Associate Professor at Mirpur University of Science and Technology, Pakistan
Dr. Aamir Saghir, an Associate Professor of Statistics at Mirpur University of Science and Technology (MUST), Pakistan, is a distinguished researcher in Statistical Quality Control, Data Analysis, and Probability Distributions. With a Ph.D. from Zhejiang University, China, and a post-doctoral fellowship from the University of Pannonia, Hungary, he has cultivated a strong international research presence. Dr. Saghir has authored over 60 research publications in reputed journals, including IEEE Access and Computers & Industrial Engineering, and co-authored a book with Wiley. He has successfully led funded research projects and supervised numerous M.Phil. and Ph.D. scholars. His leadership roles include department chairperson, treasurer, and chief librarian, reflecting a commitment to academic and administrative excellence. His future research focuses on integrating machine learning with statistical methods for anomaly detection. With proven academic contributions, strong mentorship, and impactful research, Dr. Saghir is a deserving candidate for the Best Researcher Award.
Professional Profile
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Education
Dr. Aamir Saghir has a strong academic background in the field of statistics, marked by excellence and international exposure. He earned his Ph.D. in Statistics from Zhejiang University, China (2011–2014), where he specialized in the development of flexible and robust control charts for statistical process monitoring under the supervision of Professor Zhengyan Lin. Prior to that, he completed his M.Phil. in Statistics from Quaid-i-Azam University, Islamabad (2006–2008), focusing on Bayesian and classical approaches to process parameter monitoring. He also earned his M.Sc. in Statistics from the same university (2004–2006), where he graduated with first position in his session. His academic journey began with a bachelor’s degree in Mathematics and Statistics from the University of Azad Jammu and Kashmir (2001–2003). Dr. Saghir’s education is marked by academic distinction and research depth, providing a solid foundation for his successful career as a researcher and educator in statistical sciences.Professional
Experience
Dr. Aamir Saghir brings over 17 years of diverse academic and research experience in the field of statistics. He is currently serving as an Associate Professor in the Department of Statistics at Mirpur University of Science and Technology (MUST), where he has also held administrative roles such as Chairperson, Treasurer, and Chief Librarian. He began his teaching career as a Lecturer at the University of Azad Jammu and Kashmir in 2006 and later joined MUST, where he progressed through the ranks from Lecturer to Assistant Professor, and then to Associate Professor. He also completed a prestigious post-doctoral research fellowship at the University of Pannonia, Hungary, further enhancing his international exposure. Dr. Saghir has been actively involved in both undergraduate and postgraduate teaching, curriculum development, and research supervision. His professional journey reflects a strong commitment to academic excellence, research innovation, and institutional development within Pakistan and abroad.
Research Interest
Dr. Aamir Saghir’s research interests lie at the intersection of statistical theory and modern data-driven applications. His primary focus is on Statistical Quality Control, where he develops innovative control charts and monitoring schemes to improve process efficiency and reliability. He has extensively worked on probability models, particularly weighted and mixture distributions, contributing to the theoretical advancement of distribution theory. In recent years, Dr. Saghir has expanded his research into data science and machine learning, with a special emphasis on anomaly detection in industrial processes and high-dimensional time series analysis. His work bridges classical statistical techniques with emerging computational methods, making his research highly relevant to fields such as industrial engineering, environmental science, and cyber-physical systems. With a strong foundation in both theoretical and applied statistics, Dr. Saghir continues to explore robust and adaptive statistical methods that address real-world challenges in process monitoring, environmental modeling, and complex data analysis.
