Dr. Mehrdad is a Lecturer in Statistics at the School of Engineering, Physics, and Mathematics, ֲýƵ. He earned his PhD from Shahid Bahonar University of Kerman in 2017. Before joining ֲýƵ in 2023, Dr. Mehrdad gained extensive international research experience through five years of postdoctoral fellowships at prestigious institutions:
- Institute of Statistics, Department of Applied Mathematics, National Chung Hsing University, Taiwan (November 2021 – January 2023)
- Department of Statistics, Ferdowsi University of Mashhad, Iran (March 2021 – November 2021)
- Department of Statistics, University of Pretoria, South Africa (November 2018 – February 2021)
His statistical research primarily is in the related fields of classification, cluster analyses, factor analysis, linear modeling, as well as multivariate and matrix-variate analyses in the field of applied statistical inference. He focuses on using finite mixture models and on estimation via the EM algorithm. A common theme of his research in these fields has been statistical computation, with particular attention being given to the methodology of distribution theory.
- Model-based clustering of high-dimensional incomplete data via contaminated-normal mixtures, Shahriari, L., Naderi, M., Khosravi, M. 1 Nov 2025, In: Advances in Data Analysis and Classification
- Robust Bayesian inference for the censored mixture of experts model using heavy-tailed distributions, Mirfarah, E., Naderi, M., Lin, T., Wang, W. 1 Dec 2025, In: Advances in Data Analysis and Classification
- Clustering asymmetrical data with outliers: Parsimonious mixtures of contaminated mean-mixture of normal distributions, Naderi, M., Nooghabi, M. 1 Feb 2024, In: Journal of Computational and Applied Mathematics
- Three-way data clustering based on the mean-mixture of matrix-variate normal distributions, Naderi, M., Tamandi, M., Mirfarah, E., Wang, W., Lin, T. 1 Nov 2024, In: Computational Statistics and Data Analysis
- Robust mixture regression modeling based on the normal mean-variance mixture distributions, Naderi, M., Mirfarah, E., Wang, W., Lin, T. 1 Apr 2023, In: Computational Statistics and Data Analysis
- Multivariate measurement error models with normal mean-variance mixture distributions, Mirfarah, E., Naderi, M., Lin, T., Wang, W. 1 Dec 2022, In: Stat
- Semiparametric inference for the scale-mixture of normal partial linear regression model with censored data, Naderi, M., Mirfarah, E., Bernhardt, M., Chen, D. 10 Sep 2022, In: Journal of Applied Statistics
- Stress–strength reliability inference for the Pareto distribution with outliers, Jabbari Nooghabi, M., Naderi, M. 1 Apr 2022, In: Journal of Computational and Applied Mathematics
- A flexible factor analysis based on the class of mean-mixture of normal distributions, Hashemi, F., Naderi, M., Jamalizadeh, A., Bekker, A. 1 May 2021, In: Computational Statistics Data Analysis
- Mixture of linear experts model for censored data: A novel approach with scale-mixture of normal distributions, Mirfarah, E., Naderi, M., Chen, D. 1 Jun 2021, In: Computational Statistics and Data Analysis
Mathematical Statistics PhD
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