Shariati, Ali

Dr Ali Shariati is a statistician at the School of Mathematics and Statistics, The University of New South Wales. His expertise lies in developing statistical methodologies for inference on real-world phenomena, with a focus on medical research and epidemiology. His research spans Survival Analysis, Stochastic Processes, Point Processes, Nonparametric Statistics, and Empirical Likelihood. Ali’s work focuses on developing statistical methods for complex and challenging data scenarios. In Survival Analysis, he investigates functionals of empirical processes, particularly in data subject to selection bias and informative censoring, which has significant applications in Prevalent Cohort studies. Additionally, he is working on statistical inference for Stochastic Point Processes, specifically Hawkes Processes, under incomplete data settings, with applications across various disciplines.

Ali Shariati is a researcher in the School of Mathematics and Statistics at the University of New South Wales (UNSW), specializing in Survival Analysis, Stochastic Processes, Nonparametric Statistics, and Mathematical Statistics. His work focuses on statistical methods for analyzing censored and length-biased data, with applications in medical and health sciences. He has published extensively on empirical likelihood methods, hazard function estimation, and goodness-of-fit tests in decreasing densities. His research also extends to nonparametric inference in biased sampling scenarios, including studies on prevalent cohort survival data and dementia life expectancy. Shariati's contributions emphasize robust statistical techniques for complex real-world data.