Ayyub Sheikhi | Mathematics | Best Researcher Award

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Assoc Prof Dr. Ayyub Sheikhi | Mathematics | Best Researcher Award

Department of Statistics at Shahid Bahonar University of Kerman, Iran.

Ayyub Sheikhi possesses a robust set of research skills honed through years of academic and professional experience. Proficient in both theoretical and applied aspects of statistics and data science, he excels in experimental design, statistical analysis, and modeling techniques. Ayyub demonstrates proficiency in various statistical software packages, including R, and is adept at implementing advanced methodologies such as machine learning algorithms and Bayesian inference. His research skills also extend to data visualization and interpretation, allowing him to effectively communicate complex statistical findings to diverse audiences. Ayyub’s expertise in statistical research methodologies is further augmented by his ability to collaborate across interdisciplinary teams and lead projects from conception to completion. With a keen attention to detail and a commitment to methodological rigor, Ayyub Sheikhi continues to make significant contributions to the advancement of statistical science.

Professional Profiles:

Education

Ayyub Sheikhi pursued his academic journey in statistics and applied mathematics, earning his Ph.D. in Applied Mathematics from Shahid Bahonar University of Kerman, Iran, in 2012. Prior to that, he completed his Master of Science in Statistics at AmirKabir University of Technology, Tehran, Iran, and his Bachelor of Science in Statistics at Shahid Bahonar University of Kerman. His educational background equipped him with a strong foundation in mathematical and statistical principles, which he has since applied in both academic and professional settings, contributing significantly to the field of statistics and data science.

Professional Experience

Ayyub Sheikhi has garnered extensive professional experience in academia, research, and leadership roles. From 2018 to 2020, he served as the Head of the Department of Statistics at Shahid Bahonar University of Kerman, Iran, where he demonstrated his leadership skills in managing departmental affairs and fostering academic excellence. Concurrently, since 2015, he has held the position of Assistant Professor in the Department of Statistics at the same university, contributing to both teaching and research activities. In 2020, he was promoted to the position of Associate Professor, recognizing his scholarly achievements and expertise in the field. Additionally, since 2021, Ayyub has taken on the role of Head of the “Data Mining and Machine Learning” group at the Mahani Mathematical Research Institute, Shahid Bahonar University of Kerman, further showcasing his commitment to advancing statistical research and methodologies. Moreover, he has enriched his professional experience through a research fellowship at the University of Plymouth, UK, during the academic year 2023-2024, broadening his perspective and collaborating with international scholars in the field of statistics and data science.

Research Interest

Ayyub Sheikhi’s research interests encompass a diverse array of topics within the field of statistics and data science. He is particularly interested in Bayesian methods, change-point detection, and dynamic time series analysis, exploring innovative approaches to model complex data structures and uncover temporal patterns. Additionally, he focuses on copula-related techniques for analyzing dependence structures in multivariate data, aiming to develop robust methodologies for financial modeling and risk management. Ayyub also investigates machine learning methods, such as clustering algorithms and support vector machines, with a specific focus on their applications in outlier detection, classification, and regression tasks. Furthermore, he is keen on exploring the intersection of statistics with other disciplines, including economics, medicine, and engineering, to address real-world challenges and advance interdisciplinary research initiatives. Overall, Ayyub’s research interests reflect his dedication to advancing statistical theory and methodology while addressing practical problems across various domains.

Award and Honors

Ayyub Sheikhi, a prominent figure in the field of statistics and data science, has accumulated a wealth of experience and expertise over the years. He has held various academic and research positions, including serving as the Head of the Department of Statistics at Shahid Bahonar University of Kerman, Iran, from 2018 to 2020, and as an Assistant Professor and later an Associate Professor in the same department. Ayyub’s academic journey began with a Ph.D. in Applied Mathematics from Shahid Bahonar University of Kerman, Iran, in 2012, complemented by an M.Sc. in Statistics from AmirKabir University of Technology, Tehran, and a B.Sc. in Statistics from Shahid Bahonar University of Kerman. His scholarly contributions extend beyond academia, as evidenced by his involvement in various visiting appointments, publication of books, development of statistical packages, and leadership in research projects. Ayyub’s commitment to excellence and innovation in statistics continues to drive advancements in the field, positioning him as a respected authority and mentor within the academic community.

