Assist. Prof. Dr. Jorge Muniz Junior | Operations Management | Research Excellence Award

Full Professor at São Paulo State University | Brazil

Assist. Prof. Dr. Jorge Muniz Junior is a leading researcher in production engineering, specializing in Industry 4.0, Social Systems, and Knowledge Management in manufacturing. His work focuses on enhancing production efficiency, integrating lean methodologies, and advancing smart manufacturing practices. With 69 publications and 612 citations in Scopus, he holds a h-index of 14, demonstrating significant academic impact. His research bridges theory and practice, providing solutions for complex production challenges while promoting sustainable and innovative industrial systems. Through his contributions, Professor Muniz Jr. has established himself as a thought leader in modern manufacturing and production management.

Citation Metrics (Scopus)

700

500

300

100

Citations
612

Documents
69

h-index
14

Dr. Aamir Saghir | Statistical Process Control | Best Researcher Award

Associate professor at Mirpur University of Science and Technology | Pakistan

Dr. Aamir Saghir, Associate Professor at Mirpur University of Science and Technology (MUST), Pakistan, is recognized for his outstanding work in statistical quality control, probability modeling, and industrial data analytics. His research primarily focuses on developing flexible, robust, and Bayesian control charts for process monitoring in both univariate and multivariate environments. With 49 publications, 567 citations, and an h-index of 15 (Scopus), Dr. Saghir’s contributions are well-established in the international scientific community. He has published extensively in high-impact journals, including Computers & Industrial Engineering, Quality and Reliability Engineering International, Communications in Statistics, and Applied and Computational Mathematics. His collaborative research extends globally, involving advanced modeling for reliability analysis, environmental statistics, and the integration of machine learning with statistical monitoring. His co-authored book, “Introduction to Statistical Process Control” (John Wiley & Sons, 2020), serves as a reference for modern control chart design and applications. Dr. Saghir’s scholarly output demonstrates a balance of theoretical innovation and practical relevance, influencing diverse fields such as manufacturing, environmental studies, and data-driven decision-making. Through supervision of postgraduate students and contributions to academic boards, he has fostered research excellence in Pakistan and abroad. His sustained research impact and leadership affirm his suitability for the Best Researcher Award.

Profiles : Scopus | ORCID | Google Scholar

Featured Publications

Saghir, A., Khadim, A., & Lin, Z. (2017). The Maxwell length-biased distribution: Properties and estimation.Journal of Statistical Theory and Practice, 11(1), 26–40. Citation: 24

Saghir, A., Ahmad, L., Aslam, M., & Jun, C. H. (2019). A EWMA control chart based on an auxiliary variable and repetitive sampling for monitoring process location. Communications in Statistics–Simulation and Computation, 48(7), 2034–2045. Citation: 23

Ahmad, I., Abbas, A., Saghir, A., & Fawad, M. (2016). Finding probability distributions for annual daily maximum rainfall in Pakistan using linear moments and variants. Polish Journal of Environmental Studies, 25(3), 925–937. Citation: 23

Saghir, A. (2015). Phase-I design scheme for $Xˉ\bar{X}$ -chart based on posterior distribution. Communications in Statistics–Theory and Methods, 44(3), 644–655. Citation: 22

Hu, X. L., Zhang, S. Y., Zhang, J., & Saghir, A. (2023). Efficient CUSUM control charts for monitoring the multivariate coefficient of variation. Computers & Industrial Engineering, 179, 109159. Citation: 15