Yu Xiao | Mathematics | Best Researcher Award

Posted on by sciencefather

Assoc Prof Dr. Yu Xiao | Mathematics | Best Researcher Award

Doctoral Supervisor at Harbin Institute of Technology, China.

Yu Xiao, an Associate Professor at Harbin Institute of Technology, holds a Ph.D. in Mathematics and specializes in numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. His research focuses on almost sure stability in stochastic systems under periodic intermittent control, employing advanced methodologies like stochastic analysis and multiple Lyapunov functions. Xiao has collaborated extensively with industry experts, resulting in over 40 SCI-indexed publications covering diverse topics. His contributions highlight practical applications of theoretical frameworks, reflecting his significant impact in both academic research and industrial applications.

Professional Profiles:

Education šŸŽ“

Yu Xiao, born in 1978, completed his Ph.D. at the School of Mathematics, Harbin Institute of Technology, in 2011. He holds the position of Associate Professor at the same institution. His research focuses on numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. This background highlights his extensive academic training, current professional role, and specific research interests in mathematical methodologies applied to complex systems and control theories.

Research and Innovations

Yu Xiao is actively involved in several research areas, focusing primarily on numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. His completed and ongoing research projects include work on periodic intermittent control for almost sure stability of stochastic strict-feedback semi-Markov jump systems, indexed in SCI. He has collaborated extensively with industry experts, contributing to the publication of over 40 SCI papers. Additionally, Yu Xiao has two patents under process and has published two journal articles in prominent scientific databases. He holds membership in the Mathematical Society of Heilongjiang Province, China, demonstrating his commitment to advancing mathematical research and applications.

Contributions

In his recent research, Yu Xiao explores almost sure stability (ASS) for stochastic strict-feedback semi-Markov jump systems (SSSJSs) under periodic intermittent control (PIC). The study systematically designs virtual controllers that culminate in an actual controller, establishing ASS conditions through stochastic analysis and the application of a multiple Lyapunov function method. These conditions are intricately linked to control width and period, effectively reducing conservatism. The research substantiates its findings with compelling simulation examples, showcasing the practical applicability and robustness of the proposed methodologies in enhancing system stability and performance.

Area of Research

Yu Xiao specializes in numerical methods for stochastic differential equations, stability and synchronization theory, and networked control systems. With a Ph.D. from the School of Mathematics at Harbin Institute of Technology and current role as Associate Professor at the same institution, his research spans diverse applications in control theory. His work notably explores almost sure stability in stochastic strict-feedback semi-Markov jump systems under periodic intermittent control, employing innovative methods like stochastic analysis and multiple Lyapunov functions. Xiao’s contributions extend beyond theoretical frameworks, demonstrating practical applications through extensive collaborations with industry experts and a robust publication record in SCI-indexed journals. His dedication to advancing control methodologies underscores his impact in both academic and industrial settings

Publications

  1. Almost sure synchronization of stochastic multi-links semi-Markov jump systems via aperiodically intermittent control
    • Authors: Gao, C., Gu, H., Xiao, Y., Guo, B.
    • Journal: Communications in Nonlinear Science and Numerical Simulation, 2024, 135, 108028
  2. Almost sure exponential synchronization analysis of stochastic strict-feedback systems with semi-Markov jump
    • Authors: Gao, C., Zhang, L., Zhang, H., Xiao, Y.
    • Journal: Engineering Applications of Artificial Intelligence, 2024, 133, 108453
  3. Synchronization of multi-link and multi-delayed inertial neural networks with Markov jump via aperiodically intermittent adaptive control
    • Authors: Guo, B., Xiao, Y.
    • Journal: Mathematics and Computers in Simulation, 2024, 219, pp. 435ā€“453
  4. Dynamical analysis of higher-order rogue waves on the various backgrounds for the reverse spaceā€“time Fokasā€“Lenells equation
    • Authors: Song, J.-Y., Xiao, Y., Zhang, C.-P.
    • Journal: Applied Mathematics Letters, 2024, 150, 108971
  5. Aperiodically synchronization of multi-links delayed complex networks with semi-Markov jump and their numerical simulations to single-link robot arms
    • Authors: Gao, C., Guo, B., Xiao, Y., Bao, J.
    • Journal: Neurocomputing, 2024, 575, 127286
    • Citations: 2
  6. Solitonic interactions and explicit solutions for the (2+1) -dimensional nonlocal derivative nonlinear Schrƶdinger equation
    • Authors: Xiao, Y., Song, J.-Y., Zhang, C.-P.
    • Journal: Nonlinear Dynamics, 2024, 112(5), pp. 3797ā€“3809
  7. Intermittent synchronization for multi-link and multi-delayed large-scale systems with semi-Markov jump and its application of Chua’s circuits
    • Authors: Guo, B., Xiao, Y.
    • Journal: Chaos, Solitons and Fractals, 2023, 174, 113762
    • Citations: 3 (Open access)
  8. Synchronization of Markov Switching Inertial Neural Networks with Mixed Delays under Aperiodically On-Off Adaptive Control
    • Authors: Guo, B., Xiao, Y.
    • Journal: Mathematics, 2023, 11(13), 2906
    • Citations: 3
  9. Soliton solutions and their dynamics of local and nonlocal (2+1)-dimensional Fokasā€“Lenells equations
    • Authors: Song, J.-Y., Xiao, Y., Bao, J.-C., Tang, H.-C.
    • Journal: Optik, 2023, 273, 170486
    • Citations: 1
  10. Intermittent control for synchronization of hybrid multi-weighted complex networks with reaction-diffusion effects
    • Authors: Guo, B., Xiao, Y.
    • Journal: Mathematical Methods in the Applied Sciences, 2023, 46(1), pp. 1137ā€“1155
    • Citations: 4