Research Skills

Dr. Sheikhi Ayyub possesses a breadth of research skills spanning statistical and mathematical domains, underpinned by a dedication to practical problem-solving. His expertise encompasses statistical inference, where he adeptly employs hypothesis testing, estimation, and model fitting to derive meaningful insights from data. Proficient in data analysis techniques, Dr. Ayyub excels in uncovering patterns and trends within complex datasets, thereby facilitating informed decision-making processes. Moreover, he demonstrates a keen understanding of machine learning algorithms, employing them for tasks ranging from classification and regression to clustering and anomaly detection, thereby enhancing predictive modeling capabilities. Additionally, Dr. Ayyub showcases proficiency in time series analysis, employing various techniques to analyze temporal data, identify patterns, and forecast future values effectively. Furthermore, his expertise extends to Bayesian statistics, copula models, and robust statistical methods, further enriching his analytical toolkit. Proficient in utilizing statistical software packages like R, Python, and MATLAB, Dr. Ayyub applies these skills across interdisciplinary research endeavors, contributing to advancements in fields ranging from healthcare and economics to engineering and finance.

Publications

  1. A two-stage Bridge estimator for regression models with endogeneity based on control function method
    • Authors: Bahador, F., Sheikhi, A., Arabpour, A.
    • Year: 2024
    • Journal: Computational Statistics
    • Volume: 39
    • Issue: 3
    • Pages: 1351–1370
    • Citations: 0
  2. Convex weak concordance measures and their constructions
    • Authors: Mesiar, R., Kolesárová, A., Sheikhi, A., Shvydka, S.
    • Year: 2024
    • Journal: Fuzzy Sets and Systems
    • Volume: 478
    • Pages: 108841
    • Citations: 1
  3. Multivariate Asymmetric Distributions of Copula Related Random Variables
    • Authors: Sheikhi, A., Arad, F., Mesiar, R.
    • Year: 2023
    • Journal: Austrian Journal of Statistics
    • Volume: 52
    • Issue: 4
    • Pages: 1–14
    • Citations: 0
  4. A dimension reduction in neural network using copula matrix
    • Authors: Sheikhi, A., Mesiar, R., Holeňa, M.
    • Year: 2023
    • Journal: International Journal of General Systems
    • Volume: 52
    • Issue: 2
    • Pages: 131–146
    • Citations: 3
  5. Convex concordance measures
    • Authors: Mesiar, R., Kolesárová, A., Sheikhi, A.
    • Year: 2022
    • Journal: Fuzzy Sets and Systems
    • Volume: 441
    • Pages: 366–377
    • Citations: 2
  6. Copula-based Berkson measurement error models
    • Authors: Ziaei, A.R., Zare, K., Sheikhi, A.
    • Year: 2022
    • Journal: Iranian Journal of Fuzzy Systems
    • Volume: 19
    • Issue: 4
    • Pages: 165–175
    • Citations: 0
  7. A heteroscedasticity diagnostic of a regression analysis with copula dependent random variables
    • Authors: Sheikhi, A., Arad, F., Mesiar, R.
    • Year: 2022
    • Journal: Brazilian Journal of Probability and Statistics
    • Volume: 36
    • Issue: 2
    • Pages: 408–419
    • Citations: 0
  8. ON ASYMMETRIC DISTRIBUTIONS OF COPULA RELATED RANDOM VARIABLES WHICH INCLUDES THE SKEW-NORMAL ONES
    • Authors: Sheikhi, A., Arad, F., Mesiar, R.
    • Year: 2022
    • Journal: Kybernetika
    • Volume: 58
    • Issue: 6
    • Pages: 984–995
    • Citations: 1
  9. Asymmetric distributions based on the t-copula
    • Authors: Arad, F., Sheikhi, A.
    • Year: 2022
    • Conference: 9th Iranian Joint Congress on Fuzzy and Intelligent Systems, CFIS 2022
    • Citations: 0
  10. On a generalization of the test of endogeneity in a two stage least squares estimation
    • Authors: Sheikhi, A., Bahador, F., Arashi, M.
    • Year: 2022
    • Journal: Journal of Applied Statistics
    • Volume: 49
    • Issue: 3
    • Pages: 709–721
    • Citations: 11

 

 

Abdu Qaid Saif Alameri | Mathematics | Best Researcher Award

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Assoc Prof Dr. Abdu Qaid Saif Alameri | Mathematics | Best Researcher Award

University requirements coordinator  of University of Science and Technology, Yemen.

