Mahdi Teimouri is an Assistant Professor in Statistics at Gonbad Kavous University in Iran. He obtained his Ph.D. in Statistics from Amirkabir University of Technology, where his thesis focused on clustering of stable data. Prior to his doctoral studies, he completed his M.Sc. and B.Sc. in Statistics from the same university. Dr. Teimouri’s research interests include machine learning, computational statistics, statistical signal processing, statistical inference, biostatistics, and statistics in forestry. He has been actively involved in various research projects and has received honors and awards for his contributions to the field of statistics. Dr. Teimouri has also presented his work at international conferences and has published numerous papers in reputable journals. In addition to his academic endeavors, he has developed several R packages and served on scientific committees. His dedication to teaching is evident through the diverse range of courses he has taught, covering topics such as statistical methods, regression analysis, and nonparametric statistics. Dr. Teimouri’s expertise and contributions make him a valuable asset to the field of statistics.
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🎓 Education:
Dr. Mahdi Teimouri pursued his academic journey in Statistics, culminating in a Ph.D. from Amirkabir University of Technology in Iran, awarded between 2013 and 2017. Prior to his doctoral studies, he completed his Master’s degree in Statistics at the same university from 2001 to 2003. His foundational education includes a Bachelor’s degree in Statistics from Shahid Bahonar University of Kerman, Iran, attained from 1998 to 2001.
đź’Ľ Experience:
Dr. Mahdi Teimouri currently holds the position of Assistant Professor in Statistics at Gonbad Kavous University, Iran, a role he has dedicated himself to since 2009. Over the years, he has made significant contributions to the field of statistics through his teaching, research, and academic leadership.
🏆 Honours and Awards:
In 2013, Dr. Mahdi Teimouri was honored as one of the recipients of the Wakimoto Memorial Fund in Hong Kong. This prestigious award recognized his outstanding achievements and contributions to the field of statistics, further highlighting his dedication and excellence in the discipline.
Publication Top Notes:
- Title: Comparison of estimation methods for the Weibull distribution
Authors: M Teimouri, SM Hoseini, S Nadarajah
Journal: Statistics, 47 (1), 93-109
Cited By: 149
Year: 2013
- Title: On the three-parameter Weibull distribution shape parameter estimation
Authors: M Teimouri, AK Gupta
Journal: Journal of Data Science, 11 (3), 403-414
Cited By: 75
Year: 2013
- Title: Modified beta distributions
Authors: S Nadarajah, M Teimouri, SH Shih
Journal: Sankhya B, 76, 19-48
Cited By: 32
Year: 2014
- Title: Bias corrected MLEs for the Weibull distribution based on records
Authors: M Teimouri, S Nadarajah
Journal: Statistical Methodology, 13, 12-24
Cited By: 28
Year: 2013
- Title: Estimation methods for the Gompertz–Makeham distribution under progressively type-I interval censoring scheme
Authors: M Teimouri, AK Gupta
Journal: National Academy Science Letters, 35, 227-235
Cited By: 21
Year: 2012