked on the computation and the existence of MLE in high-dimensional discrete graphical models during his PhD. He joined Texas Tech University as a tenure-track assistant professor in 2021 after doing three years postdoctoral research in lunenfeld-tanenbaum research institute, Toronto and Pompeu Fabra University, Barcelona. His research interests are in statistics and statistical genetics, and especially in exploring the conditional independence relationship in high-dimensional problems. Currently, he is working on two projects:
- Mixed graphical model structure learning via Bayesian model selection methods and applying the results in genome-wide association studies
- Non-asymptotic analysis for different MLE methods and model selection algorithms.
Research interests: Graphical models; composite likelihood estimation; non-asymptotic statistical inference; Bayesian model selection