Dr. Abdu Qaid Saif Alameri is an accomplished academician and researcher in the field of mathematics. Holding the position of Associate Professor at the Department of Biomedical Engineering, University of Science and Technology, he is recognized for his contributions to both academia and research. Dr. Alameri obtained his Ph.D. from the University of Science and Technology, Sana’a, Yemen, graduating with distinction in 2018. Since then, he has been actively involved in teaching applied mathematics and coordinating university requirements, alongside his research pursuits. His research interests primarily revolve around graph theory and related disciplines, including theoretical computer science, fuzzy graphs, and mathematical nano-science. Dr. Alameri has made significant contributions to these areas through his publications, which include books and numerous articles published in reputable journals indexed in databases like Scopus and Web of Science. Furthermore, he serves as a reviewer and editor for several international journals, contributing to the dissemination of scholarly work and advancing the field.

 

 

Professional Profiles:

Education

Dr. Abdu Qaid Saif Alameri holds both bachelor’s and master’s degrees from Taiz University. He pursued his Ph.D. at the University of Science and Technology, Sana’a, Yemen, where he graduated in 2018 with an excellent grade. Dr. Alameri’s academic journey has been marked by a consistent dedication to excellence, leading to his current role as an Associate Professor of Mathematics at the University of Science and Technology of Yemen. His educational background has equipped him with a robust foundation in applied mathematics, graph theory, and other specialized areas within the field of mathematics.

Professional Experience

Dr. Abdu Qaid Saif Alameri has accumulated 15 years of professional experience, primarily within the academic realm. He currently serves as an Associate Professor of Mathematics in the Department of Biomedical Engineering at the University of Science and Technology. In this role, he fulfills various responsibilities, including lecturing on applied mathematics and coordinating university requirements and basic sciences. Dr. Alameri’s extensive teaching experience spans over 200 courses across diverse educational, research, and administrative domains. Additionally, he has contributed significantly to the field of mathematics through his research endeavors, publication of books and articles, and participation in scientific conferences. His expertise extends to discrete mathematics, graph theory, theoretical computer science, fuzzy graph theory, mathematical chemistry, and mathematical nanoscience. Dr. Alameri’s profound commitment to academia and research is evident in his comprehensive portfolio of scholarly achievements and contributions to the advancement of mathematical knowledge.

Research Interest

Dr. Abdu Qaid Saif Alameri’s research interests encompass various aspects of mathematics, with a focus on discrete mathematics, graph theory, theoretical computer science, fuzzy graph theory, mathematical chemistry, and mathematical nanoscience. He is particularly intrigued by the application of mathematical principles in diverse fields, including biomedical engineering. Through his research, Dr. Alameri aims to explore fundamental mathematical concepts and their practical implications, seeking innovative solutions to complex problems. His interdisciplinary approach underscores the significance of mathematical modeling and analysis in addressing real-world challenges. Additionally, Dr. Alameri is committed to advancing the frontiers of knowledge in his areas of expertise, contributing to the development of novel algorithms, mathematical frameworks, and analytical techniques. His research endeavors reflect a dedication to both theoretical exploration and practical application, with the overarching goal of fostering advancements in mathematical sciences and their interdisciplinary applications.

Award and Honors

Dr. Abdu Qaid Saif Alameri, an Associate Professor of Mathematics at the University of Science and Technology, Yemen, boasts an illustrious career marked by remarkable achievements and contributions to the field of mathematics. With a Bachelor’s and Master’s degree from Taiz University and a Ph.D. from the University of Science and Technology, Sana’a, Yemen, he graduated with distinction in 2018. Currently serving as a faculty member in the College of Engineering at the University of Science and Technology of Yemen, Dr. Alameri holds the position of lecturer in applied mathematics and also serves as the coordinator for university requirements and basic sciences. His expertise spans various domains, including graph theory, theoretical computer science, and mathematical chemistry. Additionally, he is a prolific researcher with numerous publications in esteemed international journals, earning him recognition as a multiple-time recipient of the Best Researcher Award in Engineering and Computer Science. Over his 15 years of teaching experience, Dr. Alameri has delivered more than 200 courses, showcasing his commitment to education and academic excellence.