 

 

Amjad Alipanah | Mathematics | Best Researcher Award

Posted on by sciencefather

Mr. Amjad Alipanah | Mathematics | Best Researcher Award

PhD at University of Kurdistan, Iran.

Amjad Alipanah is an esteemed Associate Professor of Applied Mathematics at the University of Kurdistan, Sanandaj, Iran. Born on September 23, 1974, he has a distinguished academic background with a BSc in Mathematics from the University of Kurdistan and both an MSc and PhD in Applied Mathematics from AmirKabir University, Tehran, Iran. His research focuses on spectral and pseudospectral methods, finite difference methods, calculus of variations, approximation theory, and numerical analysis. With a robust portfolio of journal publications and conference papers, he has significantly contributed to the field. Alipanah is also a dedicated educator, teaching a variety of undergraduate and graduate courses and supervising numerous postgraduate theses. His work has earned him top ranks as a graduate student and a prominent position in the academic community. šŸŒāœØ

Professional Profiles:

Education

Amjad Alipanah received his Bachelor of Science (BSc) degree in Mathematics from the University of Kurdistan, Sanandaj, Iran, in 2000. He then pursued his Master of Science (MSc) in Applied Mathematics at AmirKabir University, Tehran, Iran, specializing in Partial Differential Equations with a focus on Finite Difference Methods. His master’s thesis, titled “Numerical Solution of Sine-Gordon Equation,” was supervised by Professor Mehdi Dehghan. Alipanah continued his academic journey at AmirKabir University, earning a PhD in Applied Mathematics in 2005 with a specialization in Optimal Control. His doctoral research, “Using Cardinal Functions in Spectral Methods,” was supervised by Professor Mohsen Razzaghi, with Associate Professor Mostafa Shamsi serving as his adviser.

Professional Experience

Amjad Alipanah currently holds the position of Associate Professor of Applied Mathematics at the University of Kurdistan in Sanandaj, Iran. His professional journey is marked by his extensive teaching and research contributions in the field of applied mathematics. Throughout his career, he has been involved in various research projects and has published numerous journal articles and conference papers on topics such as spectral and pseudospectral methods, finite difference methods, and numerical analysis. In addition to his research endeavors, Dr. Alipanah has supervised many postgraduate theses, guiding students through complex mathematical problems and innovative solutions. His commitment to education is evident through his teaching of a broad range of undergraduate and graduate courses, including Numerical Solution of Partial Differential Equations, Numerical Methods in Linear Algebra, and Advanced Numerical Analysis. šŸ§‘ā€šŸ«šŸ“ŠāœØ

Research Interest

Amjad Alipanah’s research interests lie predominantly in applied mathematics, with a focus on several specialized areas. These include spectral and pseudospectral methods, which are used for solving differential equations with high accuracy; finite difference methods, which are numerical techniques for approximating solutions to differential equations; and the calculus of variations, which deals with optimizing functionals. He is also deeply engaged in approximation theory, a branch of mathematics that focuses on how functions can best be approximated with simpler functions, and numerical analysis, which involves the development and analysis of algorithms for solving mathematical problems numerically. His diverse research interests reflect his commitment to advancing mathematical methods and their applications in solving real-world problems. šŸ“ššŸ”¢šŸ’”