Award and Honor
Dr. Aamir Saghir has received several prestigious awards and honors throughout his academic career, reflecting his excellence in research and education. He secured first position in his M.Sc. Statistics program at Quaid-i-Azam University, highlighting his early academic distinction. He was awarded the highly competitive China Scholarship Council (CSC) scholarship for his Ph.D. studies at Zhejiang University, where he also received a Distinguished Certificate in Statistics in recognition of his outstanding doctoral work. Dr. Saghir is also an HEC-approved Ph.D. supervisor, a testament to his academic credibility and mentoring capabilities. He has contributed significantly to applied research through funded projects and has served on the Board of Studies for statistics departments at multiple universities. His research contributions have been recognized internationally, and he is actively involved in organizing academic conferences and supervising impactful survey studies, such as the socio-economic impact of telecommunications in Pakistan. These honors reflect his dedication to advancing statistical science
Research Skill
Dr. Aamir Saghir’s research interests are rooted in both theoretical and applied statistics, with a strong emphasis on Statistical Quality Control, Probability Distributions, and Data Analysis. He has developed numerous robust and adaptive control charts for process monitoring, particularly useful in industrial and manufacturing settings. His work on weighted and mixture probability distributions has contributed significantly to statistical modeling, offering improved methods for analyzing non-normal and skewed data. Recently, Dr. Saghir has broadened his research scope to include machine learning techniques for anomaly detection, reflecting a forward-thinking approach to modern data challenges. He is particularly interested in the integration of data science methods with high-dimensional time series analysis, which has important applications in environmental monitoring, healthcare, and IoT-based systems. Through his interdisciplinary approach, Dr. Saghir aims to develop statistical tools that are not only theoretically sound but also practically impactful across various scientific and engineering domains.
Publications Top Noted
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Title: Phytoavailability of Cadmium (Cd) to Pak Choi (Brassica chinensis L.) Grown in Chinese Soils: A Model to Evaluate the Impact of Soil Cd Pollution on Potential Dietary Toxicity
Authors: M.T. Rafiq, R. Aziz, X. Yang, W. Xiao, P.J. Stoffella, A. Saghir, M. Azam, T. Li
Year: 2014
Citations: 74
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Title: Control Charts for Dispersed Count Data: An Overview
Authors: A. Saghir, Z. Lin
Year: 2015
Citations: 60
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Title: Weighted Distributions: A Brief Review, Perspective and Characterizations
Authors: A. Saghir, G.G. Hamedani, S. Tazeem, A. Khadim
Year: 2017
Citations: 49
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Title: Monitoring Process Variability Using Gini’s Mean Difference
Authors: M. Riaz, A. Saghirr
Year: 2007
Citations: 47
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Title: A Mean Deviation-Based Approach to Monitor Process Variability
Authors: M. Riaz, A. Saghir
Year: 2009
Citations: 43
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Title: A Control Chart for COM-Poisson Distribution Using a Modified EWMA Statistic
Authors: M. Aslam, A. Saghir, L. Ahmad, C.H. Jun, J. Hussain
Year: 2017
Citations: 33
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Title: Introduction to Statistical Process Control
Authors: M. Aslam, A. Saghir, L. Ahmad
Year: 2020
Citations: 31
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Title: A Flexible and Generalized Exponentially Weighted Moving Average Control Chart for Count Data
Authors: A. Saghir, Z. Lin
Year: 2014
Citations: 31
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Title: The Students’ Satisfaction in Higher Education and Its Important Factors: A Comparative Study Between Punjab and AJ&K, Pakistan
Authors: S. Hussain, M. Jabbar, Z. Hussain, Z. Rehman, A. Saghir
Year: 2014
Citations: 30
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Title: The Use of Probability Limits of COM–Poisson Charts and Their Applications
Authors: A. Saghir, Z. Lin, S.A. Abbasi, S. Ahmad
Year: 2013
Citations: 30
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Title: Monitoring Process Variation Using Modified EWMA
Authors: A. Saghir, M. Aslam, A. Faraz, L. Ahmad, C. Heuchenne
Year: 2020
Citations: 28
Conclusion
Dr. Aamir Saghir is highly deserving of the Best Researcher Award, given his robust academic foundation, extensive publication record, and valuable contributions to applied statistical science. His research spans both theoretical advancements and real-world applications, and he has significantly contributed to knowledge transfer, mentorship, and institutional development. With ongoing interests in data science and anomaly detection, he holds great promise for continued leadership in research and innovation on both national and international platforms.