Research Skills

Dr. Abdu Qaid Saif Alameri brings a wealth of expertise and experience to his role as an Associate Professor of Mathematics at the Department of Biomedical Engineering, University of Science and Technology. With a solid educational background, including a Ph.D. from the University of Science and Technology, Sana’a, Yemen, he graduated with honors in 2018. Since then, he has been an integral part of the academic faculty, actively contributing to both teaching and research endeavors. His academic journey encompasses a diverse range of responsibilities, including lecturing in applied mathematics, coordinating university requirements, and overseeing basic sciences. Furthermore, Dr. Alameri is a dedicated researcher, with a particular focus on graph theory and its branches, such as theoretical computer science, fuzzy graphs, and mathematical nano-science. He has demonstrated his commitment to academic excellence through numerous publications, including books and over fifty-five articles, many of which are indexed in reputable databases like Scopus and Web of Science. Dr. Alameri’s contributions extend beyond research, as he serves as a reviewer and editor for several international journals. Moreover, he has actively participated in scientific conferences, presenting his findings and fostering collaboration within the academic community. With over fifteen years of teaching experience and a track record of scholarly achievements, Dr. Abdu Qaid Saif Alameri continues to make significant contributions to the field of mathematics and its applications in various domains.

Publications

  1. Title: Y-index of some graph operations
    • Authors: A. Alameri, N. Al-Naggar, M. Al-Rumaima, M. Alsharafi
    • Journal: International Journal of Applied Engineering Research (IJAER)
    • Volume: 15
    • Issue: 2
    • Pages: 173-179
    • Year: 2020
    • Citations: 60
  2. Title: Topological indices of the mk-graph
    • Authors: A. Ayache, A. Alameri
    • Journal: Journal of the Association of Arab Universities for Basic and Applied …
    • Volume: 34
    • Year: 2017
    • Citations: 34
  3. Title: Y-coindex of graph operations and its applications of molecular descriptors
    • Authors: A. Alameri, M. Al-Rumaima, M. Almazah
    • Journal: Journal of Molecular Structure
    • Volume: 1221
    • Pages: 128754
    • Year: 2020
    • Citations: 32
  4. Title: Second hyper-zagreb index of titania nanotubes and their applications
    • Author: A. Alameri
    • Journal: IEEE access
    • Volume: 9
    • Pages: 9567-9571
    • Year: 2021
    • Citations: 28
  5. Title: Enumeration of spanning trees in a chain of diphenylene graphs
    • Authors: A. Modabish, M.N. Husin, A.Q. Alameri, H. Ahmed, M. Alaeiyan, M.R. Farahani
    • Journal: Journal of Discrete Mathematical Sciences and Cryptography
    • Volume: 25
    • Issue: 1
    • Pages: 241-251
    • Year: 2022
    • Citations: 27
  6. Title: The hyper-Zagreb index of some complement graphs
    • Authors: M. Alsharafi, M. Shubatah, A. Alameri
    • Journal: Advances in Mathematics: Scientific Journal
    • Volume: 9
    • Issue: 6
    • Pages: 3631-3642
    • Year: 2020
    • Citations: 24
  7. Title: Zagreb indices, Hyper Zagreb indices and Redefined Zagreb indices of conical graph
    • Authors: A. Alameri, M. Shubatah, M. Alsharafi
    • Journal: Advances in Mathematics: Scientific Journal
    • Volume: 9
    • Issue: 6
    • Pages: 3631-3642
    • Year: 2020
    • Citations: 23
  8. Title: On the Hyper-Zagreb coindex of some graphs
    • Authors: M.S. Alsharafi, M.M. Shubatah, A.Q. Alameri
    • Journal: J. Math. Comput. Sci.
    • Volume: 10
    • Issue: 5
    • Pages: 1875-1890
    • Year: 2020
    • Citations: 20
  9. Title: The forgotten index of complement graph operations and its applications of molecular graph
    • Authors: M.S. Alsharafi, M.M. Shubatah, A.Q. Alameri
    • Journal: Open Journal of Discrete Applied Mathematics
    • Volume: 3
    • Issue: 3
    • Pages: 53-61
    • Year: 2020
    • Citations: 17
  10. Title: The Second Hyper-Zagreb Coindex of Chemical Graphs and Some Applications
    • Authors: A. Ayache, A. Alameri, M. Alsharafi, H. Ahmed
    • Journal: Journal of Chemistry
    • Year: 2021
    • Pages: 1-8
    • Citations: 16