معرفی
Professor Amjad Al-Nasser serves as a faculty member in the Statistics Department at Yarmouk University's Faculty of Science in Jordan. His administrative career includes significant leadership roles as Vice Dean of the Faculty of Science and previously as Vice Dean of Research and Graduate Studies at Yarmouk University. In 2020, he held the position of Vice President for Academic Affairs at Al Falah University, demonstrating extensive experience in academic administration across multiple Jordanian institutions.
Dr. Al-Nasser's primary research interests revolve around Generalized Maximum Entropy and Directional Data Statistics, with substantial contributions to statistical distribution theory and methodology. His work spans theoretical developments in probability distributions including the GOLD distribution, Poisson-Gold distribution, and various generalized forms of exponential and Weibull distributions. He has pioneered applications of entropy measures in statistical modeling and has made significant contributions to acceptance sampling plans, particularly for truncated life tests across diverse industrial contexts.
The analysis of his recent publications reveals a strong focus on developing novel statistical distributions and refining sampling methodologies. His research demonstrates consistent innovation in adapting entropy principles to practical statistical problems, with applications spanning manufacturing quality control, social media analysis, epidemiological modeling, and engineering reliability. The interdisciplinary nature of his work connects statistical theory with real-world applications in public health, industrial engineering, and social sciences.
Throughout his career, Professor Al-Nasser has maintained active engagement with statistical methodology development, with recent publications showing continued productivity in distribution theory and quality control applications. His work bridges theoretical statistical advancements with practical implementation across multiple domains, reflecting both depth in statistical theory and breadth in application areas.