Award and Honors

Amjad Alipanah has received several prestigious awards and honors throughout his academic career. He graduated first in his class with a Bachelor of Science degree from the University of Kurdistan in 2000. Continuing his academic excellence, he also graduated first in his class with a Master of Science degree from AmirKabir University in Tehran, Iran, in 2002. These accolades highlight his dedication and exceptional performance in the field of mathematics. šŸŽ“āœØ

Research Skills

Amjad Alipanah possesses a wide range of research skills that reflect his expertise in applied mathematics. He has mastery in employing spectral and pseudospectral methods for solving differential equations and optimization problems. His proficiency in finite difference methods allows him to approximate solutions to differential equations effectively. Amjad is also skilled in the calculus of variations, which involves optimization techniques for functional analysis, crucial for understanding complex physical systems. Additionally, his expertise in approximation theory enables him to develop and analyze methods for approximating functions and solving mathematical problems. His extensive experience in numerical analysis involves the development and application of algorithms for solving mathematical problems numerically. These comprehensive skills equip him to tackle complex mathematical challenges and contribute significantly to his field. šŸ“ŠšŸ”

Publications

  1. Numerical solution of singularly perturbed singular third-order boundary value problems with nonclassical sinc method
    • Authors: A. Alipanah, K. Mohammadi, R.M. Haji
    • Year: 2024
    • Citations: 0
  2. On solving some stochastic delay differential equations by Daubechies wavelet
    • Authors: N.M. Shariati, M. Yaghouti, A. Alipanah
    • Year: 2024
    • Citations: 0
  3. Numerical solution of system of second-order integro-differential equations using nonclassical sinc collocation method
    • Authors: M. Ghasemi, K. Mohammadi, A. Alipanah
    • Year: 2023
    • Citations: 3
  4. Numerical solution of third-order singular boundary value problems with nonclassical SE-sinc-collocation and nonclassical DE-sinc-collocation
    • Authors: A. Alipanah, K. Mohammadi, M. Shiralizadeh
    • Year: 2023
    • Citations: 2
  5. Collocation method using auto-correlation functions of compact supported wavelets for solving Volterra’s population model
    • Authors: A. Alipanah, M. Zafari
    • Year: 2023
  6. Numerical solution of the system of second-order integro-differential equations using non-classical double sinc method
    • Authors: K. Mohammadi, A. Alipanah
    • Year: 2023
    • Citations: 3
  7. Numerical solution of third-order boundary value problems using non-classical sinc-collocation method
    • Authors: A. Alipanah, K. Mohammadi, M. Ghasemi
    • Year: 2023
    • Citations: 3
  8. Approximate solutions to the Allenā€“Cahn equation using rational radial basis functions method
    • Authors: M. Shiralizadeh, A. Alipanah, M. Mohammadi
    • Year: 2023
    • Citations: 1
  9. A convergent wavelet-based method for solving linear stochastic differential equations included 1D and 2D noise
    • Authors: N.M. Shariati, M. Yaghouti, A. Alipanah
    • Year: 2023
    • Citations: 2
  10. On the Stability of Filonā€“Clenshawā€“Curtis Rules
    • Authors: H. Majidian, M. Firouzi, A. Alipanah
    • Year: 2022

 

 

Ayyub Sheikhi | Mathematics | Best Researcher Award

Posted on by sciencefather

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: 1351ā€“1370
    • Citations: 0
  2. Convex weak concordance measures and their constructions
    • Authors: Mesiar, R., KolesĆ”rovĆ”, 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: 1ā€“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: 131ā€“146
    • Citations: 3
  5. Convex concordance measures
    • Authors: Mesiar, R., KolesĆ”rovĆ”, A., Sheikhi, A.
    • Year: 2022
    • Journal: Fuzzy Sets and Systems
    • Volume: 441
    • Pages: 366ā€“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: 165ā€“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: 408ā€“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: 984ā€“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: 709ā€“721
    • Citations: 11

 

 

Abdu Qaid Saif Alameri | Mathematics | Best Researcher Award

Posted on by sciencefather

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

University requirements coordinatorĀ  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